OpenLLM-France/wikimedia huggingface dataset:
# Survey research and design in psychology/Tutorials/Multiple linear regression/Exercises/Deterrence theory
## Deterrence theory and compliance with the law

Allen & Bennett Ch 13 Data file: data_13_2.sav
* View the accompanying screencast:
Deterrence theory suggests that compliance with the law is shaped by perceived certainty of punishment and perceived severity of punishment. When the perceived certainty (i.e., likelihood) and severity (i.e., personal costs) of punishment for breaking the law are high, law-breaking behaviour is predicted to be low. Conversely, when perceived punishment certainty and severity decrease, non-compliance with the law should increase.

### Standard

* View the accompanying screencasts:
To test deterrence theory, 62 participants were asked to complete a three-part questionnaire:
* Frequency of participants' everyday law breaking behaviours (e.g., littering, speeding, driving while intoxicated, shop-lifting etc.)
* Perceived certainty (likelihood) of being punished
* Personal severity (costs) of punishment.
Thus, the multiple linear regression model is:
* DV = (likelihood of) compliance (with the law).
* IV1 = (perceived) certainty (of being caught).
* IV2 = (perceived) severity (of punishment).
Results: R = .20, R2 = .04, F (2, 59) = 1.23, p = .30
Regression equation: Compliance = 2.969 + .154xCertainty + .015xSeverity

### Hierarchical

* View the accompanying screencasts:
For the second analysis, use IV1 and IV2 in Step 1 of a hierarchical MLR, with Step 2 consisting of:
* IV3 = (perceived) legitimacy (of the law / law-abidingness) (used in the hierarchical analysis).
* ↑ Allen, P. & Bennett, K. (2008). SPSS for the health and behavioural sciences. South Melbourne, Victoria, Australia: Thomson. | Companion site
# Survey research and design in psychology/Tutorials/Multiple linear regression/Exercises/English achievement
## English achievement

Francis 5.1.2 (pp. 120-122)
Data file: SCHL8.sav

### Design

Research question: To what extent can English Achievement in Year 8 be explained by socio-educational level (of parents), student gender, amount of English homework done by students and attentiveness paid in class?
* DV = engach (English Achievement)
* IV1 = sel (Socio-educational Level)
* IV2 = sex (Student gender)
* IV3 = enghomewk (Freq of English homework)
* IV4 = attent (Attentiveness in Year 8)

### Standard MLR

* View the accompanying screencasts:

### Hierarchical MLR

* View the accompanying screencast:

### Reference

Francis, G. (2007). Multiple linear regression (Section 5.1). In Introduction to SPSS for Windows: v. 15.0 and 14.0 with Notes for Studentware (5th ed.). Sydney: Pearson Education. Support site
* ↑ Francis, G. (2007). Introduction to SPSS for Windows: v. 15.0 and 14.0 with Notes for Studentware (5th ed.). Sydney: Pearson Education. | Support site
# Survey research and design in psychology/Tutorials/Psychometrics/Composite scores

This tutorial explains how to create composite scores in SPSS, using the compute function.

## Exercises

Exercise 1: Openness
View the accompanying screencast:
Data file: data_15_1.sav
Allen and Bennett 15.2, pp. 209-221
Create a composite satisfaction score as the average of responses to the nine items: Open1, Open3, Open7, Open9, Open2R, Open4R, Open6R, Open 8R, Open10R (where the R indicates a recoded item).
Open5 is dropped because analyses of internal consistency indicated that it didn't belong (it has negative and low correlations with other items and the Cronbach's alpha increases when it is removed). Why do you think it doesn't belong? (examine the wording of the item - "liberal" has different meanings in different contexts, e.g., in Australian politics, the Liberal Party is right-wing, whereas in North American politics, liberal means left-wing)
Open7 (carry conversation to a higher level) could be dropped or included - it has small positive correlations with the other items and the Cronbach's alpha would basically stay the same whether it was included or dropped
COMPUTE Openness=MEAN(Open1,Open2R,Open3,Open4R,Open6R,Open7,Open8R,Open9,OPen10R).
EXECUTE. :
# Survey research and design in psychology/Tutorials/Psychometrics

* This tutorial demonstrates theoretical principles and practice of exploratory factor analysis, internal consistency, and creating composite scores in the context of psychology and psychological measurement.

