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HISTORICAL CURRENT POPULATION SURVEY/HOUSING VACANCY SURVEY 

(CPS/HVS) CHANGES

Changes in 2019

In the second quarter 2019, historical housing inventory estimates were revised based on 

the latest series of independent housing controls, the vintage 2018 independent housing estimates 

issued by the Census Bureau’s Population Division. This includes the housing inventory timeseries data from 2010 through the first quarter 2019. The vintage 2018 estimates are 

benchmarked to the 2010 Census. The same general procedure will be followed each year in 

revising housing inventory estimates with the most up-to-date independent housing estimates 

available. For an explanation of the methodology used in producing the housing inventory 

independent estimates, please see: www.census.gov/programs-surveys/popest.html

Note: This time series is by the latest “vintage year.” For example, vintage 2018 means that all of 

the estimates in this time series are identified as belonging to "vintage 2018." The 2010 data are 

from the 2018 vintage, the 2011 data are from the 2018 vintage, and so on.

Changes in 2018 

In the second quarter 2018, historical housing inventory estimates were revised based on 

the latest series of independent housing controls, the vintage 2017 independent housing estimates 

issued by the Census Bureau’s Population Division. This includes the housing inventory timeseries data from 2010 through the first quarter 2018. The vintage 2017 estimates are 

benchmarked to the 2010 Census. 

Changes in 2017

In the second quarter 2017, historical housing inventory estimates were revised based on 

the latest series of independent housing controls, the vintage 2016 independent housing estimates 

issued by the Census Bureau’s Population Division. This includes the housing inventory timeseries data from 2010 through the first quarter 2017. The vintage 2016 estimates are 

benchmarked to the 2010 Census. 

In the first quarter 2017, the parameters used to calculate standard errors for rates and 

estimates were updated. The factors are evaluated, and updated if necessary, after approximately 

15 months of data have been collected from a new CPS/HVS sample following a decennial 

census. The current sample has been fully phased-in since July 2015. 

Changes in 2016

In the second quarter 2016, historical housing inventory estimates were revised based on 

the latest series of independent housing controls, the vintage 2015 independent housing estimates 

issued by the Census Bureau’s Population Division. This includes the housing inventory timeseries data from 2010 through the first quarter 2016. The vintage 2015 estimates are 

benchmarked to the 2010 Census. 
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Changes in 2015

In the second quarter 2015, historical housing inventory estimates were revised based on 

the latest series of independent housing controls, the vintage 2014 independent housing estimates 

issued by the Census Bureau’s Population Division. This includes the housing inventory timeseries data from 2010 through the first quarter 2015. The vintage 2014 estimates are 

benchmarked to the 2010 Census. 

In the first quarter 2015, the Current Population Survey/Housing Vacancy Survey began 

using the new Metropolitan Statistical Area (MSA) definitions that were announced by the 

Office of Management and Budget (OMB) in February 2013, based on the application of the 

2010 OMB standards to Census 2010 data. The definitions are available at: 

www.census.gov/programs-surveys/metro-micro.html. Caution should be used when comparing 

MSA data for 2015 to earlier data. 

Changes in 2014

In the second quarter 2014, historical housing inventory estimates were revised based on 

the latest series of independent housing controls, the vintage 2013 independent housing estimates 

issued by the Census Bureau’s Population Division. This includes the housing inventory timeseries data from 2010 through the first quarter 2014. The vintage 2013 estimates are

benchmarked to the 2010 Census. 

Beginning in April 2014, a new sample was phased in over a 15-month period. The 

methods used to select the sample households for the survey are evaluated after each decennial

census. Based on these evaluations, the design of the survey is modified and systems are put in 

place to provide the sample for the following decade. The previous decennial revision

incorporated new information from Census 2000 and was complete as of July 2005. The design 

for the entire decade was selected from the 2000 based sample. The most recent revision 

incorporates new information from Census 2010 and was complete as of July 2015. The new 

sample is based on the Master Address File (MAF) compiled during the 2010 Census and will 

use annual selections from the MAF instead of the once a decade sample selection used 

previously.

Changes in 2013

In the second quarter 2013, historical housing inventory estimates were revised based on 

the latest series of independent housing controls, the vintage 2012 independent housing estimates 

issued by the Census Bureau’s Population Division. This includes the housing inventory timeseries data from 2010 through the first quarter 2013. The vintage 2012 estimates are 

benchmarked to the 2010 Census. 

