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Welcome to the BA Sociology Statistical Matrix! Advancement
in academia typically depends upon Scientific publishing. The more you
publish, the better the first job, the higher the raise, and the faster
the promotion. Sadly only 8% of publications come from developing
countries, despite the fact that 27% of the scientists live in
developing countries and 80% of the scientists.
In almost all disciplines in Science students are required to learn
about statistics. However, statistics is a difficult topic to learn and
learning it in a second language makes it doubly difficult. A primary
reason for this is Stataphobia which is the fear of research design and
statistics, and not having access to people who can help. Stataphobia
makes it most difficult to learn about statistics. Eighty percent of all
rejected articles are due to poor research methods.
Much of what we use across disciplines is the result of the building of
research methods in the area of Sociology. We have therefore built a BA(Bibliotheca
Alexandrina) Sociology Statistical Matrix! Research
Methods Library of Alexandria (RMLA) for Sociology.
The components of the BA
Sociology Statistical include:
1.
Sociology Specific
Methods: This is a collection of lectures presenting
Sociology
specific research methods, including Quantitative and Qualitative
research methods,
Social
networking, Culture and Ethics, etc. For each area there are multiple lectures by
different faculty to learn.
2.
The General Research
methods matrix. If a student has a question about hypothesis testing
they have 5 lectures by different faculty to learn from
(below):
Agriculture
Statistics Matrix
Anthropology Statistics Matrix
Statistics Matrix
in Arabic
Statistics Matrix in
English
Farsi Statistics
Matrix Japanese
Statistics Matrix
Psychology Statistics Matrix
Russian Statistics
Matrix
Sociology Statistics Matrix
The first column of the
Matrix
has been left empty; this allows for individual adaptation of the
Matrix, where a lecturer may insert their own lecture materials (video,
powerpoint, etc.). Enjoy! |
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Add your own lectures here!
↓ ↓ |
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Developer Curtis Tilves under the direction of Malcolm Elliot, Faina
Linkov, Eric Marler, Francois Sauer, Ismail
Serageldin, Eugene Shubnikov, Ronald LaPorte and
Supercourse and Library of Alexandria
teams. Developers of
Matrices. |
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Bibliotheca Alexandrina
Sociology Statistical Matrix |
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Khan Academy Channel: Statistics playlist |
Brandon Foltz |
Statslectures |
Statisticsfun |
OnlineStatBook.com |
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Khan Academy (khanacademy.org) is a
non-profit organization which utilizes a computerized blackboard to
illustrate each step of a problem. "Our mission to provide a world-class
education for anyone, anywhere." |
Brandon Foltz has a masters in Education and
a passion for sharing knowledge. "My videos are full-length lessons...so
grab some coffee, tea, lassi, Apokat, sbiten', soo chunkwa...or whatever
sounds tasty and relaxing." |
These series of YouTube videos are brought
to you by StatisticsLectures.com. "We focus on creating short, applied
content with an emphasis on the logic behind various statistical
methods." |
David Longstreet from MyBookSucks.com
expertly takes you through several statistical concepts. "The goal is
to use 21st century tools to deliver education and learning for
statistics." |
David Lane is the principal developer of this resource although many
others have made substantial contributions. This site was developed at
Rice University, University of Houston-Clear Lake, and Tufts University. |
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Statistics: The Average |
12:35 |
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Central Tendency: Mean, Median, and Mode |
3:47 |
How to Calculate Mean and Standard Deviation |
2:12 |
Median and Mean |
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Mean and Median Demonstration |
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Statistics: Sample vs. Population Mean |
6:42 |
Population vs Sample Data |
26:47 |
Arithmetic Mean for Samples and Populations |
2:46 |
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What is Central Tendency? |
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Measures of Central Tendency |
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Balance Scale Simulation |
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Additional Measures of Central Tendency |
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Comparing Measures of Central Tendency |
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Point Estimators |
14:48 |
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Introduction to Estimation |
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Characteristics of Estimators |
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Statistics: Variance of a Population |
12:23 |
Variance and its Sampling Distribution |
27:20 |
Variance and Standard Deviation of a Population |
5:01 |
Why are Degress of Freedom (n-1) Used in Variance and Standard Deviation |
7:05 |
Measures of Variability |
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Variability Simulation |
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Variation Simulation |
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Effects of Linear Transformations |
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Variance Sum Law I |
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Statistics: Sample Variance |
11:18 |
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Variance and Standard Deviation of a Sample |
