Description

Book Synopsis


Table of Contents
  • 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
  • 3. 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
  • 4. Discrete Probability Distributions
  • 4.1 Probability Distributions
  • 4.2 Binomial Distributions
  • 4.3 More Discrete Probability Distributions
  • 5. 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
  • 6. 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
  • 7. 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
  • 8. 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
  • 9. Correlation and Regression
  • 9.1 Correlation
  • 9.2 Linear Regression
  • 9.3 Measures of Regression and Prediction Intervals
  • 9.4 Multiple Regression
  • 10. 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
  • APPENDICES
  • Appendix A: Alternative Presentation of the Standard Normal Distribution
  • Appendix B: Tables

Elementary Statistics Picturing the World Global

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    A Paperback by Ron Larson, Betsy Farber

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      View other formats and editions of Elementary Statistics Picturing the World Global by Ron Larson

      Publisher: Pearson Education
      Publication Date: Publication Date: 1/30/2019 12:00:00 AM
      ISBN13: 9781292260464, 978-1292260464
      ISBN10: 1292260467

      Description

      Book Synopsis


      Table of Contents
      • 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
      • 3. 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
      • 4. Discrete Probability Distributions
      • 4.1 Probability Distributions
      • 4.2 Binomial Distributions
      • 4.3 More Discrete Probability Distributions
      • 5. 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
      • 6. 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
      • 7. 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
      • 8. 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
      • 9. Correlation and Regression
      • 9.1 Correlation
      • 9.2 Linear Regression
      • 9.3 Measures of Regression and Prediction Intervals
      • 9.4 Multiple Regression
      • 10. 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
      • APPENDICES
      • Appendix A: Alternative Presentation of the Standard Normal Distribution
      • Appendix B: Tables

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