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Elementary Statistics, 9th edition

  • Neil A. Weiss

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Elementary Statistics, 9th Edition takes a data-driven approach that encourages you to apply your knowledge and develop statistical understanding. Weiss presents statistics fundamentals featuring data production and data analysis; data exploration is emphasized as an integral prelude to statistical inference. Careful, detailed explanations ease the learning process. This edition continues Weiss' tradition of cutting-edge learning aids, technology and data analysis. It includes hundreds of new and updated exercises with real data from journals, magazines, newspapers and websites.

Published by Pearson (June 15th 2022) - Copyright © 2023

ISBN-13: 9780137846221

Subject: Introductory Statistics

Category:

  • (NOTE: Each chapter concludes with Chapter in Review, Review Problems, Focusing on Data Analysis, Case Study Discussion, and Biography.)

  • Technology Resources
  • Data Sources

I: INTRODUCTION

  1. The Nature of Statistics
    • 1.1 Statistics Basics
    • 1.2 Simple Random Sampling
    • 1.3 Other Sampling Designs∗
    • 1.4 Experimental Designs∗

II: DESCRIPTIVE STATISTICS

  1. Organizing Data
    • Case Study: World's Richest People
    • 2.1 Variables and Data
    • 2.2 Organizing Qualitative Data
    • 2.3 Organizing Quantitative Data
    • 2.4 Distribution Shapes
    • 2.5 Misleading Graphs∗
  2. Descriptive Measures
    • Case Study: The Beatles' Song Length
    • 3.1 Measures of Center
    • 3.2 Measures of Variation
    • 3.3 Chebyshev's Rule and the Empirical Rule∗
    • 3.4 The Five-Number Summary; Boxplots
    • 3.5 Descriptive Measures for Populations; Use of Samples
  3. Descriptive Methods in Regression and Correlation
    • Case Study: Healthcare: Spending and Outcomes
    • 4.1 Linear Equations with One Independent Variable
    • 4.2 The Regression Equation
    • 4.3 The Coefficient of Determination
    • 4.4 Linear Correlation

III: PROBABILITY, RANDOM VARIABLES, AND SAMPLING DISTRIBUTIONS

  1. Probability and Random Variables
    • Case Study: Texas Hold ‘em
    • 5.1 Probability Basics
    • 5.2 Events
    • 5.3 Some Rules of Probability
    • 5.4 Discrete Random Variables and Probability Distributions∗
    • 5.5 The Mean and Standard Deviation of a Discrete Random Variable∗
    • 5.6 The Binomial Distribution∗
  2. The Normal Distribution
    • Case Study: Chest Sizes of Scottish Militiamen
    • 6.1 Introducing Normally Distributed Variables
    • 6.2 Areas under the Standard Normal Curve
    • 6.3 Working with Normally Distributed Variables
    • 6.4 Assessing Normality; Normal Probability Plots
  3. The Sampling Distribution of the Sample Mean
    • Case Study: The Chesapeake and Ohio Freight Study
    • 7.1 Sampling Error; the Need for Sampling Distributions
    • 7.2 The Mean and Standard Deviation of the Sample Mean
    • 7.3 The Sampling Distribution of the Sample Mean

IV: INFERENTIAL STATISTICS

  1. Confidence Intervals for One Population Mean
    • Case Study: Bank Robberies: A Statistical Analysis
    • 8.1 Estimating a Population Mean
    • 8.2 Confidence Intervals for One Population Mean When σ Is Known
    • 8.3 Confidence Intervals for One Population Mean When σ Is Unknown
  2. Hypothesis Tests for One Population Mean
    • Case Study: Gender and Sense of Direction
    • 9.1 The Nature of Hypothesis Testing
    • 9.2 Critical-Value Approach to Hypothesis Testing
    • 9.3 P-Value Approach to Hypothesis Testing
    • 9.4 Hypothesis Tests for One Population Mean When σ Is Known
    • 9.5 Hypothesis Tests for One Population Mean When σ Is Unknown 
  3. Inferences for Two Population Means
    • Case Study: Dexamethasone Therapy and IQ
    • 10.1 The Sampling Distribution of the Difference between Two Sample Means for Independent Samples
    • 10.2 Inferences for Two Population Means, Using Independent Samples: Standard Deviations Assumed Equal
    • 10.3 Inferences for Two Population Means, Using Independent Samples: Standard Deviations Not Assumed Equal
    • 10.4 Inferences for Two Population Means, Using Paired Samples
  4. Inferences for Population Proportions
    • Case Study: Arrested Youths
    • 11.1 Confidence Intervals for One Population Proportion
    • 11.2 Hypothesis Tests for One Population Proportion
    • 11.3 Inferences for Two Population Proportions
  5. Chi-Square Procedures
    • Case Study: Eye and Hair Color
    • 12.1 The Chi-Square Distribution
    • 12.2 Chi-Square Goodness-of-Fit Test
    • 12.3 Contingency Tables; Association
    • 12.4 Chi-Square Independence Test
    • 12.5 Chi-Square Homogeneity Test
  6. Analysis of Variance (ANOVA)
    • Case Study: Self-Perception and Physical Activity
    • 13.1 The F-Distribution
    • 13.2 One-Way ANOVA: The Logic
    • 13.3 One-Way ANOVA: The Procedure
  7. Inferential Methods in Regression and Correlation
    • Case Study: Shoe Size and Height
    • 14.1 The Regression Model; Analysis of Residuals
    • 14.2 Inferences for the Slope of the Population Regression Line
    • 14.3 Estimation and Prediction
    • 14.4 Inferences in Correlation
  • *Indicates optional material.

APPENDICES

  1. Statistical Tables
  2. Answers to Selected Exercises

Index

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