5:46 |
How to Calculate Standard Deviation, Mean, Variance Statistics, Excel |
4:35 |
Degrees of Freedom |
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Statistics: Standard Deviation |
13:07 |
Standard Deviation and NFL Field Goals - Part 1/3 |
20:05 |
Variance and Standard Deviation of Discrete Random Variables |
2:51 |
Standard Deviation and Variance (Explaining Formulas) |
5:31 |
Absolute Deviation Simulation |
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Standard Deviation and NFL Field Goals - Part 2/3 |
26:26 |
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How to Calculate Standard Deviation and Variance |
5:05 |
Squared Deviation Simulation |
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Standard Deviation and NFL Field Goals - Part 3/3 |
6:45 |
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Calculating Standard Deviation Using Excel |
6:01 |
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Statistics: Alternate Variance Formulas |
12:17 |
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Introduction to Random Variables |
12:04 |
Random Variable Basics |
11:59 |
Types of Variables |
3:34 |
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Variables |
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Discrete Random Variable Basics |
12:46 |
Independent and Dependent Variables |
1:28 |
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Discrete Random Variable Probabilities |
19:42 |
Discrete and Continuous Random Variables |
2:17 |
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Discrete Random Variable Variance |
26:16 |
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Probability Density Functions |
10:02 |
Uniform Probability Distribution |
30:31 |
Frequency Distributions and Cumulative Frequency Distributions |
1:35 |
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Distributions |
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Discrete Probability Distributions |
1:56 |
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Shapes of Distributions |
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Comparing Distributions |
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Binomial Distribution 1 |
12:16 |
The Binomial Distribution |
36:50 |
Binomial Distribution |
4:25 |
Binomial Distribution Probability Coins |
7:52 |
Binomial Distribution |
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Binomial Distribution 2 |
11:05 |
Binomial Mean and Standard Deviation |
21:41 |
Mean and Standard Deviation of Binomial Random Variables |
1:39 |
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Binomial Demonstration |
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Binomial Distribution 3 |
13:27 |
Simple Binomial Sales Quota Analysis |
20:41 |
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Normal Approximation to the Binomial |
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Binomial Distribution 4 |
10:46 |
Binomially Distributed Mac OS X User Rate |
32:43 |
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Multinomial Distribution |
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Binomially Distributed Factory Accident Data |
20:42 |
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Expected Value: E(X) |
14:53 |
Expected Value |
21:18 |
Mean and Expected Value of Discrete Random Variables |
1:51 |
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Expected Value of a Binomial Distribution |
16:56 |
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Poisson Process 1 |
11:01 |
Introduction to the Poisson Distribution |
31:14 |
Poisson Distribution/Process |
3:18 |
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Poisson Distribution |
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Poisson Process 2 |
12:42 |
Poisson Practice Problems |
28:03 |
Mean and Standard Deviation of Poisson Random Variables |
2:01 |
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Poisson Graphs in Excel |
17:52 |
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Law of Large Numbers |
9:00 |
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The Law of Large Numbers |
1:30 |
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Normal Distribution Excel Exercise |
26:04 |
Is My Data Normal? |
25:31 |
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Introduction to the Normal Distribution |
26:24 |
A Tour of the Normal Distribution |
26:58 |
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Introduction to Normal Distributions |
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Normal Distribution Problems: Qualitative Sense of Normal Distributions |
10:53 |
Sampling Distributions |
18:48 |
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Normal Distribution Problems: Z-score |
7:48 |
Understanding Z-scores |
22:57 |
Z-scores (Part One) |
3:03 |
An Introduction to Z-scores |
3:53 |
History of the Normal Distribution |
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Z-scores (Part Two) |
4:01 |
How to Calculate Z-scores |
3:51 |
Areas Under Normal Distributions |
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How to Calculate Normalized Z-score |
7:15 |
Varieties Demonstration |
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How to Look Up Normalized Tables Z-scores Standard Normal Curve Table |
7:34 |
Standard Normal Distribution |
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How to use Normalized Tables Z-score (Standard Table) |
5:03 |
Normal Approximation Demonstration |
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Normal Distribution Problems: Empirical Rule |
10:25 |
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The Normal Curve and Empirical Rule |
3:18 |
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Exercise: Standard Normal Distribution and the Empirical |
