OpenLLM-France/wikimedia huggingface dataset:
# Mean

The mean or arithmetic mean of a set of numbers is obtained by adding the numbers and dividing the result by the 'number' of numbers. It is a key piece of information: if you randomly sample some numbers from the series, you expect them to fluctuate around the mean, and the larger the sample, the closer their average will tend to be to the mean of the series.
An alternative indicator of average is the median, the middle number if all numbers are ordered according to size. The mean and the median need not have the same value; in some cases, the difference can be quite considerable.

## Example

Consider the following set of numbers:
{ 5, 4, 10, 3, 3, 4, 7, 4, 6, 5 }
First, you add the numbers to find their sum, that is:
5 + 4 + 10 + 3 + 3 + 4 + 7 + 4 + 6 + 5 = 51
Then you divide that by the number of numbers. In this case, there are 10, so the mean of this set of numbers is:
51 / 10 = 5.1

## Properties

Note from the example above, that:
* the order of the numbers in the set does not affect the mean;
* if one of the numbers is increased, and another is decreased by an equal amount, the mean will stay the same;
* if the set is divided into subsets of equal size, the mean of all the means of the subsets equals the mean of the set.
The above rules can often be used to calculate the mean of a given set faster. Note further that:
* if one of the numbers is changed, the mean changes in the same direction;
* unless all numbers are equal, there will always be at least one number larger than the mean, and at least one number smaller.
The last property implies that, for instance, it is not possible that all stocks on the stock market are outperformers.

## Questions

Which of the following statements are true, and which are false?
* If 10 is added to each number in the set, but one of the numbers was negative, the mean will grow by less than 10
* If all the numbers in the set get multiplied by 2, the mean is doubled as well
* The mean of a set of even numbers will always be an even number
* The mean of a set of odd numbers will never be an odd number
* The mean of the first half of the set is generally closer to the mean of the full set than the mean of the second half
* Seeing one of the numbers provides more information on the mean of the set than seeing a second one
* Upon removing both the highest and the lowest number from the set, the mean is expected to stay the same
# Materials Science and Engineering/Catalogue
## Catalogue of Materials

* Review Questions before PhD Qualifying Exam
* List of Materials Related Topics Grouped by Course
* Progression of Topics
# Material Requirements Planning

Material requirements planning (MRP) is a production planning and inventory control system used to manage manufacturing processes.
Most MRP systems are software-based, while it is possible to conduct MRP by hand as well.
An MRP system is intended to simultaneously meet three objectives:
* Ensure materials are available for production and products are available for delivery to customers.
* Maintain the lowest possible level of inventory.
* Plan manufacturing activities, delivery schedules and purchasing activities.

## Resources

* Enterprise Resource Planning
* Intermediate Items
* Item
* Products
* Raw Materials
* Raw Materials, Intermediate Items & Products
# Geochronology/Potassium–argon dating

The method most commonly used to date the primary standard is the potassium-argon dating technique.

## Hypotheses

* Each time frame or span of time in geochronology has at least one dating technique.
* Late Jurassic is a time frame and Upper Jurassic is a stratigraphic frame so both are different time frames.
* The overall size of—or efficiency of carbon export from—the biosphere decreased at the end of the Great Oxidation Event (GOE) (ca. 2,400 to 2,050 Ma).
# Geochronology/Palynology
## Sequence table

European Pollen Zones :
| Zone | Biostratigraphic division | Dates | Dominant plant type | Archaeological periods | Geological stage |
| IX | Sub-Atlantic | 500 BC to present | Spread of grasses and pine and beech woodland | Iron Age onwards | Flandrian interglacial |
| VIII | Sub-Boreal | 3000 - 500 BC | Mixed oak forest | Bronze Age and Iron Age | Flandrian |
| VII | Atlantic period | 5500 -3000 BC | Mixed oak forest | Neolithic and Bronze Age | Flandrian |
| V and VI | Boreal | c. 7700 - 5500 BC | Pine/birch forest and increasing mixed forest | Mesolithic | Flandrian |
| IV | Boreal - Pre-Boreal | c. 8300 - 7700 BC | Birch forest | Late Upper Palaeolithic and early - mid Mesolithic | Devensian glaciation and Flandrian |
| III | Younger Dryas | c. 8800 - 8300 BC | Tundra | Late Upper Palaeolithic | Devensian |
| II | Allerød Oscillation | c. 9800 - 8800 BC | Tundra, Park Tundra and birch forest | Late Upper Palaeolithic | Devensian |
| Ic | Older Dryas | c. 10,000 - 9800 BC | Tundra | Late Upper Palaeolithic | Devensian |
| Ib | Bølling Oscillation | c. 10,500 - 10,000 BC | Park Tundra | Late Upper Palaeolithic | Devensian |
| Ia | Oldest Dryas | c. 13,000 - 10,500 BC | Tundra | Late Upper Palaeolithic | Devensian |
# Geochronology/Neoglaciations

