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Elementary Statistics: A Brief Version / Edition 4 available in Paperback, Multimedia

- ISBN-10:
- 0073283487
- ISBN-13:
- 9780073283487
- Pub. Date:
- 10/28/2006
- Publisher:
- McGraw-Hill Companies, The

## Overview

*Elementary Statistics: A Brief Version*, 3rd edition is a shorter version of the popular text *Elementary Statistics: A Step by Step Approach*, 5th edition. This softcover edition includes all the features of the longer book, but is designed for a course in which the time available limits the number of topics covered. The book is written for general beginning statistics courses with a basic algebra prerequisite. The book use a non-theoretical approach, explaining concepts intuitively and teaching problem solving through worked examples step-by-step.

## Product Details

ISBN-13: | 9780073283487 |
---|---|

Publisher: | McGraw-Hill Companies, The |

Publication date: | 10/28/2006 |

Edition description: | Video Lecture on DVD |

Product dimensions: | 5.90(w) x 9.90(h) x 0.30(d) |

## Read an Excerpt

*Elementary Statistics: A Brief Version*, 3rd edition is a shorter version of the popular text *Elementary Statistics: A Step by Step Approach*, 5th edition. This softcover edition includes all the features of the longer book, but is designed for a course in which the time available limits the number of topics covered. The book is written for general beginning statistics courses with a basic algebra prerequisite. The book use a non-theoretical approach, explaining concepts intuitively and teaching problem solving through worked examples step-by-step.

## First Chapter

*Elementary Statistics: A Brief Version*, 3rd edition is a shorter version of the popular text *Elementary Statistics: A Step by Step Approach*, 5th edition. This softcover edition includes all the features of the longer book, but is designed for a course in which the time available limits the number of topics covered. The book is written for general beginning statistics courses with a basic algebra prerequisite. The book use a non-theoretical approach, explaining concepts intuitively and teaching problem solving through worked examples step-by-step.

