Elementary Statistics: A Brief Version - Brossura

Professor Bluman received his B.S. from California State College in California, Penn.; his M.Ed. from the University of Pittsburgh; and, in 1971, his Ed.D., also from the University of Pittsburgh. His major field of study was mathematics education.

In addition to Elementary Statistics: A Step by Step Approach, Third Edition, and Elementary Statistics: A Brief Version, the author has published several professional articles and the Modern Math Fun Book (Cuisenaire Publishing Company). He has spoken and presided at national and local mathematics conferences and has served as newsletter editor for the Pennsylvania State Mathematics Association of Two-Year Colleges. He is a member of the American Statistical Association, the National Council of Teachers of Mathematics, and the Mathematics Council of Western Pennsylvania. Al Bluman is married and has two children. His hobbies include writing, bicycling, and swimming.

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 for the 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