In the image at the top, "before present" is used in the context of radiocarbon dating, where the "present" has been fixed at 1950. The apparent decreases in solar activity are called the "Maunder Minimum", "Spörer Minimum", "Wolf Minimum", and "Oort Minimum".
"Northern Hemisphere summer temperatures over the past 8000 years have been paced by the slow decrease in summer insolation resulting from the precession of the equinoxes."
A "climate interpretation was supported by very low δ’s in the 1690’es, a period described as extremely cold in the Icelandic annals. In 1695 Iceland was completely surrounded by sea ice, and according to other sources the sea ice reached half way to the Faeroe Islands."

## Little ice ages

The Little Ice Age (LIA) appears to have lasted from about 1218 (782 b2k) to about 1878 (122 b2k).
Precisely "dated records of ice-cap growth from Arctic Canada and Iceland [show] that LIA summer cold and ice growth began abruptly between 1275 and 1300 AD, followed by a substantial intensification 1430-1455 AD. Intervals of sudden ice growth coincide with two of the most volcanically perturbed half centuries of the past millennium. [Explosive] volcanism produces abrupt summer cooling at these times, and that cold summers can be maintained by sea-ice/ocean feedbacks long after volcanic aerosols are removed. [The] onset of the LIA can be linked to an unusual 50-year-long episode with four large sulfur-rich explosive eruptions, each with global sulfate loading >60 Tg. The persistence of cold summers is best explained by consequent sea-ice/ocean feedbacks during a hemispheric summer insolation minimum; large changes in solar irradiance are not required."

## Hypotheses

* The sciences do not need to follow the humanities, religion, or the arts to be beneficial to humanity.
* The scientific method is not a recent occurrence.
# Geochronology/Orbitally forced cyclicity

"Chemical and physical proxies from sedimentary rock sequences are frequently used for palaeoclimatic studies and for detecting orbitally forced cyclicity in marine Cenozoic sequences and calibrating recognized sedimentary cycles to time-periodicity."

## Magnetic susceptibility

"Spectral analysis of the [magnetic susceptibility (MS)] record reveals the presence of the complete suite of orbital frequencies in the precession, obliquity, and eccentricity (95–128 ka and 405 ka) bands with very high amplitude of the precession index cycles originating from [decimeter (dm)] dm-scale couplets."

## Ammonites

"Ammonite zone duration estimates are made by counting the interpreted precession cycles, and provide an ultra-high resolution assessment of geologic time."

## Astronomical tuning

An alternative method of calibrating the used standard is astronomical tuning (also known as orbital tuning), which arrives at a slightly different age.

## Cyclostratigraphy

Cyclostratigraphy is the study of astronomically forced climate cycles within sedimentary successions.

## Milankovitch cycles

Astronomical cycles (also known as Milankovitch cycles) are variations of the Earth's orbit around the sun due to the gravitational interaction with other masses within the solar system.

## Precessions

The main orbital cycles are precession with current main periods of 19 and 23 kyr, obliquity with main periods of 41 kyr, and 1.2 Myr, and eccentricity with main periods of around 100 kyr, 405 kyr, and 2.4 Myr.

## Eccentricity cycles

The 405 kyr eccentricity cycle helps correct chronologies in rocks or sediment cores when variable sedimentation makes them difficult to assign. Indicators of these cycles in sediments include rock magnetism, geochemistry, biological composition, and physical features like color and facies changes.
# Instructional design/User testing of e-learning courses/Elements of an Evaluation Plan

Back to Topic: Instructional Design > User Testing of E-Learning Courses > Review Evaluation Plan
Before beginning any formative evaluation, a test plan needs to be developed. Morrison, Ross, and Kemp (2004) identify eight elements to every plan that are modified for each evaluation. These elements direct the testing for all instructional mediums, such as e-learning, classroom, and printed material.