## Contents

* Lab report overview
* General steps
* Exploratory factor analysis
* Internal consistency
* Composite scores
* Sample write-ups

## Recordings

* Virtual tutorial recording, 2018
* Screencasts
# Physics equations/10-Rotational Motion and Angular Momentum/Q:dynamics

Equations for this quiz Solutions (pdf) Testbank
# Physics equations/11-Fluid statics
## Wikiquizzes

* Q:buoyantForce

## Discussion

Pascal's Principle states that pressure only depends on depth (and density) and does not depend on the shape of the vessel and that the force transmitted to the wall regardless of orientation.
# Physics equations/11-Fluid statics/Q:buoyantForce

Equations for this quiz Solutions (pdf) Testbank

## pe11BuoyantForce Version B

* ↑ user:Clockworks
# Physics equations/10-Rotational Motion and Angular Momentum

Q:dynamics
This will have the usual terse set of equations. The long stuff has been moved
# Physics equations/12-Fluid dynamics

Wikiquiz:
More discussion:
# Physics equations/12-Fluid dynamics/Q:pipeDiameterChange

Equations for this test Solutions (pdf) Testbank

## pe12pipeDiameterChange Version B

* ↑ Thanks to user:Clockworks, this is one of the first numerical wikiquizzes generated by something other than MS Excel in the summer of 2014.
# Physics equations/09-Statics and Torque
### Wikiquizzes

Q:torques

### More on the cross product

* b:General_Mechanics/Cross_Product might be the best wiki resource for most students
* w:Cross_product#Computing_the_cross_product
* Vectors#Vector_product_of_two_vectors
# Physics equations/11-Fluid statics/Q:buoyantForce/Testbank

Study: http://en.wikiversity.org/wiki/Physics_equations/Sheet/All_chapters
# Physics equations/09-Statics and Torque/Q:torques

Equations for this quiz Solutions (pdf) Testbank

## Practice quiz

More practice
# PlanetPhysics/Polish G Space

Let $X$ be a topological $G$-space, and $G$ its associated topological group (that is, such that an action $a$ of $G$ on $X$ is continuous if $a:G\times X\to X$ is continuous). If $G$ is a Polish group and $X$ is also a Polish space, then $X$ is called a Polish G-space .
# PlanetPhysics/Position

The position of an object is its location. It is usually denoted as $x$. When working in more than one dimension, position may be considered as a vector quantity; it can then be denoted as $\mathbf {x}$.
Position is frequently considered as a function of time. In the one-dimensional case, the notations $x(t)$ and (more rarely) $s(t)$ are used. On the other hand, when working in more than one dimension, the notation $\mathbf {x} (t)$ is used.
The SI unit of position is $\mathrm {m}$ (meters).
# PlanetPhysics/Position Vector