Changes in 2012
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In the second quarter 2012, historical housing inventory estimates were revised based on 

the latest series of independent housing controls, the vintage 2011 independent housing estimates 

issued by the Census Bureau’s Population Division. This includes the housing inventory timeseries data from 2010 through the first quarter 2012. The vintage 2011 estimates are 

benchmarked to the 2010 Census. 

Beginning in the first quarter 2012, the population controls reflect the results of the 2010

Decennial Census. This change has virtually no effect on vacancy and homeownership rates. 

Research has shown that the new 2010-based controls increased the rental vacancy rate in April 

2010 from 10.43 percent to 10.45 percent - a difference of less than 1/10 of one percent. The 

homeowner vacancy rate remained the same at 2.63 percent, while the homeownership rate was 

up from 66.67 percent to 66.74 percent.

Changes in 2011

In the third quarter 2011, historical housing inventory estimates were revised based on 

the latest series of independent housing controls, the vintage 2010 independent housing estimates 

issued by the Census Bureau’s Population Division. This includes the housing inventory timeseries data from 2000 through the second quarter 2011. The vintage 2010 estimates are 

benchmarked to the 2000 and 2010 Census. 

Changes in 2010

In the third quarter 2010, historical housing inventory estimates were revised based on 

the latest series of independent housing controls, the vintage 2009 independent housing estimates 

issued by the Census Bureau’s Population Division. The vintage 2010 estimates are 

benchmarked to the 2000 Census. 

 In the first quarter 2010, the Census Bureau began imputing missing values for the family 

income question, which is used in the homeownership table 8 of the press release. Previously, 

householders not responding to this question were excluded from the homeownership 

calculations for those below/above the median family income level. 

Changes in 2007

In first quarter 2007, the Current Population Survey/Housing Vacancy Survey 

(CPS/HVS) began using Blaise, a powerful computer-assisted interviewing (CAI) system and 

survey processing tool for the Windows operating system. It is being used for many of the 

surveys now being conducted by the Census Bureau. 

Changes in 2003

Beginning in the first quarter 2003, population controls that reflect the results of the 2000 

Decennial Census were used in the CPS/HVS estimation process for the first time. This change 

had a slight effect on vacancy and homeownership rates, as described below. As a final 
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additional step in the estimation process, the estimates were controlled to independent housing 

counts used for the first time in order to produce a more accurate estimate of housing units. This 

makes the CPS/HVS estimates of housing units more consistent with other Census Bureau 

housing surveys. The new housing controls affected the count of all housing units in the sense 

that both occupied and vacant units were ratio estimated to the new control total. Vacancy rates 

and homeownership rates were not affected by this change.

In the first quarter 2003, the CPS/HVS began computing first-stage factors (used for 

weighting purposes) based on year-round and seasonal counts of housing units from the 2000 

decennial. From 1980 to 2002, the CPS/HVS first-stage factors were based on year-round 

estimates only. We believe that this improves our counts of year-round and seasonal units. 

The shift from 1990-based to 2000-based population controls (including the weighting 

revision) had a very slight effect on vacancy rates and homeownership rates. Research has shown 

that the new 2000-based controls dropped the rental vacancy rate in the first quarter 2002 from 

9.14 percent to 9.08 percent - a difference of less than 1/10 of one percent. The homeowner 

vacancy rate was revised from 1.67 percent to 1.65 percent, while the homeownership rate was 

revised from 67.82 percent to 67.81 percent. 

Beginning in the first quarter 2003, the questions on race on the CPS were modified to 

comply with the revised standards for federal statistical agencies. Respondents are now allowed 

to select more than one race. The Hispanic/Non-Hispanic origin question continues to be asked 

separately.

Changes in 1994

Beginning in the first quarter 1994, a new weighting procedure was implemented based 

on the 1990 Decennial Census. The 1990-based weighting prodedure produced an estimate of the 

total housing inventory about 0.1 percent lower than the 1980-based weighting. Generally, the 

vacancy rates were only minimally affected, while the homeownership rate was about one-half of 

a percentage point lower with the new weighting procedures. 

