FINAL DRAFT UGANDA 
STANDARD  
  FDUS 943  
First Edition  
2012 -mm-dd 
 
 
 Reference number  
FDUS 943: 2012  
© UNBS 2012   
  
Guidelines for production of quality statis tics 
 FDUS 943: 2012  
ii © UNBS 2012  – All rights reserved  
 Compliance with this standard does not, of itself confer immunity from legal obligations  
A Uganda Standard does not purport to include all necessary provisions of a contract. Users are 
responsible for its correct application  
© UNBS 20 12  
All rights reserved. Unless otherwise specified, no part of this publication may be reproduced or utilised in any 
form or by any means, electronic or mechanical, including photocopying and microfilm, without prior written 
permission from UNBS.  
Requests for permission to reproduce this document should be addressed to  
The Executive Director  
Uganda National Bureau of Standards  
P.O. Box 6329  
UKampala  
Uganda  
Tel: 256 41 4 505 995  
Fax: 256 41 4 286 123  
E-mail: HUunbs@infocom.co.ug U 
Web: www.unbs.go.ug  FDUS 943:2012  
© UNBS 2012  – All rights reserved  iii 
 Contents  Page 
UForeword U ................................ ................................ ................................ ................................ .............................  v 
U1 U UScope U ................................ ................................ ................................ ................................ ......................  1 
U2 U UNormative references U ................................ ................................ ................................ ............................  1 
U3 U UTerms and definitions U ................................ ................................ ................................ ...........................  1 
U4 U USymbols (and abbreviated terms) U ................................ ................................ ................................ ........  2 
U5 U UCensuses U ................................ ................................ ................................ ................................ ................  2 
U5.1 U UGeneral U ................................ ................................ ................................ ................................ ...................  2 
U5.2 U UCensus planning U ................................ ................................ ................................ ................................ .... 3 
U5.2.1 U UGeneral U ................................ ................................ ................................ ................................ ...................  3 
U5.2.2 U ULegal basis for a census U ................................ ................................ ................................ .......................  3 
U5.2.3 U UCensus budgeting U ................................ ................................ ................................ ................................ . 3 
U5.2.4 U UCensus calendar U ................................ ................................ ................................ ................................ .... 3 
U5.2.5 U UAdministrative  organization U ................................ ................................ ................................ .................  3 
U5.2.6 U UCensus communication activities U ................................ ................................ ................................ ....... 3 
U5.2.7 U UQuality assurance U ................................ ................................ ................................ ................................ .. 3 
U5.2.8 U UMapping U ................................ ................................ ................................ ................................ ..................  4 
U5.2.9 U UStakeholder consultations U ................................ ................................ ................................ ...................  4 
U5.2.10 U UData processing and analysis U ................................ ................................ ................................ ..............  4 
U5.2.11 U URecruitment and training U ................................ ................................ ................................ ......................  4 
U5.3 U UQuestionnaire development U ................................ ................................ ................................ .................  4 
U5.4 U UCensus pre -test and pilot U ................................ ................................ ................................ .....................  5 
U5.4.1 U UGeneral U ................................ ................................ ................................ ................................ ...................  5 
U5.4.2 U UPre-test U ................................ ................................ ................................ ................................ ...................  5 
U5.4.3 U UPilot census U ................................ ................................ ................................ ................................ ...........  5 
U5.5 U UData collection U ................................ ................................ ................................ ................................ ....... 5 
U5.6 U UData processing & analysis U ................................ ................................ ................................ ..................  6 
U5.7 U UData dissemination U ................................ ................................ ................................ ................................  6 
U5.8 U UCensus evaluation U ................................ ................................ ................................ ................................ . 6 
U5.9 U UCensus documentation U ................................ ................................ ................................ .........................  7 
U6 U USurveys U ................................ ................................ ................................ ................................ ...................  8 
U6.1 U UGeneral U ................................ ................................ ................................ ................................ ...................  8 
U6.2 U USurvey planning U ................................ ................................ ................................ ................................ ..... 8 
U6.2.1 U UGeneral U ................................ ................................ ................................ ................................ ...................  8 
U6.2.2 U USurvey plan U ................................ ................................ ................................ ................................ ............  8 
U6.2.3 U UStakeholder c onsultations U ................................ ................................ ................................ ...................  8 
U6.2.4 U URecruitment and training U ................................ ................................ ................................ ......................  8 
U6.2.5 U UAnalysis plan U ................................ ................................ ................................ ................................ .........  9 
U6.2.6 U UQuality assurance plan U ................................ ................................ ................................ .........................  9 
U6.3 U USurvey design U ................................ ................................ ................................ ................................ ........  9 
U6.4 U USurvey instruments U ................................ ................................ ................................ ...............................  9 
U6.5 U USurvey pre -test and pilot U ................................ ................................ ................................ ....................  10 
U6.5.1 U UGeneral U ................................ ................................ ................................ ................................ .................  10 
U6.5.2 U UPre-test U ................................ ................................ ................................ ................................ .................  10 
U6.6 U UData collection U ................................ ................................ ................................ ................................ ..... 11 
U6.7 U UData processing and analysis U ................................ ................................ ................................ ............  11 
U6.8 U USurvey response rates U ................................ ................................ ................................ ........................  12 
U6.9 U UData coding and standard classifications U ................................ ................................ ........................  12 
U6.10 U UProtection of data U ................................ ................................ ................................ ................................  12 
U6.11 U USurvey evaluation U ................................ ................................ ................................ ................................  13 FDUS 943: 2012  
iv © UNBS 2012  – All rights reserved  
 U6.12 U UDeveloping estimates and projections U ................................ ................................ .............................  14 
U6.13 U UInference and comparisons U ................................ ................................ ................................ ...............  15 
U6.14 U UReview information for dissemination U................................ ................................ ..............................  15 
U6.15 U UData release and dissemination U ................................ ................................ ................................ ........  16 
U6.16 U UData confidentiality and disclosure for dissemination U ................................ ................................ ... 18 
U6.17 U USurvey documentation U ................................ ................................ ................................ .......................  18 
U6.18 U URelease of public -use micro data U ................................ ................................ ................................ ...... 20 
U6.19 U URevisions to published data U ................................ ................................ ................................ ..............  21 
U7 U UAdmi nistrative data U................................ ................................ ................................ .............................  21 
U8 U UIndicators and index numbers U ................................ ................................ ................................ ...........  22 
U8.1 U UIndicators U ................................ ................................ ................................ ................................ .............  22 
U8.2 U UIndex numbers U ................................ ................................ ................................ ................................ .... 22 
UAnnex  A (normative)  Statistics Production Cycle U ................................ ................................ .......................  24 
UAnnex  B (informative)  UN Fundam ental Principles for Official Statistics U ................................ ................  25 
UAnnex  C (informative)  Rules for statistical meta data management U ................................ .........................  27 
UBibliograph y U ................................ ................................ ................................ ................................ .....................  29 
 FDUS 943:2012  
© UNBS 2012  – All rights reserved  v 
 Foreword  
Uganda National Bureau of Standards (UNBS) is a parastatal under the Ministry of Tourism, Trade and 
Industry established under Cap 327 , of the Laws of Uganda.  UNBS is mandated to co -ordinate the 
elaboration of standards and is  
(a) a member of International Organisation for Standardisation (ISO) and  
(b) a contact point for the WHO/FAO Codex Alimentarius Commission on Food Standards, and  
(c) the National Enquiry Point on TBT/SPS Agreements of the World Trade Organisatio n (WTO).  
The work of preparing Uganda Standards is carried out through Technical Committees. A Technical 
Committee is established to deliberate on standards in a given field or area and consists of representatives of 
consumers, traders, academicians, manuf acturers, government and other stakeholders.  
Draft Uganda Standards adopted by the Technical Committee are widely circulated to stakeholders and the 
general public for comments. The committee reviews the comments before recommending the draft standards 
for approval and declaration as Uganda Standards by the National Standards Council.  