In the space $\mathbb {R} ^{3}$, the vector ${\vec {r}}\;:=\;(x,\,y,\,z)\;=\;x{\vec {i}}+y{\vec {j}}+z{\vec {k}}$ directed from the origin to a point \,$(x,\,y,\,z)$\, is the position vector of this point.\, When the point is variable, ${\vec {r}}$ represents a vector field and its length $r\;:=\;{\sqrt {x^{2}+y^{2}+z^{2}}}$ a scalar field.
The simple formulae
* $\nabla \!\cdot {\vec {r}}=3$
* $\nabla \!\times \!{\vec {r}}={\vec {0}}$
* $\nabla r={\frac {\vec {r}}{r}}={\vec {r}}^{0}$
* $\nabla {\frac {1}{r}}=-{\frac {\vec {r}}{r^{3}}}=-{\frac {{\vec {r}}^{0}}{r^{2}}}$
* $\nabla ^{2}{\frac {1}{r}}=0$
are valid, where ${\vec {r}}^{0}$ is the unit vector having the direction of ${\vec {r}}$.
If\, Failed to parse (syntax error): {\displaystyle \vec} \, is a constant vector,\, ${\vec {U}}\!\!:\mathbb {R} ^{3}\to \mathbb {R} ^{3}$\, a vector function and\, $f\!\!:\mathbb {R} \to \mathbb {R}$\, is a twice differentiable function, then the formulae
* Failed to parse (syntax error): {\displaystyle \nabla(\vec\cdot\!\vec{r}) = \vec}
* $\nabla \cdot ({\vec {\times }}{\vec {r}})=0$
* $({\vec {U}}\!\cdot \!\nabla ){\vec {r}}={\vec {U}}$
* $({\vec {U}}\!\times \!\nabla )\!\cdot \!{\vec {r}}=0$
* $({\vec {U}}\!\times \!\nabla )\!\times \!{\vec {r}}=-2{\vec {U}}$
* $\nabla f(r)=f'(r)\,{\vec {r}}^{0}$
* $\nabla ^{2}f(r)=f''(r)\!+{\frac {2}{r}}f'(r)$
hold.
# PlanetPhysics/Power
## Power

Power is the rate of energy transfer. Since there are several forms of energy, there are several ways of describing power. In general terms of energy, power is defined as
$P={\frac {dE}{dt}}.$

### Mechanical Power

The energy transfer in mechanical systems where work is done by an applied force
$P={\frac {dE}{dt}}={\frac {dW}{dt}}.$
Using the relation between work and force
$dW={\mathbf {F} }\cdot d{\mathbf {r} }$
and then differentiating to get power,
$P={\frac {dW}{dt}}={\mathbf {F} }\cdot {\frac {d{\mathbf {r} }}{dt}}={\mathbf {F} }\cdot {\mathbf {v} }.$
The corresponding form of power in rotation is
$P={\mathbf {M} }\cdot {\mathbf {\omega } },$
where ${\mathbf {M} }$ is the torque and ${\mathbf {\omega } }$ the angular velocity vector.

### Electrical Power

Since energy is transfering from a device storing electrical energy to another device in the circuit that converts to another form of energy, power is the rate of change of electrical potential energy. For a DC circuit
$P={\frac {dU}{dt}}=iV.$

### Units

The SI unit of the power is one joule per second, which is called watt :
${\frac {\mathrm {J} }{\mathrm {s} }}:=\mathrm {W} .$
The watt is equal to $\mathrm {kg\cdot m^{2}/s^{3}}$ in the base units.
The english units of power are
$1\left[horsepower\right]=1\left[hp\right]=550\left[{\frac {ft\,lb}{s}}\right]$
| 1 joule/second | = 1 watt |
| 1,000 watts | = 1 kilowatt |
| 746 watts | = 1 horsepower |
| 550 ft-lb/sec | = 1 horsepower |
| 33,000 ft-lb/min | = 1 horsepower |
# PlanetPhysics/Preadditive Functor

\newcommand{\sqdiagram}[9]{Failed to parse (unknown function "\diagram"): {\displaystyle \diagram #1 \rto^{#2} \dto_{#4}& \eqno{\mbox{#9}}} }
if for any pair of morphisms Failed to parse (unknown function "\A"): {\displaystyle f, g \in Hom_{\mathcal{\A_P}}(X,Y)} one has that $F(f+g)=F(f)+F(g)$.
# PlanetPhysics/Polar Coordinate Motion Example of Generalized Coordinates