8:16 |
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More Empirical Rule and Z-score Practice |
5:57 |
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Exra Z-score Problems |
4:54 |
An
Example of how to Z-score and Hypothesis Testing |
3:59 |
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Central Limit Theorem |
9:49 |
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The Central Limit Theorem |
1:17 |
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Central Limit Theorem Demonstration |
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Sampling Distribution of the Sample Mean |
10:52 |
Sample Mean Proximity to Population Mean |
38:59 |
Distribution of the Sampling Mean |
4:49 |
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Introduction to Sampling Distributions |
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Sampling Distribution of the Sample Mean 2 |
13:20 |
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Sampling Distribution Demonstration |
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Sampling Distribution Example Problem |
14:28 |
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Sampling Size Demonstration |
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Sampling Distribution of the Mean |
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Standard Error of the Mean |
15:15 |
Standard Error of the Mean |
32:03 |
Parameters, Statistics, and Sampling Error |
2:20 |
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Confidence Interval 1 |
14:03 |
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How to use Excel to Calculate Confidence Interval |
4:59 |
Confidence Intervals Introduction |
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Mean and Variance of Bernoulli Distribution Example |
8:20 |
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Bernoulli Distribution Mean and Variance Formulas |
6:59 |
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Margin of Error 1 |
15:03 |
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How to Calculate Confidence Intervals and Margin of Error |
6:44 |
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Margin of Error 2 |
10:05 |
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How to Calculate Sample Size and Margin of Error |
6:46 |
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How to Calculate Margin of Error and Standard Deviation |
6:42 |
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How to Calculate Margin of Error Confidence Interval for a Population
Proportion |
8:04 |
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Confidence Interval Example |
18:36 |
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Confidence Interval Demonstration |
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Small Sample Size and Confidence Intervals |
11:11 |
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Hypothesis Testing and p-values |
11:27 |
Introduction to Hypothesis Formulation |
21:09 |
Null and Alternative Hypotheses |
2:42 |
P-values, Z-scores, Alpha, Critical Values |
5:37 |
Significance Testing |
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Null and Alternative Hypotheses-Part 1 |
22:17 |
User Submitted Question: Alpha Levels |
2:26 |
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Introduction to Hypothesis Testing |
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Null and Alternative Hypotheses-Part 2 |
18:10 |
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Interpreting Significant Results |
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Interpreting Non-Significant Results |
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Steps in Hypothesis Testing |
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Significance Testing and Confidence Intervals |
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Misconceptions in Hypothesis Testing |
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Sampling Distribution of p |
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One-tailed and Two-tailed Tests |
6:34 |
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One-Tailed and Two-Tailed Tests |
2:06 |
How to Calculate One Tail and Two Tail Tests for Hypothesis Testing |
4:34 |
One- and Two-Tailed Tests |
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Z-statistics vs. T-statistics |
6:40 |
To Z or to T, That is the Question |
38:17 |
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Type I Errors |
3:24 |
Type I and Type II Errors-Part 1 |
24:55 |
Type I and Type II Errors |
4:25 |
Learn to Understand Hypothesis Testing for Type I and Type II Errors |
7:01 |
Type I and Type II Errors |
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Type I and Type II Errors-Part 2 |
24:04 |
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Robustness Simulation |
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Visualizing Type I and Type II Error |
37:43 |
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Calculating Type II Error-Part 1 |
23:39 |
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Calculating Type II Error-Part 2 |
20:57 |
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Controlling Type II Error Using Sample Size |
38:10 |
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Small Sample Hypothesis Test |
9:04 |
Single Sample Hypothesis Z-test-Part 1 |
19:09 |
One Sample Z-test |
6:17 |
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Testing a Single Mean |
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Single Sample Hypothesis Z-test-Part 2 |
15:17 |
One Sample Z-test for Proportions |
6:08 |
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Confidence Interval on the Mean |
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Single Sample Hypothesis Z-test-Part 3 |
16:11 |