Committee membership  
The following organisations were represented on the Technical Committee on Applied Statistical Methods, 
UNBS/TC 17, during the development of this standar d: 
 Bank of Uganda  
 Ministry of Education & Sports  
 Ministry of Finance , Planning & Economic Development  
 Ministry of Health  
 School of Statistics & Applied Economics, Makerere University  
 Uganda Bureau of Statistics  
 Uganda National Bureau of Standards  
 Uganda Na tional Council for Science & Technology  
 Uganda Revenue Authority  
 FDUS 943: 2012  
vi © UNBS 2012  – All rights reserved  
 Introduction  
Statistical standards facilitate  quality assurance in the data production process as well as the final products , 
and provide a logical and coherent structure for collecting inf ormation.  These standards support the 
maintenance  of a unified statistical service that meets the needs of government and society.  
Uganda Bureau of Standards (UBOS)  is responsible for promoting standardization in the collection, analysis 
and publication of  statistics to ensure quality, adequacy of coverage and reliability of statistics information.   
UBOS underlines data quality as  a key determinant of its proficiency in the production of useful statistical 
products to inform national planning.   
This standa rd provide s guidance on the use and appropriate implementation of the guidelines for production 
of quality statistics . Variations from the agreed standard by different data producers in the N ational Statistics 
System  (NSS) are not encouraged . All personnel  involved in statistical activities are responsible for ensuring 
that quality has high priority in the design and implementation of statistical methods and procedures under 
their control.  
 FINAL DRAFT UGANDA STANDARD  FDUS 943: 2011  
 
© UNBS 2012 – All rights reserved  1 
 Guidelines for production of quality statistics  
0B1 Scope  
This Final Draft Uganda Standard provides guidelines that promote the application of best statistical practices 
for producing quality national statistics. These guidelines cover the three main sources of quantitative data 
namely censuses, surveys, and administrat ive records.  
1B2 Normative references  
The following referenced documents are indispensable for the application of this document. For dated 
references, only the edition cited applies. For undated references, the latest edition of the referenced 
document (i ncluding any amendments) applies.  
US ISO  3534 -1, General statistical terms and terms using probability  
US ISO 3534 -2, Applied statistics  
US ISO 3534 -3, Statistics — Design of experiments  
FDUS 942 , Code of Practice for the production of official statistics  
Compendium of Statistical Concepts and definitions  
National Statistical Meta Data Dictionary  
2B3 Terms and definitions  
For the purposes of this standard, the terms and definitions given in US ISO 3534 -1, US ISO 3534 -2, US ISO 
3534 -3, Compendium of Statist ical Concepts  and Definitions  and National Statistical Meta Data Dictionary  
shall apply.  FDUS 943: 2012  
2 © UNBS 2012  – All rights reserved  
 3B4 Symbols (and abbreviated terms)  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4B5 Censuses  
8B5.1 Gene ral 
A census covers a precisely defined territory (for example, the entire country or a sample) . In a census, 
individual units of interest are separately enumerated and their characteristics recorded. Examples of 
individual units include  
 business for busi ness censuses,  
 school for school censuses,  
 holding for agricultural censuses and  
 household, a housing unit and/or individuals for population and housing censuses .   BOU  Bank of Uganda  
CARIS  Classifications and Related International Standards System  
COICOP  Classification of Individual Consumpt ion According to Purpose  
CPC  Central Product Classification  
FAO  Food and Agricultural Organisation  
FPOS  Fundamental Principles of Official Statistics  
GDDS  General Data Dissemination System  
HS Harmonised Commodity Description and Coding System  
ISIC International Standard Industrial Classification  
ISO  International Organization for Standardization  
MDAs  Ministries, Departments and Agencies  
NSOs  National Statistical Offices  
NSS National Statistical System  
ONS  Office for National Statistics  
SDDS  Special Data Dissemination Standards  
SNA  System of National Accounts  
UBOS  Uganda Bureau of Statistics  
UNBS  Uganda National Bureau of Standards  
WHO  World Health Organisation  
WTO  World Trade Organisation  FDUS  943: 2012  
© UNBS 2012  – All rights reserved  3 
 The data collected should refer to a well defined reference period. Censuses should be t aken at regular 
intervals so that comparable information is made available in a fixed sequence.  Censuses are the basis for 
developing sampling frames for surveys.  
9B5.2 Census planning  
38B5.2.1 General  
The development of plans for a census includes the e arly preparation detailing a set of strategic aims and 
objectives used to guide the implementation process . Experiences f rom previous census es, understanding 
user requirements and assessing changes in society and technology  form the  starting point for deve loping  
census  objectives . The s et standards form a benchmark  against which outcomes can be assessed to help 
determine the success of a census.  
The decision regarding the method of enumeration should be taken at an early stage on the basis of thorough 
testing of the various altern atives in terms of their costs and their operational feasibility.  
The guidelines  in 4.2.2 – 4.2.11  should be considered during census planning . 
39B5.2.2 Legal basis for a census  
All censuses should be conducted in accordance with t he prevailing statistical legislation. Legal authority for 
the census is required for  
 fixing primary administrative responsibility,  
 obtaining the necessary  resources  and  
 determining the general scope and timing of the census .  
40B5.2.3 Census budgeting  
A comprehensive financial estimate of each census activity should be made  for effective planning and control 
of the census .   
41B5.2.4 Census calendar  
A calendar or timetable indicating the sequence and estimated duration of each activity  of the census  should 
be drawn up to guide the entire census process .  
42B5.2.5 Administrative  organization  
The role s and relationship s of the various executive and advisory organs  at national, and sub-national levels  
are useful in the planning and preparations of a census  and should therefore be clearly spelt out . 
43B5.2.6 Census communication activities  
A comprehensive communication strategy for a census which covers data  users , providers, producers and  the 
general public  should be developed  and should be consistent with the overall census strategy.   
44B5.2.7 Quality assurance  
Quality and performance measurement and process control systems should be developed to monitor data 
collection activities and integrated into the data production cycle.  A census should have a well documented 
operational quality assurance plan.  FDUS 943: 2012  
4 © UNBS 2012  – All rights reserved  
 45B5.2.8 Mapping  
Institutions undertaking the census es should develop continuous cartographic capabilit ies to serve their 
specialized needs. The mapping exercise should be preceded by an assess ment of the exi sting maps to 
determine the appropriate technology for develop ing new maps , if necessary.  
46B5.2.9 Stakeholder consultations  
There should be focused extensive consultations where stakeholders clarify and specify their data 
requirements. A reasonable trade -off between the objectives and response burden should be considered.  
47B5.2.10 Data processing and analysis  
The type of data processing equipment  should be determined well  in advance of the scheduled date of 
enumeration, in order to allow for appropriate  questionnaire design and proper preparation of instructions to 
enumerators, development of coding schemes, specification of data handling controls and procedures, and 
recruitment and training of data processing personnel.  
Control  measures should be develo ped to  ensure an uninterrupted flow of work through the various stages 
from receipt of the census questionnaires through preparation of the database and final tabulations.  
48B5.2.11 Recruitment and training  
Required personnel to support the census exercise  should be recruited in advance. Interviewers and other 
staff that interface  with respondents should be trained and equipped with skills  or techniques in  obtaining 
respondent cooperation and building rapport with respondents.  Techniques for building rappo rt include 
respect for respondents‟ rights, follow -up skills, knowledge of the goals and objectives of the data collection, 
and knowledge of the uses of the data.  The data collection protocol  or manual  should be use d by the field 
staff. Training  for field staff on new protocols  should be conducted as well as  refresher training on a routine, 
recurring cycle .  
10B5.3 Questionnaire  development   
The development  of a census questionnaire involves  designing and pre -testing of the in strument through 
stakeholder en gagement , taking into consideration the method of enumeration and the data to be collected . 
The criteria below serves as a guide in the development of the questionnaire:  
a) a tabulation plan should precede and inform the design of the questionnaire;  
b) questions  should not be ambigu ous; 
c) questions should not be offensive ;  
d) questions should not be leading the respondent to a specific answer;  
e) questions should flow logically starting from the simple general information to the more detailed 
including extremely sensiti ve issues;  
f) related topics should, as much as possible, be covered in a single questionnaire in order to minimize 
respondent fatigue;  
g) the designing of the questionnaire should take into consideration the technology to be employed for 
data processing and an alysis;  
h) where necessary, s pecial provision should be made  for transla tion; and  
i) whenever possible, pre -corded responses should be used in census questionnaires with numerical or 
alphanumerical codes being printed next to each category.  FDUS  943: 2012  
© UNBS 2012  – All rights reserved  5 
 11B5.4 Census pre-test and pilot  
49B5.4.1 General  
In determining the effectiveness of the census instruments, both the pre -test and pilot should be undertaken.  
