(eBook PDF) Introductory Statistics: Exploring the World Through Data 3rd Edition – Digital Ebook – Instant Delivery Download
Product details:
- ISBN-13: 9780136880882
- AUthor: Robert Gould (Author), Rebecca Wong (Author), Colleen Ryan (Author)
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 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
People also search:
introductory statistics answers pdf free download
what is introductory statistics
a survey of an introductory statistics class in autumn
a pathway to introductory statistics
a distribution of grades in an introductory statistics class