As an example let us get the equations in polar coordinates for motion in a plane
Here $x=r\cos \phi ,\,\,\,\,\,\,\,\,\,y=r\sin \phi$
${\dot {x}}^{2}+{\dot {y}}^{2}=v^{2}={\dot {r}}^{2}+r^{2}{\dot {\phi }}^{2}$
and
$T={\frac {m}{2}}\left[{\dot {r}}^{2}+r^{2}{\dot {\phi }}^{2}\right]$
${\frac {\partial T}{\partial {\dot {r}}}}=m{\dot {r}}$
${\frac {\partial T}{\partial r}}=mr{\dot {\phi }}^{2}.$ $\delta _{r}W=m[{\ddot {r}}-r{\dot {\phi }}^{2}]\delta r=R\delta r$ if $R$ is the impressed force resolved along the radius vector. ${\frac {\partial T}{\partial {\dot {\phi }}}}=mr^{2}{\dot {\phi }},$
${\frac {\partial T}{\partial \phi }}=0.$
$\delta _{\phi }W=m{\frac {d}{dt}}(r^{2}{\dot {\phi }})\delta \phi =\Phi r\delta \phi$
if $\Phi$ is the impressed force resolved perpendicular to the radius vector.
In a more familiar form
$m\left[{\frac {d^{2}r}{dt^{2}}}-r\left({\frac {d\phi }{dt}}\right)^{2}\right]=R,$ ${\frac {m}{r}}{\frac {d}{dt}}\left(r^{2}{\frac {d\phi }{dt}}\right)=\Phi .$
# PlanetPhysics/Polish Group

Let $G$ be a topological group regarded as a topological space. Then $G$ is defined to be a Polish group if it is also a Polish space.
# Quantum mechanics/Course/Wave-particle duality quiz/gallery

These images will help you with the quiz, especially the first animation. Click on each image to enlarge. It would be appropriate to make these images available to students during an in-class test.
* The quiz was inspired by this animation
* Young's original drawing
* Animation (not actual data)
* Double slit diffraction
* Single slit diffraction
* Single slit diffraction
* Single slit diffraction
# Quantum mechanics/Course/Wave-particle duality quiz

This quiz is based on this gallery and on links contained within the quiz. For randomized versions of this quiz, use the testbank. For information on how to print out test copies (and other questions) see How to use testbank.
# Quantum mechanics/Essays

Please contribute an essay or article on Quantum mechanics. Enter title that is not already on the list below and start your draft. If you wish to change your title, or have any other questions, visit us at Wikiversity:Colloquium.
# Religious Law
## Resources

* The Laws of the Pharisees
* Shariah Law
* Agape
* Church Doctrine
* The Ten Commandments
# Relosophy
## What is Relosophy?

Relosophy is, generally speaking, the study of beliefs, attitudes, thoughts, and behaviors. It is a cross-disciplinary approach to understanding the human mind. In the study of Relosophy, it is understood that the lines between disciplines like Philosophy, Theology, and Political Science are often artificial constructs: philosophies, religions, and other ideologies are all manifestations of overarching relosophical viewpoints.
More specifically, relosophies are ideological paradigms held by individuals—be they religious, political, philosophical, or otherwise.
More generally, Relosophy is the analysis of all human knowledge, belief, thought, and behavior.
The goal of the School of Relosophy is to understand, using a cross-disciplinary approach, how these relosophies are formed, function, and interact in real terms.

## How can I get involved?

Right now, the Relosophy learning project is just getting its feet on the ground. Do you have any thoughts on content for the School?
* A "sampler course" is pending to introduce new participants to the concept of relosophy.

## Planned Projects

* Introduction to Relosophy

## Requested Courses/Projects

* Issues of Relosophy (101)

## Active participants

The following users have made contributions to this page or engaged in school-related discussion within the past three months, and are considered active contributors. Feel free to contact them with questions or for help:
    Users are sorted chronologically by first contribution to the school
* Jade Knight—September 2008
* Jolie-October 2008
There is an archive of previously-active contributors here.

### Announcements

* No announcements at this time.