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Single Sample Hypothesis T-test-Part 1 |
25:41 |
One Sample T-test |
4:49 |
How to Calculate T Distributions |
5:47 |
t Distribution |
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Single Sample Hypothesis T-test-Part 2 |
28:08 |
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How to Calculate T Statistics Test Between the Means of Related Groups
(Dependent Means) |
11:10 |
t Distribution Demonstration |
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How to Calculate T Statistics of Different Groups |
10:22 |
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T-statistic Confidence Interval |
11:47 |
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Confidence Intervals for Independent Samples T-test |
2:54 |
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Confidence Intervals for Dependent Samples T-test |
2:33 |
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Large Sample Proportion Hypothesis Testing |
14:31 |
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Variance of Differences of Random Variables |
10:47 |
Two Populations, Z-test with Hypothesis |
26:37 |
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Difference Between Two Means (Independent Groups) |
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Two Populations, T-test with Hypothesis |
33:58 |
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Two Populations, Matched Sample T-test |
34:28 |
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F-ratio Test for Two Equal Variances |
18:03 |
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F-ratio test Practice for Two Equal Variances |
12:54 |
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Difference of Sample Means Distribution |
12:18 |
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Difference Between Means |
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Difference Between Two Means |
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Sampling Distribution of Difference Between Means |
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Confidence Interval of Difference of Means |
15:49 |
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Confidence Intervals about the Mean, Population Standard Deviation
Unknown |
5:15 |
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Clarification of Confidence Interval of Difference of Means |
2:42 |
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Hypothesis Test for Difference of Means |
10:07 |
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Comparing Population Proportions 1 |
10:47 |
Confindence Intervals, Population Deviation Known |
44:07 |
Sample Proportions |
3:09 |
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Proportion |
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Comparing Population Proportions 2 |
10:01 |
Confidence Intervals, Population Deviation Unknown-Part 1 |
27:15 |
Z-test for Proportions, Two Samples |
4:05 |
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Proportions |
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Hypothesis Test Comparing Population Proportions |
16:13 |
Confidence Intervals, Population Deviation Unknown-Part 2 |
20:57 |
Confidence Intervals for Population Proportions |
4:18 |
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Proportion of Variance Explained |
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Confidence Intervals for the Difference of Two Proportions |
1:58 |
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Squared Error of Regression Line |
6:47 |
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Introduction to Linear Regression |
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Proof (Part 1) Minimizing Squared Error to Regression Line |
10:35 |
Simple Linear Regression (Part 1), The Very Basics |
22:56 |
Linear Regression |
4:31 |
An
Introduction to Linear Regression Analysis |
2:14 |
Linear Fit Demonstration |
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Proof (Part 2) Minimizing Squared Error to Regression Line |
9:54 |
Simple Linear Regression (Part 2), Algebra, Equations, and Patterns |
24:57 |
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An
Introduction to Regression Analysis |
4:41 |
Partitioning the Sums of Squares |
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Proof (Part 3) Minimizing Squared Error to Regression Line |
10:54 |
Simple Linear Regression (Part 3), The Least Squares Method |
28:37 |
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How to Calculate Regression Equation Using Excel Statistics |
6:18 |
Standard Error of the Estimate |
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Proof (Part 4) Minimizing Squared Error to Regression Line |
4:18 |
Simple Linear Regression (Part 4), Fit and the Coefficient of
Determination |
26:10 |
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How to Calculate Regression Equation, R-square, Using Excel Statistics |
6:52 |
Inferential Statistics for b and r |
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Regression Line Example |
9:27 |
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How to Calculate Linear Regression Using Least Squares Method |
8:29 |
Influential Observations |
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R-squared or Coefficient of Determination |
12:41 |
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Standard Error of the Estimate Used in Regression Analysis (Mean Square
Error) |
3:41 |
Regression Toward the Mean |
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Second Regression Example |
9:15 |
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Calculating R-squared |
9:45 |
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How to Calculate R Squared Using Regression Analysis |
7:41 |
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Covariance and the Regression Line |