Also beginning in the first quarter 1994, the CPS/HVS became a fully computerized 

survey with the implementation of the Computer Assisted Survey Information Collection 

(CASIC). The CASIC tools consist of state-of-the-art computer-assisted modules for data 

collection and processing. Although the concepts, definitions and questionnaire items remain the 

same, the shift to CASIC may affect vacancy rates and homeownership rates. The Census Bureau 

was unable to determine the quantitative effects of the use of CASIC on the vacancy and 

homeownership rates. Data users should use caution when comparing data for 1994 and later 

with earlier data.
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SOURCE AND ACCURACY OF ESTIMATES

Source of Data 

The estimates presented in this report were primarily based on data obtained from the 

Census Bureau’s Current Population Survey/Housing Vacancy Survey (CPS/HVS). The 

populations represented (the population universe) are all housing units (vacancy rates) and the 

civilian non-institutional population of the United States (homeownership rate). Data concerning 

vacancy rates and tenure of occupied housing units were from the monthly sample of the CPS.

The data presented are averaged for the three months – October, November, and December 2019. 

The average weighted CPS response rate for the fourth quarter 2019 was 83.3 percent. 

Distributions of characteristics of occupied housing units in detailed table 3 were from 

the American Housing Survey (AHS). The distributions were applied to the CPS/HVS housing 

inventory independent estimates to obtain the characteristics of occupied housing units used in 

this report. The Survey of Construction (SOC) and the Consumer Price Index (CPI) also were 

used to improve estimates of the rent distribution. 

For the 2017 AHS Integrated National sample, 84,879 sample housing units were 

selected for interview. Of the selected units, 2,052 were found to be ineligible because the units 

either no longer existed or did not meet the AHS definition of a housing unit. Of the 82,933 

eligible sample units, 16,181 (both occupied and vacant housing units) were classified as 

noninterviews. The Integrated National Sample includes a representative sample of housing 

units for the United States. However, due to budget restrictions, the AHS does not include 

housing units from every political jurisdiction (that is, county or city) or census area (tract or 

block group) within the United States. A detailed description of the AHS sample design and 

estimation procedure can be found here: https://www.census.gov/programs-surveys/ahs/techdocumentation/def-errors-changes.html

CPS Design 

Since the inception of the CPS in 1940, the sample has been redesigned several times to 

upgrade the quality and reliability of the data and to meet changing data needs. From July 1995 

to March 2004, the CPS/HVS sample was selected from a frame based on the 1990 Decennial 

Census. From April 2004 to June 2005, the sample consisted of sample units drawn from both 

the 1990 and 2000 Decennial Censuses. From July 2005 to March 2014, the sample consisted of 

housing units drawn from Census 2000, along with housing units built after April 1, 2000. 

Beginning in April 2014, the CPS/HVS sample was based on the Master Address File (MAF) 

complied during the 2010 Census and will use annual selections from the MAF instead of the 

once a decade sample selection used previously. 

Beginning in the first quarter 1986, vacant seasonal mobile homes were included in the 

count of vacant seasonal units. This change resulted in a 12 percent increase in the number of 

vacant seasonal housing units. 

Beginning the second quarter of 1999, a change was made in the way data for housing 

units in structure were collected. Previously, there was one category to show a 1-unit structure. 

That has been broken into two categories: 1-unit attached and 1-unit detached.
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Beginning in the first quarter 2002, the size of the CPS/HVS sample increased to 

approximately 72,000 housing units. This expansion was one of the Census Bureau’s plans to 

meet the requirements of the State Children’s Health Insurance Program (SCHIP) legislation. Of 

the 72,000 housing units contained in the CPS/HVS sample, approximately 61,200 are eligible 

for interview each month; of this number, on average 3,900 occupied units, are visited but 

interviews are not obtained because occupants are not found at home after repeated calls or are 

unavailable for some other reason. In addition of the 61,200 units, there are also about 10,800 

sample units in an average month which are visited but are found to be vacant or otherwise not to 

be interviewed. About half of the 10,800 are vacant and interviewed for the HVS. 

The CPS estimation procedure for occupied units involves the inflation of the weighted 

sample results to independent estimates of the total civilian non-institutional population of the 

United States by age, race, sex and Hispanic/non-Hispanic categories. These independent 

estimates were based on statistics from the decennial censuses of population; statistics on births, 

deaths, immigration and emigration; and statistics on the strength of the Armed Forces.