## Table of Contents

#### Preface

#### 1: The Nature of Probability and Statistics

#### 1.1 Introduction

#### 1.2 Descriptive and Inferential Statistics

#### 1.3 Variables and Types of Data

#### 1.4 Data Collection and Sampling Techniques

#### 1.5 Observational and Experimental Studies

#### 1.6 Uses and Misuses of Statistics

#### 1.7 Computers and Calculators

#### 1.8 Summary

#### 2: Frequency Distributions and Graphs

#### 2.1 Introduction

#### 2.2 Organizing Data

#### 2.3 Histograms, Frequency Polygons, and Ogives

#### 2.4 Other Types of Graphs

#### 2.5 Paired Data and Scatter Plots

#### 2.6 Summary

#### 3: Data Description

#### 3.1 Introduction

#### 3.2 Measures of Central Tendency

#### 3.3 Measures of Variation

#### 3.4 Measures of Position

#### 3.5 Exploratory Data Analysis

#### 3.6 Summary

#### 4: Probability and Counting Rules

#### 4.1 Introduction

#### 4.2 Sample Spaces and Probability

#### 4.3 The Addition Rules for Probability

#### 4.4 The Multiplication Rules and Conditional Probability

#### 4.5 Counting Rules

#### 4.6 Probability and Counting Rules

#### 4.7 Summary

#### 5: Discrete Probability Distributions

#### 5.1 Introduction

#### 5.2 Probability Distributions

#### 5.3 Mean, Variance, Standard Deviation, and Expectation

#### 5.4 The Binomial Distribution

#### 5.5 Summary

#### 6: The Normal Distribution

#### 6.1 Introduction

#### 6.2 Properties of the Normal Distribution

#### 6.3 The Standard Normal Distribution

#### 6.4 Applications of the Normal Distribution

#### 6.5 The Central Limit Theorem

#### 6.6 The Normal Approximation to the Binomial Distribution

#### 6.7 Summary

#### 7: Confidence Intervals and Sample Size

#### 7.1 Introduction

#### 7.2 Confidence Intervals for the Mean (Sigma Known or n __>__ 30) and Sample Size

#### 7.3 Confidence Intervals forthe Mean (Sigma Unknown and n < 30)

#### 7.4 Confidence Intervals and Sample Size for Proportions

#### 7.5 Confidence Intervals for Variances and Standard Deviations

#### 7.6 Summary

#### 8: Hypothesis Testing

#### 8.1 Introduction

#### 8.2 Steps in Hypothesis Testing – Traditional Method

#### 8.3 z Test for a Mean

#### 8.4 t Test for a Mean

#### 8.5 z test for a Proportion

#### 8.6 Chi-Square Test for a Variance or Standard Deviation

#### 8.7 Confidence Intervals and Hypothesis Testing

#### 8.8 Summary

#### 9: Testing the Difference Between Two Means, Two Variances, and Two Proportions

#### 9.1 Introduction

#### 9.2 Testing the Difference Between Two Means: Large Samples

#### 9.3 Testing the Difference Between Two Variances

#### 9.4 Testing the Difference Between Two Means: Small Independent Samples

#### 9.5 Testing the Difference Between Two Means: Small Dependent Samples

#### 9.6 Testing the Difference Between Two Proportions

#### 9.7 Summary

#### Hypothesis Testing Summary

#### 10: Correlation and Regression

#### 10.1 Inroduction

#### 10.2 Correlation

#### 10.3 Regression

#### 10.4 Coefficient of Determination and Standard Error of the Estimate

#### 10.5 Summary

#### 11: Chi-Square and Analysis of Variance (ANOVA)

#### 11.1 Introduction

#### 11.2 Test for Goodness of Fit

#### 11.3 Tests Using Contingency Tables

#### 11.4 Analysis of Variance (ANOVA)

#### 11.5 Summary

#### Hypothesis Testing Summary

## Reading Group Guide

#### Preface

#### 1: The Nature of Probability and Statistics

#### 1.1 Introduction

#### 1.2 Descriptive and Inferential Statistics

#### 1.3 Variables and Types of Data

#### 1.4 Data Collection and Sampling Techniques

#### 1.5 Observational and Experimental Studies

#### 1.6 Uses and Misuses of Statistics

#### 1.7 Computers and Calculators

#### 1.8 Summary

#### 2: Frequency Distributions and Graphs

#### 2.1 Introduction

#### 2.2 Organizing Data

#### 2.3 Histograms, Frequency Polygons, and Ogives

#### 2.4 Other Types of Graphs

#### 2.5 Paired Data and Scatter Plots

#### 2.6 Summary

#### 3: Data Description

#### 3.1 Introduction

#### 3.2 Measures of Central Tendency

#### 3.3 Measures of Variation

#### 3.4 Measures of Position

#### 3.5 Exploratory Data Analysis

#### 3.6 Summary

#### 4: Probability and Counting Rules

#### 4.1 Introduction

#### 4.2 Sample Spaces and Probability

#### 4.3 The Addition Rules for Probability

#### 4.4 The Multiplication Rules and Conditional Probability

#### 4.5 Counting Rules

#### 4.6 Probability and Counting Rules

#### 4.7 Summary

#### 5: Discrete Probability Distributions

#### 5.1 Introduction

#### 5.2 Probability Distributions

#### 5.3 Mean, Variance, Standard Deviation, and Expectation

#### 5.4 The Binomial Distribution

#### 5.5 Summary

#### 6: The Normal Distribution

#### 6.1 Introduction

#### 6.2 Properties of the Normal Distribution

#### 6.3 The Standard Normal Distribution

#### 6.4 Applications of the Normal Distribution

#### 6.5 The Central Limit Theorem

#### 6.6 The Normal Approximation to the Binomial Distribution

#### 6.7 Summary

#### 7: Confidence Intervals and Sample Size

#### 7.1 Introduction

#### 7.2 Confidence Intervals for the Mean (Sigma Known or n __>__ 30) and Sample Size

#### 7.3 Confidence Intervals forthe Mean (Sigma Unknown and n < 30)

#### 7.4 Confidence Intervals and Sample Size for Proportions

#### 7.5 Confidence Intervals for Variances and Standard Deviations

#### 7.6 Summary

#### 8: Hypothesis Testing

#### 8.1 Introduction

#### 8.2 Steps in Hypothesis Testing – Traditional Method

#### 8.3 z Test for a Mean

#### 8.4 t Test for a Mean

#### 8.5 z test for a Proportion

#### 8.6 Chi-Square Test for a Variance or Standard Deviation

#### 8.7 Confidence Intervals and Hypothesis Testing

#### 8.8 Summary

#### 9: Testing the Difference Between Two Means, Two Variances, and Two Proportions

#### 9.1 Introduction

#### 9.2 Testing the Difference Between Two Means: Large Samples

#### 9.3 Testing the Difference Between Two Variances

#### 9.4 Testing the Difference Between Two Means: Small Independent Samples

#### 9.5 Testing the Difference Between Two Means: Small Dependent Samples

#### 9.6 Testing the Difference Between Two Proportions

#### 9.7 Summary

#### Hypothesis Testing Summary

#### 10: Correlation and Regression

#### 10.1 Inroduction

#### 10.2 Correlation

#### 10.3 Regression

#### 10.4 Coefficient of Determination and Standard Error of the Estimate

#### 10.5 Summary

#### 11: Chi-Square and Analysis of Variance (ANOVA)

#### 11.1 Introduction

#### 11.2 Test for Goodness of Fit

#### 11.3 Tests Using Contingency Tables

#### 11.4 Analysis of Variance (ANOVA)

#### 11.5 Summary

#### Hypothesis Testing Summary

## Interviews