15:08 |
Understanding Covariance |
26:23 |
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The Covariance Matrix |
17:32 |
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Chi-square Distribution Introduction |
10:23 |
Introduction to Chi-square Test |
37:39 |
Chi-square Test for Goodness of Fit |
4:01 |
How to Calculate Chi-square Goodness of Fit (One Way) |
9:33 |
Chi Square Distribution |
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Pearson's Chi-square Test (Goodness of Fit) |
11:48 |
Quick Chi-square in SPSS |
18:26 |
Chi-square Test for Independence |
3:54 |
How to Calculate Chi-square Test for Independence (Two-Way) |
12:59 |
One-Way Tables (Testing Goodness of Fit) |
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Contingency Table Chi-square Test |
17:38 |
Chi-square in Excel using College Enrollment Data |
41:35 |
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Testing Distribution Demonstration |
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Contingency Tables |
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2x2 Simulation |
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ANOVA 1: Calculating SST (Total Sum of Squares) |
7:39 |
ANOVA, a Visual Introduction |
24:18 |
Introduction to ANOVA |
7:16 |
How to Calculate and Understand ANOVA F-test |
14:30 |
Introduction to ANOVA |
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ANOVA 2: Calculating SSW and SSB (Total Sum of Squares Within and
Between) |
13:20 |
One-way ANOVA (Part 1), A Visual Guide |
24:14 |
One-Way ANOVA |
6:51 |
How to Read F Distribution Table Used in ANOVA |
5:52 |
Analysis of Variance Designs |
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ANOVA 3: Hypothesis Test with F-statistic |
10:14 |
One-way ANOVA (Part 2), Understanding the Calculation |
35:22 |
Effect Size for One-Way ANOVA |
2:03 |
How to Calculate ANOVA (Plugging Numbers Into Equation) |
9:57 |
One-Factor ANOVA (Between Subjects) |
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Two-Way ANOVA without Replication (Part 1), A Visual Guide |
37:36 |
Post-Hoc Tests for One-Way ANOVA |
6:10 |
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One-way ANOVA Demonstration |
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Two-Way ANOVA without Replication (Part 2), The Calculation |
43:02 |
Repeated-Measures ANOVA |
9:03 |
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Multi-Factor Between-Subjects Designs |
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Two-way ANOVA with Replication (Part 1), An Introduction |
34:15 |
Factorial ANOVA, Two Independent Factors |
9:10 |
How to Calculate a Two Way ANOVA (Factorial Analysis) |
18:02 |
Unequal Sample Sizes |
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Two-way ANOVA with Replication (Part 2A), Interactions |
18:28 |
Factorial ANOVA, Two Dependent Factors |
13:38 |
How to Interpret the Results of a Two Way ANOVA |
17:41 |
Tests Supplementing ANOVA |
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Two-way ANOVA with Replication (Part 2B), Marginal Means Graphs |
28:53 |
Factorial ANOVA, Two Mixed Factors |
11:08 |
Introduction to Two Way ANOVA |
8:01 |
Within-Subjects ANOVA |
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Power of Within-Subjects Designs Demonstration |
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Correlation and Causality |
10:45 |
Understanding Correlation |
27:06 |
Correlation vs. Causation |
2:19 |
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Correlation |
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Pearson's r Correlation |
4:03 |
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Causation |
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Hypothesis Testing with Pearson's r |
2:58 |
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Introduction to Bivariate Data |
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Spearman Correlation |
3:13 |
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Values of the Pearson Correlation |
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Guessing Correlations |
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Properties of Pearson's r |
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Computing Pearson's r |
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Range Restriction Demonstration |
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Variance Sum Law II |
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Sampling Distribution of Pearson's r |
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All Pairwise Comparisons Among Means |
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Specific Comparisons (Independent Groups) |
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Difference Between Two Means (Correlated Pairs) |
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Correlated t Demonstration |
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Specific Comparisons (Correlated Observations) |
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Pairwise Comparisons (Correlated Observations) |
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Multiple Regression (Part 1), The Very Basics |
20:26 |
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Introduction to Multiple Regression |
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Multiple Regression (Part 2), Preparation |
24:05 |
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Multiple Regression (Part 3A), Evaluating Basic Models |
25:17 |
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Multiple Regression (Part 3B), Evaluating Basic Models |
26:22 |
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Multiple Regression (Part 4), Dummy Variables |
20:59 |
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Multiple Regression (Part 5A), Two Categorical Variables |
