Introductory Statistics Exploring the World Through Data 1st Edition Gould Test Bank

Introductory Statistics Exploring the World Through Data 1st Edition Gould Test Bank

Product details:

• ISBN-10 ‏ : ‎ 013518892X
• ISBN-13 ‏ : ‎ 978-0135188927
• Author: Robert L. Gould

Embracing these characteristics, Introductory Statistics teaches students how to explore and analyze real data to answer real-world problems. Crafted by authors who are active in the classroom and in the statistics education community, the 3rd Edition pairs a clear, conversational writing style with new and frequent opportunities to apply statistical thinking. Its tone and learning aids are designed to equip any student to analyze, interpret, and tell a story about modern data, regardless of the student’s mathematical proficiency.

Table contents:

1: Introduction to Data

1.1 What Are Data?1.2 Classifying and Storing Data1.3 Investigating Data1.4 Organizing Categorical Data1.5 Collecting Data to Understand Causality

2: Picturing Variation with Graphs

2.1 Visualizing Variation in Numerical Data2.2 Summarizing Important Features of a Numerical Distribution2.3 Visualizing Variation in Categorical Variables2.4 Summarizing Categorical Distributions2.5 Interpreting Graphs

3: Numerical Summaries of Center and Variation

3.1 Summaries for Symmetric Distributions3.2 What’s Unusual? The Empirical Rule and z-Scores3.3 Summaries for Skewed Distributions3.4 Comparing Measures of Center3.5 Using Boxplots for Displaying Summaries

4: Regression Analysis: Exploring Associations between Variables

4.1 Visualizing Variability with a Scatterplot4.2 Measuring Strength of Association with Correlation4.3 Modeling Linear Trends4.4 Evaluating the Linear Model

5: Modeling Variation with Probability

5.1 What Is Randomness?5.2 Finding Theoretical Probabilities5.3 Associations in Categorical Variables5.4 Finding Empirical Probabilities

6: Modeling Rando Events: The Normal and Binomial Models

6.1 Probability Distributions Are Models of Random Experiments6.2 The Normal Model6.3 The Binomial Model (Optional)

7: Survey Sampling and Inference

7.1 Learning about the World through Surveys7.2 Measuring the Quality of a Survey7.3 The Central Limit Theorem for Sample Proportions7.4 Estimating the Population Proportion with Confidence Intervals7.5 Comparing Two Population Proportions with Confidence

8: Hypothesis Testing for Population Proportions

8.1 The Essential Ingredients of Hypothesis Testing8.2 Hypothesis Testing in Four Steps8.3 Hypothesis Tests in Detail8.4 Comparing Proportions from Two Populations

9: Inferring Population Means

9.1 Sample Means of Rando Samples9.2 The Central Limit Theorem for Sample Means9.3 Answering Questions about the Mean of a Population9.4 Hypothesis Testing for Means9.5 Comparing Two Population Means9.6 Overview of Analyzing Means

10: Associations between Categorical Variables

10.1 The Basic Ingredients for Testing with Categorical Variables10.2 The Chi-Square Test for Goodness of Fit10.3 Chi-Square Tests for Associations between Categorical Variables10.4 Hypothesis Tests When Sample Sizes Are Small

11: Multiple Comparisons and Analysis of Variance

11.1 Multiple Comparisons11.2 The Analysis of Variance11.3 The ANOVA Test11.4 Post-Hoc Procedures

12: Experimental Design: Controlling Variation

12.1 Variation Out of Control12.2 Controlling Variation in Surveys12.3 Reading Research Papers

13: Inference without Normality

13.1 Transforming Data13.2 The Sign Test for Paired Data13.3 Mann-Whitney Test for Two Independent Groups13.4 Randomization Tests

14: Inference for Regression

14.1 The Linear Regression Model14.2 Using the Linear Model14.3 Predicting Values and Estimating Means

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