Solutions manual for Introductory Statistics by Robert Gould 0321891937

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Product details:

• ISBN-10 ‏ : ‎ 0321891937
• ISBN-13 ‏ : ‎ 978-0321891938
• Author: Robert L. Gould; Colleen N. Ryan

Table of contents:

1. 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

2. 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

3. 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<

4. 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

5. 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

6. 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)

7. 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

8. 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

9. 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

10. 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

11. 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

12. Experimental Design: Controlling Variation

• 12.1 Variation Out of Control
• 12.2 Controlling Variation in Surveys
• 12.3 Reading Research Papers

13. 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

14. 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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