While a pre -test can be work in progress during the design of the instruments, a pilot census is a more 
detailed undertaking that is normally conducted  one year prior to the actual census.  
50B5.4.2 Pre-test 
A pre -test determine s the strengths and weaknesses of the census instrument in terms of format, wording , 
appropriateness of codes, and sequence among others. It is normally administered to a very small sample of 
respondents, taking into consideration the variations in the study population. The pre-test should test 
specifically for:  
a) question ambiguity, flow, consistency, redundancy, sensitivity and reliability,  
b) time required to administer the questionnaire;  
c) validity of the questions determined by how well it measures the purpose/objective it is intended to 
measure.  
d) after the pre-test, enumerators must share their experiences in order to improve the census 
questionna ire. 
51B5.4.3 Pilot census  
The pilot  census is a mock census that should be conducted during a period comparable to the one in which 
the actual census will be conducted using the actual census instruments. Appropriate sampling techn iques 
should be employed  to ensure that all issues to be test ed are taken into consideration.  The pilot census 
should test:  
a) the operational feasibility of the census undertaking including human and financial resource 
requirements, logistics, publicity among others;  
b) the overall re spondent interest and attention;  
c) the suitability of the entire census administrative structure;  and 
d) data processing and analysis procedures.  
12B5.5 Data collection  
In a census, all the units of interest such as households, businesses, agricultural holding s, and housing units 
are enumerated. However, for some specialised censuses like agricultural census and Hcensus of business 
e Hstablishments , a large sample is used instead of total coverage. This is in agreement with the law of inertia of 
large numbers which states that large groups or aggregate of data show a higher degree of stability than small 
ones. T he respondent should be a knowledgeable person in the relevant unit of interest preferably the head of 
that unit. The reference  period for any census should be clearly spelt out. The following guidelines should be 
applied during data collection : 
a) selected enumerators should be well facilitated to locate and visit each and every enumeration unit ; 
b) data collection should be undertaken  during a period when the census is likely to be most successful 
and to yield the most reliable data ; and  
c) rigorous supervision should be undertaken particularly in the initial phase of the enumeration exercise, 
to facilitate the correction of inefficiencie s and maintain satisfactory progress during the enumeration 
period.  FDUS 943: 2012  
6 © UNBS 2012  – All rights reserved  
 13B5.6 Data processing & analysis  
It is critical that data processing and analysis are undertaken in tandem with the census tabulation plan.  A 
successful  data processing operation is depe ndent on effective  collaboration, at all levels, be tween the data 
processing  and the census technical team.  The following guidelines should be applied during data processing 
and analysis : 
a) data entry applications should be developed and tested before embark ing on the data capture ; 
b) appropriate pre -coding and editing should be undertaken before data entry ;  
c) coding should be based on the code books and standard classifications ;  
d) regular data back -ups should be undertaken and stored preferably at off -site locati ons;  
e) double data entry is recommended where resources permit ; 
f) appropriate imputation should be applied for missing data ; and   
g) a master file containing original clean data records should be maintained.  
14B5.7 Data dissemination  
A census is not complete unt il the information collected is made available to potential users in a form suited to 
their needs. The information may be included in published tables and reports or monographs for general 
distribution, produced as tables in unpublished form for limited di stribution or stored in a database and 
supplied upon request, or disseminated online.  The following guidelines should be applied during data 
sissemination : 
a) information should be disseminated in line with the overall communication strategy;  
b) data and informa tion to be shared should observe confidentiality principles;  
c) relevant metadata should be availed and/or accessed in a standard format;  
d) the data should be disseminated in a way that facilitate s widespread use; 
e) published census material  should be  subject to  copyright rules;  
f) the c hoice of dissemination media should be guided by the context and  the intended categories of 
users ; and  
g) a comprehensive list of key stakeholder should be maintained.  
15B5.8 Census evaluation  
The purpose of census evaluation is to prov ide users with a level of confidence when utilizing the data, and to 
explain errors in the census result. Census evaluation is a critical ingredient in a continuous census 
improvement program.  There are various tools that can be used for census evaluation  including  Post 
Enumeration Survey (PES) and demographic analysis. The evaluation should assess the degree of coverage 
and content errors registered during census enumeration in order to improve the current census results and 
inform the design of future cen suses.  
The following guidelines should be followed when conducting a census evaluation : 
a) effective evaluation mechanisms focused on census results should serve as a basis for constructing a 
best estimate of census aggregates, such as the total population, o r to provide census results 
adjusted to take into account identified errors.  FDUS  943: 2012  
© UNBS 2012  – All rights reserved  7 
 b) the decision on whether to measure coverage error, content error or a combination of the two should 
be made in advance. In addition, both gross and net error should be considered when developing the 
overall evaluation plan.  
c) numerous methods to estimate the coverage and content error of censuses should be considered for 
example; simple techniques of quality assurance such as internal consistency checks. Comparisons 
of results with o ther data sources including previous censuses, current household surveys and/or 
administrative records. Such comparisons may be made in aggregate form where comparisons of the 
overall estimates from two sources (net error only) are made.  
d) the design of a PES is complex and should therefore be done carefully depending on the available 
alternatives. These will also depend on whether a single or dual system estimation will be utilized ; and  
e) a periodic evaluation report  should be produce d, for example , a methodol ogy report that itemizes all 
sources of identified error for recurring censuses.  Where possible, provide estimates or bounds on 
the magnitudes of these errors; discuss the total error model for the census; and assess the census in 
terms of this model.  
16B5.9 Census documentation  
Documentation involves the collection of material that provides a description of the activity. Census  
documentation provides a description of the statistical production process and is presented in various formats 
(that is,  electro nic or hard copy) . Census documentation includes all information necessary to analyze the 
data properly  and should include the following:  
a) description of variables used to uniquely identify records in the data file;  
b) description of the census design, inclu ding unit identifiers to be used for analysis;   
c) final instrument(s) or a facsimile thereof for censuses conducted.  
d) definitions of all variables, including all modifications;  
e) data file layout;  
f) descriptions of constructed variables on the data file that are computed from responses to other 
variables on the file;   
g) descriptions of known data anomalies and corrective actions;  
h) comparisons with independent sources, if available;  
i) overall unit response rates and non -response bias analyses (if applicable).  
Census documentation should  be readily accessible to users, unless it is necessary to restrict access to 
protect confidentiality. The following guidelines should be applied for census  documentation : 
a) provide complete census  documentation for all data files and  the entire census pr ocess. This 
documentation should be done according to the statistics archival policy ; and  
b) retain all census  documentation according to appropriate statistics archival policies. Data archiving 
should be well managed, such that data are  available for historical research in the future years.  FDUS 943: 2012  
8 © UNBS 2012  – All rights reserved  
 5B6 Surveys  
17B6.1 General  
A survey covers a precisely defined part of the entire population. Surveys are undertaken for businesses, 
schools, agricultural holdings, markets and households among other s.  The data collected refer s to a well 
defined reference period. Surveys are preferably undertaken at regular intervals so that comparable 
information is made available in sequence.   
18B6.2 Survey planning  
52B6.2.1 General  
The planning process for a surv ey involves the definition of objectives, the current and potential user 
requirements and the key questions and/or issues to which analysis will be directed. Experiences from 
previous surveys and assessment of changes in society and technology  form the sta rting point for developing 
the objectives.  The guidelines  in 5.2.2 – 5.2.6  should be followed when planning for a survey;  
53B6.2.2 Survey plan  
An agency initiating a survey should have a well written plan that includes:  
a) a justification , goals and objective s, hypotheses, and definitions of key variables .   
b) a review of related literature  
c) the scope of the survey  
d) detailed budget;  
e) a survey design and 
f) standard elements of project management, the target completion dates, the resources needed to 
complete each ac tivity, and risk  mitigation . 
