**Introduction to Statistics**

**A quick introduction to statistics**

**Variables**

**Descriptive Statistics**

**Measuring “The Center” – Mean, Median, and Mode**

**Measuring “The Spread” – Range, Interquartile Range, Standard Deviation, and Variance**

**Measuring “Position” – Percentiles, Quartiles, and Z-Scores**

**Visualizing Data**

**Bar Charts & Histograms**

**Boxplots**

**Stem and leaf plots**

**Scatterplots**

Frequency Tables

Ogive (Cumulative Frequency Polygon)

**Classifying the Shapes of Distributions**

**Comparing Distributions**

Frequency Tables

Ogive (Cumulative Frequency Polygon)

**Study Design**

**Four Methods of Collecting Data**

**Sampling Methods**

The Characteristics of an Experiment

Experimental Design

The Characteristics of an Experiment

Experimental Design

**Probability**

**Intro to Probability**

Probability Using Sample Spaces

Set Operations – Unions, Intersections, Complements, and More

Theoretical vs. Experimental Probability

The Addition Rule for Probability

The Multiplication Rule for Probability

Conditional Probability and Independence

Probability Using Sample Spaces

Set Operations – Unions, Intersections, Complements, and More

Theoretical vs. Experimental Probability

The Addition Rule for Probability

The Multiplication Rule for Probability

Conditional Probability and Independence

**Counting, Combinations, and Permutations**

**Counting Outcomes Using Tree Diagrams**

Permutations

Combinations

Practice Problems with Permutations & Combinations

Probability with Permutations & Combinations

Permutations

Combinations

Practice Problems with Permutations & Combinations

Probability with Permutations & Combinations

**Random Variables**

**Discrete Random Variables**

Continuous Random Variables

The Normal Distribution

Empirical Rule (Practice Problems)

**Converting Between Z-Scores and Percentiles Using the Normal Distribution**

Transforming Random Variables

Combining Random Variables

Combining Normal Random Variables

The Binomial Distribution

The Uniform Distribution

The Geometric Distribution

The Negative Binomial Distribution

The Poisson Distribution

The Hypergeometric Distribution

The Multinomial Distribution

Continuous Random Variables

The Normal Distribution

Empirical Rule (Practice Problems)

Transforming Random Variables

Combining Random Variables

Combining Normal Random Variables

The Binomial Distribution

The Uniform Distribution

The Geometric Distribution

The Negative Binomial Distribution

The Poisson Distribution

The Hypergeometric Distribution

The Multinomial Distribution

**Sampling Distributions**

**What is a Sampling Distribution?**

Understanding the Central Limit Theorem

Finding the Difference Between Means

**Finding the Difference Between Proportions**

Understanding the Central Limit Theorem

Finding the Difference Between Means

**Confidence Intervals**

**Introduction to Confidence Intervals**

Confidence Interval for a Mean

Confidence Interval for a Difference in Means

Confidence Interval for a Proportion

Confidence Interval for a Difference in Proportions

A Simple Explanation of Bootstrapping in Statistics with an Example

Confidence Interval for a Mean

Confidence Interval for a Difference in Means

Confidence Interval for a Proportion

Confidence Interval for a Difference in Proportions

A Simple Explanation of Bootstrapping in Statistics with an Example

**Hypothesis Testing**

**Introduction to Hypothesis Testing**

Hypothesis Testing for a Mean

Hypothesis Testing for a Difference in Means

Hypothesis Testing for a Difference in Paired Means

Hypothesis Testing for a Proportion

Hypothesis Testing for a Difference in Proportions

Mann-Whitney U Test

**How to Interpret a P-Value of 0.000 **

An Explanation of P-Values and Statistical Significance

Hypothesis Testing for a Mean

Hypothesis Testing for a Difference in Means

Hypothesis Testing for a Difference in Paired Means

Hypothesis Testing for a Proportion

Hypothesis Testing for a Difference in Proportions

Mann-Whitney U Test

An Explanation of P-Values and Statistical Significance

**Chi-Square Tests**

**Chi-Square Test for Goodness of Fit**

Chi-Square Test for Homogeneity

Chi-Square Test for Independence

Chi-Square Test for Homogeneity

Chi-Square Test for Independence

**Linear Regression**

**Pearson Correlation Coefficient**

**Introduction to Simple Linear Regression**

**Testing the Significance of a Regression Slope**

How to Read and Interpret a Regression Table

A Simple Guide to Understanding the F-Test of Overall Significance in Regression

Understanding the Standard Error of the Regression

**What is a Good R-squared Value?**

Understanding Heteroscedasticity in Regression

A Guide to Multicollinearity in Regression

How to Read and Interpret a Regression Table

A Simple Guide to Understanding the F-Test of Overall Significance in Regression

Understanding the Standard Error of the Regression

Understanding Heteroscedasticity in Regression

A Guide to Multicollinearity in Regression

**ANOVA**

**One-Way ANOVA**

Kruskal-Wallis Test

One-Way Repeated Measures ANOVA

Two-Way ANOVA

A Guide to Using Post Hoc Tests with ANOVA

Understanding the Differences Between ANOVA, ANCOVA, MANOVA, and MANCOVA

Kruskal-Wallis Test

One-Way Repeated Measures ANOVA

Two-Way ANOVA

A Guide to Using Post Hoc Tests with ANOVA

Understanding the Differences Between ANOVA, ANCOVA, MANOVA, and MANCOVA