Elementary Statistics: Picturing the World, 7th edition

Published by Pearson (August 17, 2021) © 2019

  • Ron Larson Penn State University at Erie
  • Betsy Farber Bucks County Community College

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ISBN-13: 9780137504329 (2021 update)
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Elementary Statistics: Picturing the World describes our world through statistics. It makes statistics understandable with stepped-out instruction, extensive real-life examples and exercises, and a design that fits content to each page to make the material more digestible. The authors' combination of theory, learning aids and design helps you understand concepts and use statistics to describe and think about the world. Real-life examples, exercises and projects help you picture the world using statistics. The 7th Edition incorporates a thorough update of key features, examples and exercises; new Tech Tips now appear in most sections and show how to use Minitab, Excel, the TI-84 Plus and StatCrunch to solve a problem; and much more.

I. DESCRIPTIVE STATISTICS

  1. Introduction to Statistics
    • 1.1 An Overview of Statistics
    • 1.2 Data Classification
    • 1.3 Data Collection and Experimental Design
  2. Descriptive Statistics
    • 2.1 Frequency Distributions and Their Graphs
    • 2.2 More Graphs and Displays
    • 2.3 Measures of Central Tendency
    • 2.4 Measures of Variation
    • 2.5 Measures of Position

II. PROBABILITY AND PROBABILITY DISTRIBUTIONS

  1. Probability
    • 3.1 Basic Concepts of Probability and Counting
    • 3.2 Conditional Probability and the Multiplication Rule
    • 3.3 The Addition Rule
    • 3.4 Additional Topics in Probability and Counting
  2. Discrete Probability Distributions
    • 4.1 Probability Distributions
    • 4.2 Binomial Distributions
    • 4.3 More Discrete Probability Distributions
  3. Normal Probability Distributions
    • 5.1 Introduction to Normal Distributions and the Standard Normal Distribution
    • 5.2 Normal Distributions: Finding Probabilities
    • 5.3 Normal Distributions: Finding Values
    • 5.4 Sampling Distributions and the Central Limit Theorem
    • 5.5 Normal Approximations to Binomial Distributions

III. STATISTICAL INFERENCE

  1. Confidence Intervals
    • 6.1 Confidence Intervals for the Mean (S Known)
    • 6.2 Confidence Intervals for the Mean (S Unknown)
    • 6.3 Confidence Intervals for Population Proportions
    • 6.4 Confidence Intervals for Variance and Standard Deviation
  2. Hypothesis Testing with One Sample
    • 7.1 Introduction to Hypothesis Testing
    • 7.2 Hypothesis Testing for the Mean (S Known)
    • 7.3 Hypothesis Testing for the Mean (S Unknown)
    • 7.4 Hypothesis Testing for Proportions
    • 7.5 Hypothesis Testing for Variance and Standard Deviation
  3. Hypothesis Testing with Two Samples
    • 8.1 Testing the Difference Between Means (Independent Samples, S1 and S2 Known)
    • 8.2 Testing the Difference Between Means (Independent Samples, S1 and S2 Unknown)
    • 8.3 Testing the Difference Between Means (Dependent Samples)
    • 8.4 Testing the Difference Between Proportions

IV. MORE STATISTICAL INFERENCE

  1. Correlation and Regression
    • 9.1 Correlation
    • 9.2 Linear Regression
    • 9.3 Measures of Regression and Prediction Intervals
    • 9.4 Multiple Regression
  2. Chi-Square Tests and the F-Distribution
    • 10.1 Goodness-of-Fit Test
    • 10.2 Independence
    • 10.3 Comparing Two Variances
    • 10.4 Analysis of Variance
  3. Nonparametric Tests (Web Only)*
    • 11.1 The Sign Test
    • 11.2 The Wilcoxon Tests
    • 11.3 The Kruskal-Wallis Test
    • 11.4 Rank Correlation
    • 11.5 The Runs Test
  • * Available at www.pearson.com/math-stats-resources and in MyLab Statistics.

APPENDICES

  • A. Alternative Presentation of the Standard Normal Distribution
  • B. Tables
  • C. Normal Probability Plots

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