All surveys should be conducted in accordance with the prevailing national and international legislation.  
The choice of the data collection method should be determined apriori.  
54B6.2.3 Stakeholder consultations  
Consultations w ith stakeholders are important to identify their requirements and expectations.  There should be 
focused extensive consultations where stakeholders clarify and specify their data requirements. A reasonable 
trade -off between the objectives and response burde n should be considered.  
55B6.2.4 Recruitment and training  
Required personnel to support the survey exercise should be recruited in advance. Interviewers and other 
staff that interface  with respondents should be trained and equipped with skills/techniques in obtaining 
respondent cooperation and building rapport with respondents.  Techniques for building rapport include 
respect for respondents‟ rights, follow -up skills, knowledge of the goals and objectives of the data collection, 
and knowledge of the uses o f the data.  The data collection protocol  or manual  should be use d by the field 
staff. Training  for field staff on new protocols  should be conducted as well as  refresher training on a routine, 
recurring cycle . FDUS  943: 2012  
© UNBS 2012  – All rights reserved  9 
 56B6.2.5 Analysis plan  
A plan for the analysis of survey data should be developed in line with the tabulation plan prior to the start of a 
specific analysis .  This is  to ensure that statistical tests are used appropriately and that adequate resources 
are available to complete the analysis.  The followin g should be included in the analysis plan  
a) an introduction that describes the purpose, the research question, relevant literature, data sources 
(including a brief description of the survey data and any limitations of the data), tabulations expected, 
key var iables to be used in the analysis, type of analysis, and significance level to be used where 
applicable;  
b) table and figure shells that support the analysis; and  
c) a framework for technical notes including the history of the survey program, data collection m ethods 
and procedures, sample design, response rates and the treatment of missing data, weighting 
methods, computation of standard errors, instructions for constructed variables, limitations of the data, 
and sources of error in the data.  
57B6.2.6 Quality assurance plan  
Quality and performance measurement and process control systems should be developed to monitor data 
collection activities and integrated into the data production cycle.  A survey should have a well documented 
operational quality assurance pla n. 
19B6.3 Survey design  
A survey design involves the identification of the target population, sampling frame, sampling techniques, the 
data collection instruments and methods, realistic timetable and cost estimate, and appropriate statistical 
methods.  Th e size and design of the sample must reflect the level of detail needed in tabulations and other 
data products, and the precision required of key estimates.  Documentation of each of these activities and 
resulting decisions must be maintained in the survey  files for use in documentation.  The following guidelines 
should be followed when designing a survey;  
a) the frame for the survey should be clearly defined and updated where necessary prior to the survey 
design ;  
b) where a sampling frame is non -existent, approp riate methods should be used to construct it ; 
c) frames for the planned sample survey should be appropriate for the study design and must be 
evaluated against the target population for quality ; 
d) an appropriate sampling technique should be employed taking into account the probabilistic and/or 
non-probabilistic sampling methods ; 
e) a representative sample should be developed taking into account the objectives of the survey, 
precision and the available financial resources ; 
f) any use on non -probabilistic methods should be justified statistically ; 
g) appropriate sample weights should be generated ; 
20B6.4 Survey instruments  
The development  of survey  instruments  involves  the design and pre -test of the  questionnaire through 
stakeholder engagement , taking into consideration the method of interview  and the data to be collected . It also 
involves development of instruction manuals, code lists/standard classifications among others. The criteria 
below serve as a guide in the development of the instruments:  FDUS 943: 2012  
10 © UNBS 2012  – All rights reserved  
 a) a tabulation plan should pre cede and inform the design of the questionnaire ; 
b) questions should not be ambiguous ; 
c) questions should not be offensive;  
d) questions should not be leading the respondent to a specific answer;  
e) questions should flow logically starting from the simple general in formation to the more detailed 
including extremely sensitive issues ; 
f) related topics should, as much as possible, be covered in a single questionnaire in order to minimize 
respondent fatigue ; 
g) the designing of the questionnaire should take into consideration  the technology to be employed for 
data processing and analysis ; 
h)  where necessary, special provision should be made for translation ; 
i) whenever possible, pre -coded responses should be used in census questionnaires with numerical or 
alphanumerical codes being  printed next to each category ; and  
j) instruction manuals and code lists should be developed before training of interviewers.  
21B6.5 Survey pre-test and pilot   
58B6.5.1 General  
In determining the effectiveness of the survey instruments, both the pre -test and  pilot should be undertaken.  
While a pre -test can be work in progress during the design of the instruments, a pilot survey is a more detailed 
undertaking.  
59B6.5.2 Pre-test 
A pre-test determines the strengths and weaknesses of the survey instrument in te rms of format, wording, 
appropriateness of codes, and sequence among others. It is normally administered to a very small sample of 
respondents, taking into consideration the variations in the study population. The pre-test should test 
specifically for:  
a) question ambiguity, flow, consistency, redundancy, sensitivity and reliability ;  
b) time required to administer the questionnaire ; 
c) validity of the questions determined by how well it measures the purpose/objective it is intended to 
measure ; and   
d) after the pre-test, interviewers should  share their experiences in order to improve the survey 
questionnaire.  
6.5.3 Pilot survey  
The pilot survey  is a mock survey .  Appropriate sampling techniques should be employed to ensure that all 
issues to be tested are taken into co nsideration. The pilot survey  should test:  
a) the operational feasibility of the survey  undertaking including human and financial resource 
requirements, logistics, publicity among others;  
b) the overall respondent interest and attention;  FDUS  943: 2012  
© UNBS 2012  – All rights reserved  11 
 c) the suitability of the entire survey administrative structure;  and 
d) data processing and analysis procedures.  
22B6.6 Data collection  
In a survey, selected units such as households, businesses, agricultural holdings, and housing units are 
interviewed. The respondent should be a kn owledgeable person in the relevant unit of interest preferably the 
head of that unit. The reference period for any survey should be clearly spelt out.  The following guidelines 
should be considered : 
a) the data collection instrument should be administered in a  manner that minimizes respondent burden, 
while maximizing data quality ;   
b) methods to reduce item non -response should be employed ; 
c) in order to maximize response rates and improve data quality : 
 the data collection period should be  adequate ,  
 the data collec tion materials should be forwarded to respo ndents in advance  whenever possible,  
and 
 adequate follow -up should be done;  
d) the data collection manuals should be utilized by the field staff ; and  
e) best practice mechanisms should be implemented to minimize intervi ewer falsification, such as 
monitoring interviewers, in -field validation and re -interviewing respondents;  
23B6.7 Data  processing and analysis  
It is critical that data processing and analysis are undertaken in tandem with the survey design.  A successful  
data processing operation is dependent on effective  collaboration, at all levels, be tween the data processing 
and the survey  technical team.  The following guidelines should be applied : 
a) data entry applications should be developed and tested before embarking o n the data capture ; 
b) appropriate pre -coding and editing should be undertaken before data entry ; 
c) coding should be based on the code books and standard classifications ; 
d) regular data back -ups should be undertaken and stored preferably at off -site locations ; 
e) double data entry is recommended where resources permit ; 
f) appropriate imputation should be applied for missing data ;  
g) a master file containing original clean data records should be maintained ; 
h) appropriate weights should be used during analysis ; and  
i) adjustment s should be made to the initial weight to cater for non -response.   FDUS 943: 2012  
12 © UNBS 2012  – All rights reserved  
 24B6.8 Survey response rates  
Surveys are designed  to achieve the highest practical rates of response, commensurate with the importance 
of the survey , respondent burden, and data collectio n costs . This is to ensure that survey results are 
representative of the Htarget population H so that they can be used with confidence to inform decisions.  
Non-response has two effects on results , one contribut es to bias of estimates when non -respondents differ 
from respondents in the characteristics measured  and the other contribut es to a decrease in the accuracy of 
the survey estimates resulting from the smaller effective sample size.  Adjustment s are subsequently made to 
data to compensate for non -response (for example,  weighting adjustments or imputation) .  The following 
guidelines should be considered : 
a) the response rate should be computed using standard formulae for every survey ;   
b) prior to dat a collection, the expected unit response rates at each stage of data collection should be 
identified, based on content, use, mode, and type of survey ; and  
c) decisions regarding adjustment or imputation of data for item non response should be based on how 
the data will be used, the non response analysis and prior experience.   