The HVS estimation procedure for vacant units is similar to that used for occupied units. 

Weighted sample results were adjusted at the state level using 2010 census vacant counts. A 

second adjustment inflated these results based on the CPS coverage of occupied units by 

geographic areas. As a final step for both the CPS and HVS, all housing unit counts were 

adjusted to reflect independent housing control totals. This change was effective, beginning in 

the first quarter 2003.

Comparability with Decennial Census Housing Data 

The most recent research has shown that the CPS/HVS and the 2010 census produced 

significant differences for vacancy characteristics. The rental vacancy rate from the April 2010 

census was 9.2 percent, whereas the CPS/HVS reported the rental vacancy rate of 10.6 percent 

for the first half of 2010. The April 2010 census had a homeowner vacancy rate of 2.4 percent, 

while the CPS/HVS had a vacancy rate of approximately 2.6 percent for the first half of 2010. 

For occupied housing, the April 2010 census produced a homeownership rate of 65.1 percent, 

while for the first half of 2010, the CPS/HVS produced a rate of 67.0 percent. These differences 

illustrate that, for these characteristics as well as others, caution should be used when making 

comparisons between the 2010 census and the CPS/HVS. 

Further research has shown that the CPS/HVS and the 2000 census produced significant 

differences for vacancy characteristics. The rental vacancy rate from the April 2000 census was 

6.8 percent, whereas the CPS/HVS reported the rental vacancy rate of 7.9 percent for the first 

half of 2000. The April 2000 census had a homeowner vacancy rate of 1.7 percent, while the 

CPS/HVS had a vacancy rate of approximately 1.5 percent for the first half of 2000. For 

occupied housing, the April 2000 census produced a homeownership rate of 66.2 percent, while 

for the first half of 2000, the CPS/HVS produced a rate of 67.2 percent. These differences 

illustrate that, for these characteristics as well as others, caution should be used when making 

comparisons between the 2000 census and the CPS/HVS. 

Research has shown that the CPS/HVS and the 1990 census produced significant 

differences for vacancy characteristics. The rental vacancy rate from the April 1990 census was 

8.5 percent, whereas, the CPS/HVS reported the rental vacancy rate of 7.2 percent for the first 

half of 1990. The April 1990 census had a homeowner vacancy rate of 2.1 percent, while the 

CPS/HVS had a vacancy rate of approximately 1.7 percent for the first half of 1990. For 
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occupied housing, the April 1990 census produced a homeownership rate of 64.2 percent, while 

for the first half of 1990 the CPS/HVS produced a rate of 63.9 percent. These differences 

illustrate that, for these characteristics as well as others, caution should be used when making 

comparisons between the 1990 census and the CPS/HVS. 

Most of the concepts and definitions were the same for items that appear in 1980, 1990, 

2000 and 2010 censuses and the Housing Vacancy Survey. However, there was one minor 

difference in the housing unit definition between the CPS/HVS and the 1980 and 1990 Decennial 

Censuses. The difference was that, in the CPS/HVS prior to 1983, living arrangements 

containing five or more persons, not related to the person in charge, were classified as group 

quarters; for the 1980 and 1990 census, the requirement was raised to nine or more persons not 

related to the person in charge. For Census 2000, the conversion requirement was eliminated. 

There were some differences in what has been counted as housing units between the earlier 

censuses and the CPS/HVS. Descriptions of the differences between earlier censuses and the 

HVS appear in the 1985 and earlier reports of this series. 

Prior to the first quarter 1990, there were significant differences between the CPS/HVS 

and the decennial censuses. The 1980 and 1990 Decennial Censuses included vacant mobile 

homes as housing units, whereas prior to 1986 the CPS/HVS did not. However, beginning in the 

first quarter 1986, vacant seasonal mobile homes were counted as housing units in the CPS/HVS. 

In addition, year-round vacant mobile homes were counted as housing units, beginning in the 

first quarter 1990 in the CPS/HVS. Another difference in the housing unit definition between the 

CPS/HVS (prior to 1986) and the 1980 and 1990 censuses was that the CPS/HVS required units 

to be separate living quarters and have direct access or have complete kitchen facilities. For the 

1980 and 1990 Decennial Censuses, the complete kitchen facilities alternative was dropped with 

direct access required of all units. However, beginning in 1990, the CPS/HVS requirement for 

complete kitchen facilities was dropped with direct access required of all units. Thus, the earlier 

definitional differences were eliminated. 