## The Plan in Review

The eight elements to any evaluation plan are:
1. Purpose
Why is the evaluation being conducted? First, ask yourself if the evaluation is necessary. If so, then what is the evaluation’s purpose:
a.) to improve the material? b.) to determine time requirements? c.) to satisfy administrative requirements?
2. Audience
Who are the target recipients of the evaluation results? The audience will determine the type of information collected and reported.
3. Issues
What are the major questions/objectives of the evaluation? This sets the stage for the evaluation. These determine what data collection instruments and analysis are needed to provide answers to the questions/objectives that have been determined.
4. Resources
What resources will be needed to conduct the evaluation? Resources differ between objectives. They can include SMEs, students, data collection instruments, equipment, etc.
5. Evidence
What type of data or information will be needed to answer the evaluation questions? Give careful consideration to the type of evidence needed to answer the questions/objectives under the issues section. Consider such things as sample size, realism of exercise, participant objectivity, etc.
6. Data-gathering Techniques
What methods are needed to collect the evidence needed? Use multiple techniques to increase the validity of the results. Some examples are observation, questionnaires, interviews, and performance tests.
7. Analysis
How will the evidence collected be analyzed? Use descriptive analysis in the report and address the issues/objectives in a straightforward manner. Traditionally, frequency distributions and graphs/histograms have been used. Today, descriptive statistics and actual tester comments are frequently used as analysis procedures.
8. Reporting
How, to whom, and when will the results of the evaluation be reported? An evaluation report is distributed to the identified audience. The main report headings are: executive summary, purpose of evaluation, methodology, results, and conclusions and recommendations.
Now that you know the elements of an evaluation plan and the specific types of content, you're ready to move to the next topic, a completed user test plan. These elements have been tailored into a test plan that will be used to guide the testing of a Wikiversity page that will be performed in the next lesson.
| Previous | Next |
Click Next to learn about evaluation for e-learning courses.
Back to Topic: Instructional Design > User Testing of E-Learning Courses > Review Evaluation Plan
# Instructional design/User testing of e-learning courses/Knowledge Check

Back to Topic: Instructional Design > User Testing of E-Learning Courses > Course Introduction

## Knowledge Check 1

...kcheck content here...

## Knowledge Check 2

...kcheck content here...

## Knowledge Check 3

...kcheck content here...

## Knowledge Check 4

...kcheck content here...
# Instructional design/User testing of e-learning courses/Course Resources

Back to Topic: Instructional Design > User Testing of E-Learning Courses > Course Summary

## Websites

...page content here...

## Documents

...page content here...
# Instructional design/User testing of e-learning courses/Formative Evaluation Overview

Back to Topic: Instructional Design > User Testing of E-Learning Courses

## Overview

In this lesson, you'll learn about how formative evaluations fit into the "E" of ADDIE. The ADDIE instructional systems design (ISD) model uses formative evaluation throughout its life cycle, not just at the end as a final evaluation. “Formative” means to shape or transform; it should be conducted at regular review intervals during the development cycle. “User Testing” is a specific type of formative evaluation that occurs at the end of the development cycle.

## Objectives

Upon completion of this lesson, you will be able to:
* Describe formative evaluation
* Explain what user testing is
* Explain why to conduct user testing

## Lesson Topics

To go to a topic, click its title below:
* Reviewing Evaluation Fundamentals
* Check Your Knowledge 1
| Previous | Next |
Click Next to go to the first topic in this lesson.
Back to Topic: Instructional Design > User Testing of E-Learning Courses
# Instructional design/User testing of e-learning courses/Developing a Plan

Back to Topic: Instructional Design > User Testing of E-Learning Courses

## Overview

...in this lesson...

## Objectives

Upon completion of this lesson, you will be able to:
* objective 1
* objective 2

## Lesson Topics

To go to a topic, click its title below:
* Why Develop a Plan?
* Elements of a Plan
* Creating the Plan
* Check Your Knowledge 3
* Job Aids
# Instructional design/User testing of e-learning courses/Course Introduction

Back to Topic: Instructional Design > User Testing of E-Learning Courses

## Overview

In this lesson, you'll learn about how formative evaluations fit into the "E" of ADDIE. The ADDIE instructional systems design model uses formative evaluation throughout its life cycle, not just at the end as a final evaluation. “Formative” means to shape or transform; it should be conducted at regular review intervals during the development cycle. “User Testing” is a specific type of formative evaluation that occurs at the end of the development cycle.