25B6.9 Data coding and standard classifications  
International standard classifications for the respective data types that is , trade, national accounts, and pri ces 
etc) should be adopted and applied.  Where possible, international classifications can also be customized to 
country specific products, activities etc which may not be clearly shown in the international coding. The 
following guidelines should be used : 
a) appropriate coding nomenclat ure to the specific data variables including provision for missing data 
should be adapted ;   
b) when converting text data to codes to facilitate easier analysis, standardized codes should be used, if 
they exist ; 
c) when setting up a manual coding process to conv ert text to codes, create a quality assurance process 
that verifies the different codes used for the respective data sets/types.  
d) establish a Classifications and Related International Standards System (CARIS) which will be a 
central repository for all class ifications, concordances and coding indexes for storing and accessing 
classifications. If established, this system will do the following:  
i. use database technology to provide centralized classification storage, maintenance and access 
facilities for classific ation data that are used both in the development and processing of surveys 
and in the subsequent analysis and evaluation of the data ; 
ii. help reduce the time and resources required when developing surveys and to contribute to 
improved data quality by supporti ng the use of standard classifications ; and  
iii. facilitate the comparison and analysis of data by storing concordances . 
26B6.10 Protection of data  
Data may only be used for the specific purposes for which it was collected. Data protection creates rights for 
those who have their data processed and stored, and those who store  the data. The following guidelines 
should be applied : 
a) implement safeguards and data protection policies that preserve the data collected on respondents.  FDUS  943: 2012  
© UNBS 2012  – All rights reserved  13 
 b) for all surveys, appropriate procedu res and mechanisms should be established to ensure protection of 
the data during the production, use, storage, transmittal, and disposition ; 
c) ensure that : 
i. individually -identifiable survey data are protected;  
ii. data systems and electronic products are protect ed from unauthorized intervention ; and  
iii. data files, network segments, servers, and desktop computer s are electronically secure from 
malicious software and intrusion ; 
d) ensure controlled access to data sets so that only specific, named individuals working on a  particular 
data set can have read only, write only, or both read and write access to the data set.  Data set 
access rights should be periodically reviewed by the project manager.  
e) all temporary staff engaged in a particular survey should swear the oath of secrecy as stipulated in the 
statistical legislation .  In addition individuals or research institutions using the data for further analysis 
should swear an oath of secrecy.  However, appropriate mechanisms should be adopted to 
anonymise the individual reco rds before they are used for further analysis.   
27B6.11 Survey  evaluation  
Survey  evaluation  involves  evaluating the final statistical output in light of the original objective of the statistical 
activity /survey . Such information allows users to make infor med interpretations of the survey results, and also 
facilitates  improve ment  for future surveys. The general types of data quality evaluation used include:  
a) macro editing or quality validation  which is a  process of reviewing data before official release to 
ensure that erroneous data are not released, or to identify data of marginal quality.  
b) sources of error studies: provide quantitative information on specific sources of error in the data. 
While timeliness is still important, the results of these studies are often available only after the official 
release of the data.  
c) estimation of the effects of potential non -sampling errors including measurement errors; non -response 
error; coverage error; and processing error.  
The following guidelines  should be applied when performing survey  evaluation : 
a) evaluate the quality of the data and make the evaluation results available to users ( that is through 
technical notes and documentation included in reports of results or through a separate report ); 
b) include an evaluation compone nt in the survey plan that assesses survey procedures, results, and 
errors. The following sources of error should be evaluated:  
i. coverage errors, which consist of omissions, erroneous inclusions, and duplications in the frame 
used to conduct the survey ; 
ii. non-response errors, which occur when the survey fails to get a full response ; 
iii. measurement errors, which occur when the response received differs from the „true‟ value, and 
can be caused by the respondent, interviewer, questionnaire, mode of collection, or th e 
respondent‟s record -keeping system ; 
iv. processing errors, which can occur at the subsequent steps of data editing, coding, capture, 
imputation and tabulation ; and  
v. sampling errors, which occur when the results of the survey are based on a sample  rather than 
the entire population ; FDUS 943: 2012  
14 © UNBS 2012  – All rights reserved  
 c) review past surveys similar to the ones being planned to determine likely sources of error and the 
appropriate evaluation problems that are likely to be encountered ; and   
d) involve both internal and external users in setting the object ives for the data evaluation program and 
the overall evaluation process.  
The following macro editing and quality validation methods should be used:  
a) checks of consistency with external sources of data, for example from other surveys or from previous 
instanc es of the same survey ; 
b) internal consistency checks, for example calculation of ratios that are known to lie within certain 
ranges (sex ratios, average value of commodities, etc.) ; 
c) unit-by-unit reviews of the largest contributors to aggregate estimates, typ ically in cases of business, 
household and health surveys ; and  
d) debriefings with staff involved in the collection and processing of data.  
28B6.12 Developing estimates and projections  
Generally accepted  theory and methods should be used when deriving direct survey -based estimates, as well 
as model -based estimates and projections .  Error estimates are calculated and disseminated to support 
assessment of the appropriateness of the estimates or projections.  The following guidelines should be 
considered when dev eloping estimates and projections : 
a) prior to developing estimates, establish criteria for determining when the error (both sampling and 
non-sampling) associated with a direct survey estimate, model -based estimate, or projection is too 
large to publicly rele ase the estimate/projection ; 
b) develop direct survey estimates by applying weights appropriate for the sample design to calculate 
population estimates.  (An agency may employ an alternative method (e.g., ratio estimators) to 
calculate its population estimate s);  
c) use auxiliary data to improve precision and/or reduce the error associated with direct survey 
estimates ; 
d) calculate variance estimates by a method appropriate to the survey‟s sample design, taking into 
account probabilities of selection, stratification , clustering and the effects of non -response, post -
stratification, and raking ;   
e) the estimates should  reflect any design effect resulting from a complex design ; 
f) develop model -based estimates and projections according to accepted theory and practices ( that 
is,assumptions, mathematical specifications );    
g) subject any model used for developing estimates or projections to the following:  
i. sensitivity analysis to determine if changes in key model inputs cause key model outputs to 
respond in a sensible fashion;   
ii. model validation to analyze a model‟s performance by comparing the results to available 
independent information sources; and  
iii. demonstration of reproducibility to show that, given the same inputs, the model produces similar 
results ;    
h) document methods and models used to generate estimates and projections to help ensure objectivity, 
utility, transparency, and reproducibility of the estimates and projections ; and    FDUS  943: 2012  
© UNBS 2012  – All rights reserved  15 
 i) archive data and models so the estimates/projections can be reproduced.  
29B6.13 Inference and comparisons  
Statements of comparisons and other statistical conclusions derived from survey data are based on 
acceptable statistical practice.   The following guidelines should be followed for inferences and comparisons of 
survey data :   
a) specify the criter ion for judging statistical significance for tests of hypotheses (Type I error) before 
conducting the testing ;  
b) make comparison tests between two estimates, if either is constructed from a sample ;   
c) use methods for comparisons appropriate for the nature of  the estimates.   In most cases, this 
requires estimates of the standard error of the estimates and, if the estimates are not independent, an 
estimate of the covariance between the two estimates ;  
d) when performing multiple comparisons with the same data bet ween subgroups, include a note with 
the test results indicating whether or not the significance criterion (Type I error) was adjusted and, if 
adjusted, by what method ;  
e) test and report only the differences that are substantively meaningful when performing comparison 
tests. ( that is, don‟t necessarily run a comparison between every pair of estimates; run only those that 
are meaningful within the context of the data, and report only differences that are large enough to be 
substantively meaningful, even if oth er differences are also statistically significant ); 
f) given a comparison that does not have a statistically significant difference, conclude that the data do  
not support a statement that they are different.  If the estimates have apparent differences, but ha ve 
large standard errors making the difference statistically insignificant, note this in the text or as a note 
with tables or graphs ;  
g) support statements about monotonic trends (strictly increasing or decreasing) in time series using 
appropriate tests.  If  extensive seasonality, irregularities, known special causes, or variation in trends 
are present in the data, take those into account in the trend analysis ; 
h) use concurrent seasonal factors for seasonal adjustment . These are the factors obtained using all 
recent values of the series. This will give frequent, mostly small, revisions to seasonally adjusted 
series. Many series are published in seasonally adjusted form to reveal the underlying trend 
movements and to facilitate data analysis ; and  
i) if part of a his torical series is revised, data for both the old and the new series should be published for 
a suitable overlap period for the use of analysts.  
