Synopses & Reviews
ELEMENTARY STATISTICS: A STEP BY STEP APPROACH is for general beginning statistics courses with a basic algebra prerequisite. The book is non-theoretical, explaining concepts intuitively and teaching problem solving through worked examples and step-by-step instructions. This edition features increased emphasis on Excel, MINITAB, and the TI-83 Plus graphing calculator, computing technologies commonly used in such coureses.
About the Author
Allan G. Bluman is Professor of Mathematics at Community College of Allegheny County, near Pittsburgh. For the McKeesport and New Kensington Campuses of Pennsylvania State University, he has taught teacher-certification and graduate education statistics courses. Prior to his college teaching, he taught mathematics at a junior high school.
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.
Table of Contents
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 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, and Expectation
5-4 The Binomial Distribution
5-5 Other Types of Distributions (Optional)
5-6 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 (s Known or n³30)
7-3 Confidence Intervals for the Mean (s Unknown or 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^2 test for a Variance or Standard Deviation
8-7 Additional Topics Regarding 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 Proportions
9-7 Summary
10 Correlation and Regression
10-1 Introduction
10-2 Scatter Plots
10-3 Correlation
10-4 Regression
10-5 Coefficient of Determination and Standard Error of the Estimate
10-6 Multiple Regression (Optional)
10-7 Summary
11 Other Chi-Square Tests
11-1 Introduction
11-2 Test for Goodness of Fit
11-3 Tests Using Contingency Tables
11-4 Summary
12 Analysis of Variance
12-1 Introduction
12-2 One-Way Analysis of Variance
12-3 The Scheffé Test and the Tukey Test
12-4 Two-Way Analysis of Variance
12-5 Summary
13 Nonparametric Statistics
13-1 Introduction
13-2 Advantages and Disadvantages of Nonparametric Methods
13-3 The Sign Test
13-4 The Wilcoxon Rank Sum Test
13-5 The Wilcoxon Signed-Rank Test
13-6 The Kruskal-Wallis Test
13-7 The Spearman Rank Correlation Coefficient and the Runs Test
18-8 Summary
14 Sampling and Simulation
14-1 Introduction
14-2 Common Sampling Techniques
14-3 Surveys and Questionnaire Design
14-4 Simulation Techniques
14-5 The Monte Carlo Method
14-6 Summary
Appendix A: Algebra Review
Appendix B-1: Writing the Research Report
Appendix B-2: Bayes's Theorem
Appendix B-3: Alternate Method for the Standard Normal Distribution
Appendix C: Tables
Appendix D: Data Bank
Appendix E: Glossary
Appendix F: Bibliography
Appendix G: Photo Credits
Appendix H: Selected Answers