## Objectives

Upon completion of this lesson, you will be able to:
* Describe Formative Evaluation
* List different stages and examples of Formative Evaluation

## Lesson Topics

To go to a topic, click its title below:
* Before You Begin
* Check Your Knowledge 1
# Instructional design/User testing of e-learning courses/Course Summary

Back to Topic: Instructional Design > User Testing of E-Learning Courses

## User Testing of E-learning Courses

In this course, you learned how to describe the role formative evaluation plays in the ADDIE model, as well as the role user testing plays in the development of an e-learning course. In addition, you learned how to create a user testing plan for an e-learning course and how to conduct the test. Finally, you learned how to analyze the results of the user test.
This isn't all there is to conducting a User Test. After analyzing the results of the test, there are several more steps that you'll need to go through. These steps, preparing a report and implementing your findings, are described briefly in this lesson's "Next Steps" topic.
The "Resources" topic provides you with a comprehensive list of all the .... presented in this course.

## Lesson Topics

To go to a topic, click its title below:
* Next Steps
* Module Resources
# Instructional design/User testing of e-learning courses/Developing a Plan/Why develop a plan?

Back to Topic: Instructional Design > User Testing of E-Learning Courses > Developing a Plan

## Page 1 Header

...page content here...

## Page 2 Header

...page content here...

## Page 3 Header

...page content here...

## Page 4 Header

...page content here...
# Instructional design/User testing of e-learning courses/Evaluation Tips

Back to Topic: Instructional Design > User Testing of E-Learning Courses > Conducting User Testing
The following tips have been adopted from the article, "Virtual Formative Evaluation: Twelve Tips for E-Learning" by Peter Honebein and Darryl Sink (2006). The artle is specific to the virtual observation but the concepts are helpful in conducting user test of an e-learning course.

## The Tips

* Record the test
* Focus on a single subject per person
   Make sure each tester has their own computer and when possible, observe one tester at a time.
* Describe the learning scenario
   * Always communicate the goals of the test. For user testing, the goal is to assess the course usability and learner attitudes while completing the instruction. It’s important to assure them they are not being tested, the instruction.
   * Don’t provide too much detail or commentary about the course because it should be self explanatory. If the tester runs into problems, that’s a sign there’s something wrong with the instruction.
   * Ask the tester to talk out loud while performing the testing. Not only the steps they’re taking but also what they’re thinking about the course itself and various parts such as activities, images, etc. If the test is self-paced, encourage them to write down their comments.
* Listen for triggers via words, body language, and mouse mania.
   If an observer is not present, a background program such as WebTrends can report how many times a user clicks on a certain page within the course or runs a particular interface element.
* Prioritize learning activities.
* Perform On-The-Fly updates if possible
   Testers have a more positive evaluation experience if they can see their suggestions implemented while they’re testing.
* Provide Feedback and Subsequent Engagement
   Provide additional feedback tools as links within the course they’re testing. This feedback can be submitted directly to a database or via email to the designer.
Are you ready to put all of this together and perform a user test on an e-learning Wikiversity page?
| Previous | Next |
Click Next to check your understanding.
Back to Topic: Instructional Design > User Testing of E-Learning Courses > Conducting User Testing
# New Zealand Pilot License/Meteorology

There are two related subjects for the New Zealand Pilot Licenses:
* Commercial
* Private
# New journalism
## New Journalism - An overview

New Journalism is a broad term for how journalism is changing as the internet and technology enhance how journalists report and deliver the news. New media involves blogging, podcasting, webcasting, and Twittering. It improves upon what journalism is a about: news. By breaking a story at almost the instant it happens, and spreading it around the net, the news travels fast.
The biggest factor in new journalism is that the professional journalist now must compete with the general populace when it comes to reporting. With the aid of blogs and smart phones, any amateur can become a field reporter. Many news agencies, such as CNN, have specialized iReport sites that allow the people to input their field work to gain better coverage of the news.