In addition, there are differences between the methodologies used to collect data for the 

CPS/HVS and the censuses. These differences include interviewing procedures, staff experience 

and training; differences in processing procedures and sample designs; the sampling variability 

associated with the CPS/HVS and the sample data from the census; and the non-sampling errors 

associated with the CPS/HVS and census data. 

Comparability with Earlier CPS/HVS Data 

As stated earlier in this report, beginning in the first quarter 1994 new weighting 

procedures based on the 1990 Decennial Census were implemented. In addition, the survey data 

collection procedures became fully computerized. Caution should be used when comparing 

current data with unrevised data prior to 1994.

In the first quarter 1990, year-round vacant mobile homes were included for the first time 

as part of the year-round vacant count of housing units. This change was made to make the 

composition of the housing unit inventory for the CPS/HVS similar to the decennial census and 

other surveys, which count all mobile homes as housing units for both occupied or vacant 

(available for occupancy on the site). Research has shown that the inclusion of vacant mobile 

homes increased the vacancy rate significantly in some cases. We have revised 1989 data in this

report to reflect all changes. Caution should be used when comparing data from 1990 or later 

with unrevised data prior to 1990.
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In the fourth quarter 1989, new edit procedures were implemented in the CPS/HVS. 

These new procedures were used to allocate cases that would have been classified as "not 

reported" under previous procedures. 

In the first quarter 1980, several changes were implemented in the survey to improve the 

reliability of the data presented. These included adding a supplemental sample, refining the 

estimation procedures, and changing the source of occupied characteristics from the Quarterly 

Housing Survey to the AHS. 

Although the above mentioned changes resulted in more reliable estimates, data for 1980 

and later in this report are not completely comparable to data for the fourth quarter 1979 and 

previous quarters, as published in Housing Vacancies reports, series H-111, Nos. 1 to 79-Q4. 

Furthermore, unrevised data prior to 1990 were not completely comparable to 1990 data and 

beyond, due to the inclusion of year-round vacant mobile homes, beginning in the first quarter 

1990. Thus, particular caution should be observed in drawing conclusions about trends that 

extend from before 1980 to 1980 and beyond, and also trends from before 1990 to 1990 and 

later. For comparative purposes, 1979 data in this report were revised to incorporate all changes 

made in 1980, and 1989 data were revised to incorporate all changes made in 1990. Unrevised 

1989 and 1979 data are provided to show the magnitude of the various changes. 

Vacancy Rates for Characteristics in Historical Tables 3 and 4 

Vacancy rates in historical tables 3 and 4 are based in part on forecasts of occupied 

housing units. These forecasts are periodically revised to incorporate more recent data and 

improved forecasting procedures. In fourth quarter 2013, historical tables 3 and 4 were updated 

to include the most recent AHS data. Beginning in 2013, the first quarter 2013 data are based on 

data from the 2011 AHS. Beginning in 2015, the first quarter 2015 data are based on data from 

the 2013 AHS. Beginning in 2017, first quarter 2017 data are based on data from the 2015 AHS. 

Beginning in the first quarter 2019, data are based on data from the 2017 AHS.

For the occupied unit forecasts of the monthly rent categories in detailed table 3, the AHS 

data are updated quarterly to reflect the rise in the cost of renting through the use of the 

residential rent index and the latest available asking rent data for newly constructed rental units. 

Caution in Using Seasonal Vacant Data 

Analysis of seasonal vacant data prior to the first quarter 1987 has shown that estimates 

for these characteristics have been underestimated by approximately 28 percent. The estimates 

beginning with the first quarter 1987 were adjusted to reflect this. 

Accuracy of the Estimates 

Since the CPS/HVS estimates are based on a sample, they may differ somewhat from the 

figures that would have been obtained if a complete census had been taken using the same 

questionnaires, instructions and enumerators. There are two types of errors possible in an 

estimate based on a sample survey: sampling and non-sampling. The accuracy of a survey result 

depends on both types of errors, but the full extent of the non-sampling error is unknown. 

Consequently, particular care should be exercised in the interpretation of figures based on a 

relatively small number of cases or on small differences between estimates. The margins of error
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provided for the CPS/HVS estimates primarily indicate the magnitude of the sampling error. 