30B6.14 Review information for dissemination   
The information for dissemination should  have  appropriate content/ subject matter, statistical and 
methodological review procedures to comply with the existing quality guidelines . The  guidelines  include :  
a) conduct a content/subject -matter review of all information products that present a description or 
interpretation of re sults from the survey, such as analytic reports or “briefs.”   
b) select reviewers with appropriate expertise in the subject matter, operation, or statistical program 
discussed in the document.  Among the areas that reviewers should consider are the following :  
i. subject -matter literature is referenced in the document if appropriate;  
ii. information is factually correct;  FDUS 943: 2012  
16 © UNBS 2012  – All rights reserved  
 iii. information is presented clearly and logically, conclusions follow from analysis, and no 
anomalous findings are ignored ;  
c) conduct a statistical a nd methodological review of all information products.  Select reviewers with 
appropriate expertise in the methodology described in the document.  Among the tasks that reviewers 
should consider are the following:  
i. review assumptions and limitations for accu racy and appropriateness;  
ii. ensure that appropriate statistical methods are used and reported;  
iii. review calculations and formulas for accuracy and statistical soundness;  
iv. review data and presentations of data ( for example , tables) for disclosure risk, as nec essary;  
v. review contents, conclusions and technical (statistical and operational areas) recommendations 
to ensure that they are supported by the methodology used ; 
d) review all information products that will be disseminated electronically for compliance with t he 
statistical legislation ; and    
e) ensure that any product that is disseminated via special software is tested for accessibility and 
interpretability prior to dissemination.  
31B6.15 Data release and dissemination   
A survey  is not complete until the informat ion collected is made available to potential users in a form suited to 
their needs. The forms of presentation and dissemination should facilitate access and easy interpretation by 
users.  The information may be presented in  the form of published tables and reports or mono graphs for 
general distribution Information in unpublished form is also produced for limi ted distribution, stored in a 
database and supplied upon request, or disseminated online.  The following guidelines should be followed for 
release and di ssemination of information : 
a) information should be disseminated in line with the dissemination plan. T he following should be 
considered when preparing the dissemination procedures for major information products:    
i. develop schedules and modes for the release  of information products;  
ii. inform targeted audiences;  
iii. ensure equivalent, timely access to all users ; and 
iv. ensure that data sources and technical documentation, including data limitations, are included or 
referenced ;  
b) protect information against any unautho rized pre -release ; 
c) if revisions to estimates are planned, establish a schedule for anticipated revisions, make it available 
to users, and identify initial releases as preliminary ; 
d) establish a policy for handling unscheduled corrections due to previously un recognized errors.  The 
policy may include threshold criteria ( for example , if the correction will change a national level total 
value by more than one percent or a regional value by more than five percent ); 
e) identify conditions under which data will be cor rected and re -disseminated appropriately ;   
f) relevant metadata should be availed and/or accessed in a standard format. In addition, the users 
should be provided access to the following information:   FDUS  943: 2012  
© UNBS 2012  – All rights reserved  17 
 i. quality -related documentation such as conceptual limitati ons and non sampling error;  
ii. variance estimation documentation;  
iii. time period covered by the information and units of measure;  
iv. data taken from alternative sources;   
v. point of contact to whom further questions can be directed;  
vi. software or links to software  needed to read/access the information and installation/operating 
instructions, if applicable;   
vii. date the product was last updated; and  
viii. standard dissemination policies and procedures ; 
g) data and information to be shared should observe confidentiality princi ples;  
h) for information products derived using models, adhere to the following:   
i. clearly identify forecasts and derived estimates; and   
ii. make descriptions of forecasting models or derivation procedures accessible from the product 
along with any available e valuation of its accuracy ;   
i) include criteria for instances when information will not be publicly disseminated ( for example , 
underlying data are of insufficient quality) in the agency‟s standard dissemination policies and 
procedures ; 
j) for presentation of st atistical results in tabular, chart or publication form, adhere to the following : 
i. for tables : 
 every table should have clear headings to clearly identify the content ; 
 the table layout should  be clear and easy to follow ; 
 all units of measurement should be di splayed clearly ; 
 where a comparison between numbers is required, listing should be done in columns to 
facilitate reading ; 
 ensure all rounding to significant digits is mathematically correct ; and  
 ensure that footnotes are clearly marked and that the text is  clear and readable ; 
ii. for charts : 
 the chart title must explain what phenomenon is represented and the time periods covered ; 
 the chart should convey a clear and accurate representation of the phenomenon being 
studied ; 
 all axes must be clearly labelled and in clude the units of measurement ; 
 legends, labels and tick marks should all be clear and readable ; FDUS 943: 2012  
18 © UNBS 2012  – All rights reserved  
  all elements on the chart should be identified ; 
 any apparent discrepancy should be highlighted and explained ; 
iii. for reports/ publications : 
 be well -organized and e asy to follow ; 
 ensure titling and systematic page, chapter and section numbering ; 
 text should be written in clear and unambiguous language ; 
 for analytical reports and abstracts, the text should aim to describe inferences, rather than 
repeat numeric results ; 
 should define all technical terms used ; 
 should give references for all sources of both primary and secondary data used, and to any 
other publications quoted ; 
 should be attractive to look at ; 
 may include conventions for indicating missing data inclusion a nd style of notes ; and  
 should inform evidence -based policy formulation and monitoring of development outcomes ; 
k) published survey material  should be  subject to copyright rules ; 
l) the choice of dissemination media should be guided by the context and  the intende d categories of 
users ; and  
m) a comprehensive list of key stakeholder should be maintained.  
32B6.16 Data confidentiality and disclosure for dissemination   
The national statistical legislation  provides for confidentiality of the information collected which is intended for 
statistical purposes . Personal information provided by respondents is considered confidential and should 
therefore not be disseminated, shown or communicated to any person or body.  The following guidelines 
should be adhered to regarding data c onfidentiality and disclosure for dissemination : 
a) when releasing statistical products, ensure strict compliance with the confidentiality pledge to the 
respondents as stipulated in statistical legislation;   
b) for survey information collected under a pledge of confidentiality, employ sufficient procedures and 
mechanisms to protect any individually -identifiable data from unauthorized disclosure ; and   
c) do not publicly reveal parameters associated with disclosure limitation rules.    
33B6.17 Survey documentation  
Documentation involves the  collection of material that provides a description of the activity. Survey 
documentation provides a  description of the statistical production process and is presented in various formats 
(that is,  electronic or hard copy) . Survey sy stem documentation includes all information necessary to analyze 
the data properly. Documentation should  include the following:  
a) description of variables used to uniquely identify records in the data file;  
b) description of the sample design, including strat a and sampling unit identifiers to be used for analysis;   FDUS  943: 2012  
© UNBS 2012  – All rights reserved  19 
 c) final instrument(s) or a facsimile thereof for surveys conducted ;    
d) definitions of all variables, including all modifications;  
e) data file layout;  
f) descriptions of constructed variables on the data  file that are computed from responses to other 
variables on the file;   
g) unweighted frequency counts;  
h) description of sample weights, including adjustments for non -response and benchmarking and how to 
apply them;  
i) description of how to calculate variance e stimates appropriate for the survey design;  
j) description of all editing and imputation methods applied to the data (including evaluations of the 
methods) and how to remove imputed values from the data;   
k) descriptions of known data anomalies and corrective actions;  
l) description of the magnitude of sampling error associated with the survey;  
m) description of the sources of non sampling error associated with the survey ( for example , coverage, 
measurement) and evaluations of these errors;  
n) comparisons with indepe ndent sources, if available;  
o) overall unit response rates (weighted and unweighted) and non -response bias analyses (if 
applicable); and  
p) item response rates and non -response bias analyses, (if applicable) . 