## Common types of New Journalism

* Blogging
* Crowdsourcing
* Citizen journalism

## See Also

* School:Journalism
* Wikinews
# New Zealand Pilot License/Human Factors

There are two related subjects for the New Zealand Pilot Licenses:
* Commercial
* Private
# PlanetPhysics/Fuzzy Logics of Living Organisms
### Fuzzy logics of living organisms

Living organisms or biosystems can be represented as super-complex systems with dynamics that is not reducible to that of their components, such as molecules and atoms. It is an empirically accepted fact that living organisms exhibit a wide degree of `biological variability': genetic, epigenetic and also phenotypic, metabolic within the same species; their behavior and dynamics thus exhibit a type of `fuzziness' (refs.) that unlike Zadeh's fuzzy sets characteristic is neither random nor always following a (symmetric) Gaussian distribution. It has been proposed that the operational logics underlying super-complex systems dynamics are $LM_{n}$ many-valued logics for both genetic and neural networks (refs.).
# PlanetPhysics/Gamma Function

The gamma function is
$\Gamma (x)=\int _{0}^{\infty }e^{-t}t^{x-1}dt$
where $x\in \mathbb {C} \setminus \{0,-1,-2,\ldots \}$.
The Gamma function satisfies
$\Gamma (x+1)=x\Gamma (x)$
Therefore, for integer values of $x=n$,
$\Gamma (n)=(n-1)!$
Some values of the gamma function for small arguments are:
${\begin{matrix}\Gamma (1/5)=4.5909&\Gamma (1/4)=3.6256\\\Gamma (1/3)=2.6789&\Gamma (2/5)=2.2182\\\Gamma (3/5)=1.4892&\Gamma (2/3)=1.3541\\\Gamma (3/4)=1.2254&\Gamma (4/5)=1.1642\end{matrix}}$
and the ever-useful $\Gamma (1/2)={\sqrt {\pi }}$. These values allow a quick calculation of
$\Gamma (n+f)$
Where $n$ is a natural number and $f$ is any fractional value for which the Gamma function's value is known. Since $\Gamma (x+1)=x\Gamma (x)$, we have
   ${\begin{matrix}\Gamma (n+f)&=&(n+f-1)\Gamma (n+f-1)\\&=&(n+f-1)(n+f-2)\Gamma (n+f-2)\\&\vdots &\\&=&(n+f-1)(n+f-2)\cdots (f)\Gamma (f)\end{matrix}}$
Which is easy to calculate if we know $\Gamma (f)$.
The gamma function has a meromorphic continuation to the entire complex plane with poles at the non-positive integers. It satisfies the product formula $\Gamma (z)={\frac {e^{-\gamma z}}{z}}\prod _{n=1}^{\infty }\left(1+{\frac {z}{n}}\right)^{-1}e^{z/n}$
where $\gamma$ is Euler's constant, and the functional equation
$\Gamma (z)\Gamma (1-z)={\frac {\pi }{\sin \pi z}}.$
This entry is a derivative of the gamma function article from PlanetMath. Author of the orginial article: akrowne. History page of the original is here
# PlanetPhysics/Gauge Bosons 2

Gauge bosons are (quantum) particles of zero or integer spin (i.e., bosons or particles that follow the Bose-Einstein statistics) which act as the carriers of the four fundamental forces of nature. Thus, the major gauge boson classes are: photons, W and Z bosons/Higgs bosons, gluons and gravitons , that are carriers of, respectively, electromagnetic interactions, (electro)weak interactions (W and Z), strong interactions and gravitational ones.
Unlike photons and (W,Z) bosons, the scalar massive Higgs bosons (spin-0) and (massless) gravitons (spin-2 bosons) are yet to be observed, and are thus considered hypothetical. Therefore, the Standard Model of physics currently includes only photons, W, Z bosons and gluons.
In quantum gauge theories, gauge bosons are the quanta of gauge fields. There are distinct gauge (symmetry) groups associated with each class of gauge bosons. Thus, the gauge group of electromagnetic interactions in quantum electrodynamics (QED) is the unitary symmetry group $U(1)$ as it has only one gauge boson --the photon. On the other hand, in quantum chromodynamics (QCD) the gauge group is the special unitary group $SU(3)$ corresponding to the eight different gluon types (distinguished by their quantum flavors) which are responsible for the strong interactions.
Note also that not all bosons are field carriers, and thus there are many more bosons besides the gauge bosons, such as: the deuteron, all nuclei of either zero or integer spin, Cooper (electron) pairs and all quasi-particles of either zero or integer spin.