They also partially measure the effect of some non-sampling errors in responses and 

enumeration; but do not measure any systematic biases in the data. (Bias is the difference 

averaged over all possible samples, between the estimate and the desired value). Approximately 

2 percent of the CPS/HVS households are selected for quality control reinterview each month 

based on the previous month’s outcome.

Non-Sampling Variability 

Nonsampling errors can be attributed to many sources, e.g., inability to obtain 

information about all cases in the sample, definitional difficulties, differences in the 

interpretation of questions, inability or unwillingness on the part of respondents to provide 

correct information, inability to recall information, errors made in collection such as recording or 

coding the data, errors made in processing the data, errors made in estimating values for missing 

data and failure to represent all units with the sample (undercoverage). Undercoverage in the 

CPS/HVS results from missed housing units and misclassifying housing units. Ratio estimation 

to independent controls, as described previously, partially corrects for the bias due to survey 

undercoverage. However, biases exist in the estimates to the extent that missed households have 

different characteristics than interviewed households. While highly unusual, HVS interviews 

may not always be complete. In the case of missing information, the data will be allocated. An 

HVS interview is not considered a Type B Noninterview unless the question “Is this interview by 

observation only?” is answered. 

Sampling Variability 

The margins of error shown in the tables are primarily measures of sampling variability -

the variations that occurred by chance because a sample rather than the entire population was 

surveyed. The sample estimate and its standard error enable one to construct margins of error -

ranges that would include the average results of all possible samples with a known probability.

For example, if all possible samples were selected, each of these being surveyed under 

essentially the same general conditions and using the same sample design, and if an estimate and 

its standard error were calculated from each sample, then approximately 90-percent of the 

margins of error would include the average result of all possible samples. 

The average estimate derived from all possible samples is or is not contained in any

particular computed margin of error. However, for a particular sample, one can say with 

specified confidence that the average estimate derived from all possible samples is included in 

the margin of error. 

Standard errors may also be used to perform hypothesis testing, a procedure for 

distinguishing between population parameters using sample estimates. The most common types 

of hypotheses appearing in this report are: (1) the population parameters are identical, and (2) the 

population parameters are different. An example of this would be comparing the vacancy rate 

inside MSAs versus the vacancy rate outside MSAs. Tests may be performed at various levels of 

significance, where a level of significance is the probability of concluding that the characteristics 

are different when in fact they are identical. 

To perform the most common test, let x and y be sample estimates for two characteristics 

of interest. Let the standard error on the difference x-y be SEDIFF. If the ratio R = (x-
10

y)/SEDIFF is between -1.645 and +1.645, no conclusion about the difference between the 

characteristics is justified at the 0.10 level of significance. If, on the other hand, this ratio is 

smaller than -1.645 or larger than +1.645, the observed difference is significant at the 0.10 level. 

In this event, it is a commonly accepted practice to say that the characteristics are different. Of 

course, sometimes this conclusion will be wrong. When the characteristics are in fact the same, 

there is a 10 percent chance of concluding that they are different. 

The Census Bureau uses 90-percent confidence intervals and 0.10 levels of significance 

to determine statistical validity. All statements of comparison in the text have passed a 

hypothesis test at the 0.10 level of significance. This means that, for most differences cited in the 

text, the absolute value of the estimated difference between characteristics is greater than or 

equal to 1.645 times the estimated standard error of the difference. In addition to sampling error, 

the figures in this report, both the estimates and their margins of error, are also subject to 

rounding error.

Illustration of the Use of Tables and Standard Errors 

The sample estimate and its standard error enable one to construct a margin of error. A 

margin of error is a measure of an estimate’s variability. The larger a margin of error is in 

relation to the size of the estimate, the less reliable the estimate. For example, the estimated 

percent of all housing units vacant and available for rent is 2.1 percent (Table 10) and the 

standard error on the estimate is 0.1 percentage points (Table A-1). The margin of error, at the 90 

percent confidence interval, is calculated as 1.645 x 0.1, or 0.2. Thus, the 90 percent confidence 

interval is from 1.9 percent to 2.3 percent. If all possible samples were surveyed under 

essentially the same general conditions and the same sample design, and if an estimate and its 

standard error were calculated from each sample, then approximately 90 percent of the margins 

of error would include the average result of all possible samples.