Survey documentation should be readily accessible t o users, unless it is necessary to restrict access to 
protect confidentiality. Meta data for the respective surveys should  be documented  and stored. The following 
guidelines should be applied for survey documentation : 
a) provide complete survey documentation for all data files and the entire survey process. This 
documentation should be done according to the statistics archival policy ;  
b) to ensure that a survey can be replicated and evaluated, the agency‟s internal archived portion of the 
survey system documenta tion, should include the following:  
i. survey planning and design decisions, including the Information Collection Request packages;  
ii. field test design and results;  
iii. selected sample;  
iv. sampling frame;  
v. justifications for the items on the survey instrument, inc luding why the final items were selected;  
vi. all instructions to respondents and/or interviewers either about how to properly respond to a 
survey item or how to properly present a survey item;  
vii. description of the data collection methodology;  
viii. sampling plan a nd justifications, including any deviations from the plan;  FDUS 943: 2012  
20 © UNBS 2012  – All rights reserved  
 ix. data processing plan specifications and justifications;   
x. final weighting plan specifications, including calculations for how the final weights were derived, 
and justifications;  
xi. final imputation plan specifications and justifications;  
xii. data editing plan specifications and justifications;   
xiii. evaluation reports;  
xiv. descriptions of models used for indirect estimates and projections;  
xv. analysis plans;  
xvi. time schedule for revised data; and  
xvii. documentation ma de publicly available in conjunction with the release of data ;   
c) produce a periodic evaluation report, for example a methodology report that itemizes all sources of 
identified error for recurring surveys.  Where possible, provide estimates or bounds on the  magnitudes 
of these errors; discuss the total error model for the survey; and assess the survey in terms of this 
model ;  
d) retain all survey documentation according to appropriate statistics archival policies ; and  
e) data archiving should be well managed, such  that data are available for historical research in the 
future years.  
34B6.18 Release of public -use micro data  
Micro data should be well documented prior to release for public use. The documentation describ es how the 
information is constructed and provide s the appropriate  metadata for users to access . The following guidelines 
should be used for release of public -use micro data.   
a) provide a file description and record layout for each file.  All variables should  be clearly identified and 
described ( metadata).    
b) for complete metadata compilation and availability, the following should be adhered to : 
i. responsibility centers should  ensure that all concepts and definitions used in statistics production 
are clearly defined and harmonized;  
ii. common methodology should b e adopted when undertaking related surveys to avoid 
inconsistencies across data producing agencies which affect the quality of statistical results and 
outputs;  
iii. the metadata should be stored on the National Databank and, should  be reviewed and updated 
when ever a change is made to any part of the statistical activity; and 
iv. standard rules for metadata management should be developed ; 
c) clearly identify all imputed values on the data file ;  
d) release public -use micro data and metadata in a timely manner  to ensure ti mely availability for data 
users ; and .    
e) retain all micro data products and documentation according to the appropriate statistic s archival 
policies.   FDUS  943: 2012  
© UNBS 2012  – All rights reserved  21 
 35B6.19 Revisions to published d ata 
Revisions to published data can, and do, occur for many reasons. Occasionally, revisions arise from a change 
in methodology which may necessitate the re -compilation  of data from the previous period using the new 
methodology.  Common sources of revisions to statistics are:  
a) the availability of additional information (e.g. lat e survey responses; a new period‟s data available for 
the calculation of seasonal factors) ; 
b) the receipt of amended information (e.g. as a result of the response to a query) ; and  
c) changes resulting from additional and more detailed data editing.  
The followin g guidelines represent best practices that may be useful when revising published data : 
a) produce for users a clear and concise data revisions policy for all published statistics  that undergo 
revisions ; 
b) the users should be made aware of the frequency of data revisions  
c) when publishing data that is likely to be subsequently revised ( for example,  preliminary estimates), 
always indicate this to the user ; 
d) describe the main reasons why particular statistics are subject to revision ; and  
e) for established statistical da ta series, inform users of the frequency and size of past revisions . 
6B7 Administrative data 
Administrative data is generated during the process of executing administrative functions to inform policy and 
decision -making.   For it to serve a statistical purp ose, there is need to compile administrative data following a 
systematic, objective and standardized approach. Statistical use of administrative data include creation and 
maintenance of frames , the complete or partial (via record linkage) replacement of st atistical collection , 
editing, imputation and weighting of data from statistical collection and evaluation of statistical outputs.  
The following guidelines should be followed in administrative data production;  
a) the agency or organization should describe the  primary purpose of data collection through 
administrative sources ; 
b) actively investigate and assess all potential sources of administrative data ; 
c) describe the format in which the administrative data are available ; 
d) describe and document the concepts, defini tions and procedures underlying the collection of 
administrative data ; 
e) each administrative dataset should be accompanied by metadata about its contents so that users 
assess their suitability for their purposes ; 
f) describe the main uses of administrative data , including where applicable  the statistical processes 
and/or outputs that require data from administrative sources ; 
g) describe the extent of coverage of the administrative data and any known coverage problems ; 
h) describe the known sources of error in administ rative data ; 
i) describe the timescale since the last update of data from administrative sources ; FDUS 943: 2012  
22 © UNBS 2012  – All rights reserved  
 j) describe the common identifiers of population units in administrative data ; 
k) set up an edit and imputation procedure or a weight adjustment procedure to deal with  non-response ; 
l) describe the extent to which the data from administrative sources meets statistical requirements ; 
m) describe any changes in the legislative environment through which the administrative data are 
provided and the effects on the statistical produ ct; 
n) the confidentiality implications of the publication of information from administrative records should be 
considered;  
o) maintain continuing collaboration with the providers and suppliers of administrative data ; and  
p) implement continuous or periodic quality  assessments for administrative data production.  
7B8 Indicators and index numbers  
36B8.1 Indicators  
An indicator measures change  over time or against benchmarks, targets or visions for the future. It is a pointer 
used specifically to show the state, level or condition of a variable of interest. The condition of interest may be 
demographic, social, economic or political . Indicators are categorised under input, output, process, outcome 
or impact.  
The following guidelines should be considered in indicator deve lopment and reporting:  
a) define the purpose for developing indicators ;  
b) develop and publish metadata for the indicators ; 
c) identify key stakeholders and define their process of engagement ; 
d) establish common working groups for key statistical and high frequency indicators that are produced 
regularly ; 
e) develop an operational plan for indicator development and reporting ; 
f) determine the methods for compilation and reporting of indicators and frequency of update in 
advance ; 
g) compile statisti cal indicators in line with recommended national and international standards and 
guidelines ;  
h) document the compilation processes for statistical indicators and archive the information ; 
i) disseminate the indicators in line with the release calendar ; and  
j) review the indicator framework and  indicators periodically to ensure that it is reflective of the current 
economic situation.  
37B8.2 Index numbers  
An index number is a positive number measuring the average change in a group of related items over a 
specified period. There are two types of i ndex numbers , price and volume index numbers.  The index number 
may be used in studying the general level of activity conditions over a specified time period. Indices are key 
macro - economic indicators used to monitor price movements and net output of the different sectors of the 
economy.  FDUS  943: 2012  
© UNBS 2012  – All rights reserved  23 
 A price index measures the percentage change in a set of prices of a group of items over time. There are 
three types of price indices namely Consumer Price Index (CPI), Producer Price Index (PPI) and import and 
export pric e indices. The volume index describes relative change in the volume of output over time.  
Volume indices include Index of Production (IoP) and Index of Services (IoS) among others.  
The following guidelines should be considered when computing indices:  
a) define the purpose of the index to be computed;  
b) derive weights based on the relevant survey/census/administrative data and specify the base period;  
c) determine the scope of the index;  
d) classify the relevant components of the index  according to international stand ards and classifications;  
e) undertake regular data collection and compute the index in line with the internationally recommended 
formulae;  
f) disseminate the index in line with the release calendar ; 
g) document the compilation processes and archive data ; 
h) revise th e index in line with the revision policy of the organisation ; and   
i) rebase the index periodically to ensure that it is reflective of the current economic situation.  