18:34 |
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Multiple Regression (Part 5B), Two Categorical Variables |
18:03 |
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Logistic Regression, An Introduction |
11:26 |
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Logistic Regression Probability, Odds and Odds ratio |
13:03 |
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Logistic Regression, Logit and Regression Equation |
16:58 |
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Logistic Regression, Estimating the Probability |
11:22 |
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Logistic Regression, Odds Ratio for Any Interval |
24:47 |
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Logistic Regression in Excel/Google Sheets, PC/Mac |
10:10 |
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Permutations vs. Combinations |
21:00 |
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Hypergeometric Distribution |
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Combinations |
20:54 |
Combinations |
2:50 |
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Permutations |
19:04 |
Permutations |
3:04 |
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Combinations-Losing Your Marbles |
28:43 |
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Combinations-Dogs of the Dow |
28:50 |
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Combinations-Nearly Normal |
23:45 |
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Combinations-Under the Curve |
29:22 |
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Joint and Marginal Probabilities |
21:20 |
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Basic Concepts in Probability |
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Combinations-Playing with a Full Deck |
29:35 |
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Estimating Sample Size Requirements |
37:42 |
Calculating Required Sample Size to Estimate Population Mean |
2:19 |
How to Calculate Sample Size Proportions |
2:44 |
Introduction to Power |
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Calculating Required Sample Size to Estimate Population Proportions |
2:45 |
How to Calculate Sample Size |
2:46 |
Example Calculations (Power) |
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Power |
6:23 |
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Power Demonstration 1 |
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Power Demonstration 2 |
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Factors Affecting Power |
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Effect Size |
2:26 |
How to Calculate Cohen d Effect Size |
4:50 |
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Effect Size for Dependent Samples t-Test |
2:26 |
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Effect Size for Independent Samples t-Test |
2:25 |
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Confidence Intervals for the Variance |
40:41 |
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Hypothesis Test for the Variance |
26:53 |
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How to Calculate Weighted Mean and Weighted Average |
2:17 |
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The Basics: Descriptive and Inferential Statistics |
2:51 |
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Descriptive Statistics |
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Inferential Statistics |
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Sampling Methods |
3:56 |
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Sampling Simulation |
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Variable Measurement Scales |
2:43 |
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Measurement |
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Basics of Data Collection |
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Levels of Measurement |
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Measurement Demonstration |
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Bar Graphs and Pie Charts |
2:13 |
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Bar Charts |
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Graphing Qualitative Variables |
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Histograms and Stem & Leaf Plots |
5:35 |
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Stem and Leaf Displays |
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Probability Histograms |
1:24 |
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Histograms |
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Percentiles and Quartiles |
3:37 |
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Percentiles |
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The Five Number Summary, Interquartile Range (IQR), and Boxplots |
3:31 |
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Box Plots |
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Coordinate (Cartesian) Planes |
1:19 |
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Box Plot Demo |
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Quadrants |
1:04 |
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Quantitative Variables |
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Scatter Plots |
1:21 |
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Frequency Polygons |
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Line Graphs |
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Dot Plots |
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Quantile-Quantile (q-q) Plots |
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Contour Plots |
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3D Plots |
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The Effects of Outliers |
3:08 |