## Related Schools and Departments

* Philosophy
* Theology
* Psychology
* Political Science
* Cognitive Science
# Reliability and validity/Data analysis tutorial

Data analysis tutorials for reliability and validity:
* Internal consistency
* Composite scores
* Test-retest reliability
# Reliability engineering

Reliability is a broad term that focuses on the ability of a product to perform its intended function. Reliability can be defined as the probability that an item will continue to perform its intended function without failure for a specified period of time under stated conditions. The product or a system defined here could be an electronic or mechanical hardware product, a software product, a manufacturing process or even a service.
Reliability engineering consists of the systematic application of time-honored engineering principles and techniques throughout lifecycle of an item,product,assembly or a system. Its goal is to evaluate the inherent reliability of a product or process and showcase potential areas for improvement in its reliability. As all failures cannot be eliminated from a design, hence another goal of reliability engineering is to identify the most likely failures and then identify appropriate actions to reduce the effects of those failures.

## See Also

* Wikipedia: Reliability engineering
# Religiosity

This Theology resource is a "stub". Learn how you can help Wikiversity to develop it.
Religiosity refers to the extent and nature of a person's orientation towards religious and spiritual beliefs, experiences, and actions.
# Reliability
## Pre-requisites

Before reading this section, make sure you understand:
* Correlation

## Reliability

In psychological measurement, reliability refers to the reproducibility or consistency of scores from a measure in a particular sample.
We commonly describe cars, for example, in terms of their reliability. A reliable car is one that starts every time ignition is attempted. An unreliable car doesn't start all the time.
There are several types of reliability that are commonly examined in psychological measurement:
* Internal consistency (Internal reliability): Correlation amongst the items used in a multi-item measurement scale, providing a sense of whether the items are measuring the "same thing"
* Test-retest reliability: Correlation between scores on the same measure by the same participants at different times
* Inter-rater reliability: Correlation between scores by different raters (observers); for observational measures
It is possible to look at other factors that influence the reproducibility of scores. The most fully developed methods for studying these include generalizability theory and item response theory approaches.
Current thinking, as well as the standards (AERA, 2014), emphasizes that reliability is not an intrinsic property of a measure. Reliability refers to the performance of scores observed in a particular sample or setting. When the measure is used with someone similar to the sample used to evaluate the reliability, then the score is likely to perform similarly. When the person is different from the samples used to develop and benchmark the measure, then the scores may not generalize. A spelling test designed for eighth graders may do a good job ranking new eighth graders in terms of spelling performance, but the same test might not show good reliability for 4th graders or college students.
# Reliability and validity
## Pre-requisites

Before reading this section, make sure you understand:
* Reliability
* Validity
as separate concepts.

## Relationship between reliability and validity

Reliability and validity are important concepts within psychometrics.
Reliability is generally thought to be necessary for validity, but it does not guarantee validity.
Reliability and validity are, conceptually, quite distinct and there need not be any necessary relationship between the two. Be wary of statements which imply that a valid test or measure has to be reliable. Where the measurement emphasis is on relatively stable and enduring characteristics of people (e.g. their creativity), a measure should be consistent over time (reliable). It also ought to distinguish between inventors and the rest of us if it is a valid measure of creativity. A measure of a characteristic which varies quite rapidly over time will not be reliable over time - if it is then we might doubt its validity. For example, a valid measure of suicide intention may not be particularly stable (reliable) over time though good at identifying those at risk of suicide.
Validity is often expressed as a correlation between the measure and some criterion. This validity coefficient will be limited or attenuated by the reliability of the test or measure. Thus, the maximum correlation of the test of measure with any other variable has an upper limit determined by the internal reliability.
Within classical test theory, predictive or concurrent validity (correlation between the predictor and the predicted) cannot exceed the square root of the correlation between two versions of the same measure — that is, reliability limits validity.
With this in mind, it can be helpful to conceptualize the following four basic scenarios for the relation between reliability and validity:
* Reliable (consistent) and valid (measures what it's meant to measure, i.e., a stable construct)
* Reliable (consistent) and not valid (measures something consistently, but it doesn't measure what its meant to measure)
* Unreliable (not consistent) and not valid (inconsistent measure which doesn't measure what its meant to measure)
* Unreliable (not consistent) and valid (measures what its meant to measure, i.e., an unstable construct)
It is important to distinguish between internal reliability and test-retest reliability. A measure of a fluctuating phenomenon such as suicide intention may be valid but have low test-retest reliability (depending on how much the phenomenon fluctuates and how far apart the test and retest is), but the measure should exhibit good internal consistency on each occasion.