 
 FDUS 943: 2012  
24 © UNBS 2012  – All rights reserved  
 Annex  A 
(normative)  
 
Statistics Production Cycle  
7.3
Produce 
“Quality 
Statement. ”1
Need2
Design3
Build4
Collect5
Process6
Analyze7 Disseminate 8
Archive
1.1
Determine 
need for
information
1.2 
Consult & 
confirm 
information 
requirements
1.3
Establish
output
objectives
1.4
Check data
availability 
1.5
Prepare 
business 
case2.1
Outputs
2.2
Frame
and sample
methodology
2.4
Data
collection
2.5
Statistical 
processing 
methodology 
2.7
Processing 
systems and 
workflow3.1
Data
collection
instrument
3.2
Process 
components
3.3
Configure 
workflows
3.4
Test end -to-
end
3.5
Finalize 
production 
systems
3.6
Draw sample4.1
Set up 
collection
4.2
Run 
collection
5.2
Load data 
into 
processing 
environment5.1
Standardize
5.3
Integrate 
data5.1
Classify and 
code
5.4
Edit and 
impute
5.5
Derive new 
variables6.2
Calculate 
aggregates6.1
Acquire
ancillary 
information
6.3
Prepare draft 
outputs
6.4
Validate 
6.5
Describe and 
explain 
6.6
Disclosure 
control & 
Anomyse
6.7
Finalize
outputs for 
dissemination7.1
Update output 
systems
7.2
Produce 
products
7.4
Manage 
release of 
products
7.6
Manage 
customer 
queries7.5
Market and 
promote 
products2.6
Define archive 
rules8.1
Manage 
archive 
repository
8.2
Preserve 
data and 
associated 
metadata
8.3
Dispose of 
data and 
associated 
metadata
5.6
Calculate 
weights2.3
Tabulation 
Plan / 
Variables9
Audit   
9.1
Gather 
inputs for 
audit
9.2
Prepare 
audit report
9.3
Quality plan
2.8
Detailed 
project plan
 FDUS  943: 2012  
© UNBS 2012  – All rights reserved  25 
 Annex  B 
(informative)  
 
UN Fundamental Principles for Official Statistics  
 
HPrinciple 1. H  Official statistics provide an indispensable element in the information system of a democratic 
society, serving the Government, th e economy and the public with data about the economic, 
demographic, social and environmental situation. To this end, official statistics that meet the test 
of practical utility are to be compiled and made available on an impartial basis by official 
statist ical agencies to honour citizens' entitlement to public information.  
HPrinciple 2. H  To retain trust in official statistics, the statistical agencies need to decide according to stri ctly 
professional considerations, including scientific principles and professional ethics, on the 
methods and procedures for the collection, processing, storage and presentation of statistical 
data.  
HPrinciple 3. H  To facilitate a correct interpretation of the data, the statistical agencies are to present information 
according to scientific standards on the sources, methods and procedures of the statistics.  
 
HPrinciple 4. H  The statistical agencies are entitled to comment on erroneous interpretation and misuse of 
statistics.  
HPrinciple 5. H  Data for statistical purposes may be drawn from all types of sources, be they statistical surveys 
or administrative records. Statistical agencies are to choose the source with regard to quality, 
timeliness, costs and the burden on respondents.  
HPrinciple 6. H  Individual data collected by statistical agencies for statistical compilation, whether they refer to 
natural or legal persons, are to be strictly confidential and used exclusi vely for statistical 
purposes.  
HPrinciple 7. H  The laws, regulations and measures under which the statistical systems operate are to be made 
public.  
HPrinciple 8. H  Coordination among statistical agencies within countries is essential to achieve consistency and 
efficiency in the statistical system.  
HPrinciple 9. H  The use by statistical agencies in each country of international concepts, classifications and 
methods promotes the consistency and efficiency of statistical systems at all official levels.  FDUS 943: 2012  
26 © UNBS 2012  – All rights reserved  
 HPrinciple 10. H Bilateral and multilateral cooperation in statistics contributes to the improvement of systems of 
official statistics in all countries.  FDUS  943: 2012  
© UNBS 2012  – All rights reserved  27 
 Metadata Rule 1 : Good statistical metadata confo rms to international and national standards in a way 
that is appropriate to user needs, the purpose and procedures for statistics production.  
Metadata Rule 2 : Good statistical metadata supports interoperability and intercomparability in statistics 
producti on and use across MDAs in the NSS.  
Metadata Rule 3 : Good statistical metadata uses quality guidelines and standardised instruction 
manuals to describe the type and general procedures for various statistics produced and related 
outputs.  For every statistic al indicator, the indicator name and description are specified. Content rules  
(how content must be formulated), representation rules (e.g., how the metadata is illustrated and 
presented), and allowed element values (e.g., the vocabulary used)  can also be s pecified optionally.  
Metadata Rule 4 : Good statistical metadata includes a clear statement of the conditions and terms of 
use for various statistics produced.  
Metadata Rule 5 : Good statistical metadata supports long -term improvement and maintenance of data / 
statistics collected. Appropriate mechanisms for storage/archive, effective retrieval and process 
management are imperative.  
Metadata Rule 6 : Good statistical metadata records are an integral part of process documentation. 
Accordingly,     compilation an d maintenance of metadata records should be uniform, authentic, 
continuous, participatory, and perceptive towards the different institutional structures that support 
statistics production and use in the MDAs. These may vary from systematic and unique repor ting 
mechanisms, intra and inter departmental linkages, to cross -sectoral collaborative arrangements 
&committees for data/statistical purposes.       Annex  C 
(informative)  
 
Rules for statistical meta data management  
 
 
 FDUS  943: 2012  
© UNBS 2012 – All rights reserved  29 
 Bibliography   
[1] Statistics Canada, October 1998, Statistics Canada Quality Guidelines , 3rd edition  
[2] Euro stat, 2003, Assessment of quality in statistics, Methodological documents – Definition of Quality 
 in Statistics , Doc. Eurostat/A4/Quality/03/Genera l/Definition . 
[3] Standards and Guidelines for Statistical Surveys - 2006,  Statistical Programmes and Standards, Office  
 of Management and Budget, Washington -USA 
[4] Guidelines for measuring statistical quality,  Office for National Statistics  - Wales, UK  
[5] Statistica l Quality Assessment Framework for Uganda  
[6] Guidelines for Statistical Outputs  
[7] Guidelines for development and Reporting Statistical Indicators  
[8] Classification of Individual Consumption According to Purpose (COICOP)   
[9] International Standard Industrial Classific ation (ISIC)  
[10] Government Finance Statistics (GFS) manual   
[11] Chart of Accounts   
[12] System of National Accounts (SNA)  
[13] Central Product Classification (CPC)  
[14] Harmonized Commodity Description and Coding System (HS)  
[15] UN guidelines for conducting censuses  
[16] UN Fundame ntal Principles of Official Statistics  
[17] Africa Statistics Charter  
[18] International classification of disease (ICD)  
[19] International classification of Functioning Disability and Health (ICF)  
[20] International standard classification of Occupation (ISCO)  
 FDUS 943: 2012  
30 © UNBS 2012  – All rights reserved  
 Certification  marking  
Products that conform to Uganda standards may be marked with Uganda National Bureau of Standards 
(UNBS) Certification Mark shown in the figure below.  
The use of the UNBS Certification Mark is governed by the Standards Act, and the Regulations mad e 
thereunder. This mark can be used only by those licensed under the certification mark scheme operated by 
the Uganda National Bureau of Standards and in conjunction with the relevant Uganda Standard. The 
presence of this mark on a product or in relation t o a product is an assurance that the goods comply with the 
requirements of that standard under a system of supervision, control and testing in accordance with the 
certification mark scheme of the Uganda National Bureau of Standards. UNBS marked products ar e 
continually checked by UNBS for conformity to that standard.  
Further particulars of the terms and conditions of licensing may be obtained from the Director, Uganda 
National Bureau of Standards.  
 
 FDUS 943: 2012    
 
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