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Contents: Preface. Why Statistics? Part I: Descriptive Statistics. Frequency Distributions and Percentiles. Central Tendency and Variability. z Scores and Normal Distributions. Part II: Introduction to Inferential Statistics. Overview of Inferential Statistics. Probability. Sampling Distributions. Logic of Hypothesis Testing. Power. Logic of Parameter Estimation. Part III: Applications of Inferential Statistics. Inferences About Population Proportions Using the z Statistic. Inferences About µ When o Is Unknown: The Single Sample t Test. Comparing Two Populations: Independent Samples. Random Sampling, Random Assignment, and Causality. Comparing Two Populations: Dependent Samples. Comparing Two Population Variances: The F Statistic. Comparing Multiple Population Means: One-Factor ANOVA. Introduction to Factorial Designs. Computational Methods for the Factorial ANOVA. Describing Linear Relationships: Regression. Measuring the Strength of Linear Relationships: Correlation. Inferences From Nominal Data: The X² Statistic.
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