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Introductory Statistics Exploring the World Through Data, 3rd edition By Robert N. Gould, Colleen Ryan (Test Bank )

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Brief Contents Introduction to Data 1.1 What Are Data? 1.2 Classifying and Storing Data 1.3 Investigating Data 1.4 Organizing Categorical Data 1.5 Collecting Data to Understand Causality Picturing Variation with Graphs 2.1 Visualizing Variation in Numerical Data 2.2 Summarizing Important Features of a Numerical Distribution 2.3 Visualizing Variation in Categorical Variables 2.4 Summarizing Categorical Distributions 2.5 Interpreting Graphs Numerical Summaries of Center and Variation 3.1 Summaries for Symmetric Distributions 3.2 What's Unusual? The Empirical Rule and z-Scores 3.3 Summaries for Skewed Distributions 3.4 Comparing Measures of Center 3.5 Using Boxplots for Displaying Summaries Regression Analysis: Exploring Associations between Variables 4.1 Visualizing Variability with a Scatterplot 4.2 Measuring Strength of Association with Correlation 4.3 Modeling Linear Trends 4.4 Evaluating the Linear Model Modeling Variation with Probability 5.1 What Is Randomness? 5.2 Finding Theoretical Probabilities 5.3 Associations in Categorical Variables 5.4 Finding Empirical Probabilities Modeling Rando Events: The Normal and Binomial Models 6.1 Probability Distributions Are Models of Random Experiments 6.2 The Normal Model 6.3 The Binomial Model (Optional) Survey Sampling and Inference 7.1 Learning about the World through Surveys 7.2 Measuring the Quality of a Survey 7.3 The Central Limit Theorem for Sample Proportions 7.4 Estimating the Population Proportion with Confidence Intervals 7.5 Comparing Two Population Proportions with Confidence Hypothesis Testing for Population Proportions 8.1 The Essential Ingredients of Hypothesis Testing 8.2 Hypothesis Testing in Four Steps 8.3 Hypothesis Tests in Detail 8.4 Comparing Proportions from Two Populations Inferring Population Means 9.1 Sample Means of Rando Samples 9.2 The Central Limit Theorem for Sample Means 9.3 Answering Questions about the Mean of a Population 9.4 Hypothesis Testing for Means 9.5 Comparing Two Population Means 9.6 Overview of Analyzing Means Associations between Categorical Variables 10.1 The Basic Ingredients for Testing with Categorical Variables 10.2 The Chi-Square Test for Goodness of Fit 10.3 Chi-Square Tests for Associations between Categorical Variables 10.4 Hypothesis Tests When Sample Sizes Are Small Multiple Comparisons and Analysis of Variance 11.1 Multiple Comparisons 11.2 The Analysis of Variance 11.3 The ANOVA Test 11.4 Post-Hoc Procedures Experimental Design: Controlling Variation 12.1 Variation Out of Control 12.2 Controlling Variation in Surveys 12.3 Reading Research Papers Inference without Normality 13.1 Transforming Data 13.2 The Sign Test for Paired Data 13.3 Mann-Whitney Test for Two Independent Groups 13.4 Randomization Tests Inference for Regression 14.1 The Linear Regression Model 14.2 Using the Linear Model 14.3 Predicting Values and Estimating Means

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