Course Contents at a Glance

The following list shows a summary of the topics covered in this e-book.

Module 1: Sampling and Data

• Definitions of Statistics, Probability, and Key Terms
• Sampling and Data
• Frequency, Frequency Tables, and Levels of Measurement
• Experimental Design and Ethics

Module 2: Descriptive Statistics

• Stem-and-Leaf Graphs (Stemplots)
• Measures of the Location of the Data
• Histograms, Frequency Polygons, and Time Series Graphs
• Box Plots
• Measures of the Center of the Data
• Skewness and the Mean, Median, and Mode
• Measures of the Spread of Data
• When to use each measure of Central Tendency

Module 3: Probability

• The Terminology of Probability
• Independent and Mutually Exclusive Events
• Two Basic Rules of Probability
• Contingency Tables
• Tree and Venn Diagrams

Module 4: Discrete Random Variables

• Probability Distribution Function (PDF) for a Discrete Random Variable
• Mean or Expected Value and Standard Deviation
• Binomial Distribution
• Geometric Distribution
• Poisson Distribution

Module 5: Continuous Random Variables

• Continuous Probability Functions
• The Uniform Distribution
• The Exponential Distribution

Module 6: Normal Distribution

• The Standard Normal Distribution
• Using the Normal Distribution

Module 7: The Central Limit Theorem

• The Central Limit Theorem for Sample Means (Averages)
• The Central Limit Theorem for Sums
• Using the Central Limit Theorem

Module 8: Confidence Intervals

• A Single Population Mean using the Normal Distribution
• A Single Population Mean using the Student Distribution
• A Population Proportion

Module 9: Hypothesis Testing With One Sample

• Null and Alternative Hypotheses
• Outcomes and the Type I and Type II Errors
• Distributions Needed for Hypothesis Testing
• Rare Events, the Sample, Decision and Conclusion
• Additional Informational and Full Hypothesis Test Examples

Module 10: Hypothesis Testing With Two Samples

• Two Population Means with Unknown Standard Deviations
• Two Population Means with Known Standard Deviations
• Comparing Two Independent Population Proportions
• Matched or Paired Samples

Module 11: The Chi Square Distribution

• Facts About the Chi-Square Distribution
• Goodness-of-Fit Test
• Test of Independence
• Test for Homogeneity
• Comparison of the Chi-Square Tests
• Test of a Single Variance

Module 12: Linear Regression and Correlation

• Linear Equations
• Scatter Plots
• The Regression Equation
• Testing the Significance of the Correlation Coefficient
• Prediction
• Outliers

Module 13: F-Distribution and the One-Way ANOVA

• One-Way ANOVA
• The F Distribution and the F-Ratio
• Facts about the F Distribution
• Test of Two Variances
• Relationships in an ANOVA Table

Module 14: Multiple and Logistic Regression

• Model Selection
• Checking Model Assumptions Using Graphs
• Line Fitting, Residuals, and Correlation
• Fitting a Line by Least Linear Regression
• Types of Outliers in Linear Regression
• Inference for Linear Regression