## Data analysis exercises

* Data analysis tutorial
# Unit Testing/Pytest/Test Output
## Create a Python Program

Create the following Python program. Save it as multiply.py

## Create a Test Program

Create the following Pytest test program. Save it as test_multiply.py

## Test Success

Test the program by running pytest in a terminal or command prompt in the same folder as the two programs above and observe the results.

## Test Failure

Change the test source code somehow, such as replacing one of the input numeric values with a different value. Test the program by running pytest again and observe the results.
# Unit Testing/xUnit.net

xUnit.net is a free and open-source unit testing tool for the .NET Framework, written by the original author of NUnit.

## Readings

* Wikipedia: Test automation
* Wikipedia: xUnit.net

## Activities

* Install xUnit
* Create a Simple Test
* Test Exceptions
* View Test Coverage

## See Also

* Wikipedia: xUnit.net
# Unit Testing/xUnit.net/Create a Simple Test
## Create a C# Program

Create the following C# program. Save it as Multiply.cs

## Create a Test Program

Create the following C# test program. Save it as MultiplyTest.cs

## Test Success

Test the program by running the following command in a terminal or command prompt in the same folder as the project above and observe the results.

## Test Failure

Change the multiply source code somehow, such as multiplying by 0 rather than multiplying by y. Test the program by running the test again and observe the results.
# Unit Testing/Pytest/Create a unittest Test
## Create a Python Program

Create the following Python program. Save it as multiply.py

## Create a Test Program

Create the following Pytest test program. Save it as either test_multiply.py or multiply_test.py

## Test Success

Test the program by running pytest in a terminal or command prompt in the same folder as the two programs above and observe the results.

## Test Failure

Change the multiply source code somehow, such as multiplying by 0 rather than multiplying by y. Test the program by running pytest again and observe the results.
# Unit Testing/Pytest/Create an assert Test
## Create a Python Program

Create the following Python program. Save it as multiply.py

## Create a Test Program

Create the following Pytest test program. Save it as test_multiply.py

## Test Success

Test the program by running pytest in a terminal or command prompt in the same folder as the two programs above and observe the results.

## Test Failure

Change the multiply source code somehow, such as multiplying by 0 rather than multiplying by y. Test the program by running pytest again and observe the results.
# Unit Testing/Pytest/Install Pytest

Create a Python test environment.
* Install Python3 from Python.org.
* Install Pytest using either:
** pip install pytest
** pip3 install pytest
# Unit Testing/Pytest/Test Input
## Create a Python Program

Create the following Python program. Save it as multiply.py

## Create a Test Program

Create the following Pytest test program. Save it as test_multiply.py

## Test Success

Test the program by running pytest in a terminal or command prompt in the same folder as the two programs above and observe the results.

## Test Failure

Change the test source code somehow, such as replacing one of the input numeric values with characters. Test the program by running pytest again and observe the results.
# Unit Testing/Pytest/Test Exceptions
## Create a Python Program

Create the following Python program. Save it as multiply.py

## Create a Test Program

Create the following Pytest test program. Save it as test_multiply.py

## Test Success

Test the program by running pytest in a terminal or command prompt in the same folder as the two programs above and observe the results.

## Test Failure

Change the test source code somehow, such as replacing the invalid input with valid input. Test the program by running pytest again and observe the results.