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Log Transformations |
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Skewness |
1:36 |
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Tukey's Ladder of Powers |
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Box-Cox Transformations |
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Statistical vs. Practical Significance |
2:02 |
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What are Statistics? |
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Importance of Statistics |
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Independent and Dependent Samples |
2:17 |
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Benefits of Distribution-Free Tests |
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Randomization Tests: Two Conditions |
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Randomization Tests: Two or More Conditions |
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Randomization Tests: Association (Pearson's r) |
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Randomization Tests: Contingency Tables (Fisher's Exact Test) |
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Mann-Whitney U-Test |
4:36 |
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Rank Sum Randomization: Two Conditions (Mann-Whitney U, Wilcoxon Rank
Sum) |
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Wilcoxon Signed-Ranks Test |
3:48 |
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The Kruskal-Wallis Test |
5:20 |
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Rank Randomization: Two or More Conditions (Kruskal-Wallis) |
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The Friedman Test |
3:27 |
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Rank Randomization for Association (Spearman's p) |
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Student's T-distribution |
2:56 |
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Independent Samples T-test |
6:53 |
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Dependent Samples T-test |
4:59 |
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Confidence Intervals about the Mean, Population Standard Deviation Known |
4:30 |
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Summation |
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Linear Transformations |
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Logarithms |
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Scientific Method |
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Experimental Designs |
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Sampling Bias |
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Statistical Literacy (Introduction) |
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Exercises (Introduction) |
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Statistical Literacy (Research Design) |
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Exercises (Research Design) |
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Statistical Literacy (Normal Distribution) |
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Exercises (Normal Distribution) |
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Statistical Literacy (Hypothesis Testing) |
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Exercises (Hypothesis Testing) |
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Statistical Literacy (Tests of Means) |
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Exercises (Tests of Means) |
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Statistical Literacy (Power) |
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Exercises (Power) |
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Statistical Literacy (Regression) |
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Exercises (Regression) |
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Statistical Literacy (Transformations) |
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Exercises (Transformations) |
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Statistical Literacy (ANOVA) |
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Exercises (ANOVA) |
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Statistical Literacy (Chi Square) |
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Exercises (Chi Square) |
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Statistical Literacy (Effect Size) |
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Exercises (Effect Size) |
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Statistical Literacy (Distribution Free Tests) |
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Exercises (Distribution Free Tests) |
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Statistical Literacy (Sampling Distributions) |
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Exercises (Sampling Distributions) |
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Statistical Literacy (Estimation) |
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Exercises (Estimation) |
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Statistical LIteracy (Summarizing Distributions) |
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Exercises (Summarizing Distributions) |
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Statistical Literacy (Describing Bivariate Data) |
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Exercises (Describing Bivariate Data) |
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Statistical Literacy (Graphing Distributions) |
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Exercises (Graphing Distributions) |
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Statistical Literacy (Advanced Graphs) |
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Exercises (Advanced Graphs) |
