The textbook content and assessments for Introduction to Statistics are aligned to the following learning outcomes. A full list of course learning outcomes can be viewed here: Introduction to Statistics Corequisite Learning Outcomes.

Module 1: Sampling and Data

• Review topics needed for success in Algebra Essentials.
• Definitions of Statistics, Probability, and Key Terms.
• Data, Sampling, and Variation in Data and Sampling.
• Frequency, Frequency Tables, and Levels of Measurement.
• Experimental Design and Ethics.

Module 2: Descriptive Statistics

• Review topics needed for success in Descriptive Statistics.
• Stem-and-Leaf Graphs (Stemplots), Line Graphs, and Bar Graphs.
• Histograms, Frequency Polygons, and Time Series Graphs.
• Measures of the Location of the Data.
• Box Plots.
• Measures of the Center of the Data.
• Skewness and the Mean, Median, and Mode.
• Measures of the Spread of the Data.

Module 3: Probability Topics

• Review topics needed for success in Probability Topics.
• Terminology.
• Independent and Mutually Exclusive Events.
• Two Basic Rules of Probability.
• Contingency Tables.
• Tree and Venn Diagrams.

Module 4: Discrete Random Variables

• Review topics needed for success in Discrete Random Variables.
• Probability Distribution Function (PDF) for a Discrete Random Variable.
• Mean or Expected Value and Standard Deviation.
• Binomial Distribution.
• Geometric Distribution.
• Hypergeometric Distribution.
• Poisson Distribution.

Module 5: Continuous Random Variables

• Review topics needed for success in Continuous Random Variables.
• Continuous Probability Functions.
• The Uniform Distribution.
• The Exponential Distribution.

Module 6: The Normal Distribution

• Review topics needed for success in The Normal Distribution.
• The Standard Normal Distribution.
• Using the Normal Distribution.

Module 7: The Central Limit Theorem

• Review topics needed for success in 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

• Review topics needed for success in Confidence Intervals.
• A Single Population Mean using the Normal Distribution.
• A Single Population Mean using the Student t Distribution.
• A Population Proportion.

Module 9: Hypothesis Testing With One Sample

• Review topics needed for success in Hypothesis Testing with One Sample.
• Null and Alternative Hypotheses.
• Outcomes and the Type I and Type II Errors.
• Distribution Needed for Hypothesis Testing.
• Rare Events, the Sample, Decision and Conclusion.
• Additional Information and Full Hypothesis Test Examples.

Module 10: Hypothesis Testing With Two Samples

• Review topics needed for success in 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

• Review topics needed for success in 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

• Review topics needed for success in 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

• Review topics needed for success in F Distribution and One-Way ANOVA.
• One-Way ANOVA.
• The F Distribution and the F-Ratio.
• Facts About the F Distribution.
• Test of Two Variances.