Introductory Statistics MAC

by Sheldon M. Ross

This exciting new text is written for the introductory non-calculus based statistics course offered in mathematics and/or statistics departments. The text contains an abundance of well constructed and interesting problems at varying levels of difficulty. There is an excellent balance between basic skills and applications, with real-world data adding to its overall appeal.

Genres: Mathematics, Nonfiction

800 pages, Hardcover

First published November 1, 1995

About the author

Sheldon M. Ross is the Epstein Chair Professor at the Department of Industrial and Systems Engineering, University of Southern California. He received his Ph.D. in statistics at Stanford University in 1968 and was formerly a Professor at the University of California, Berkeley, from 1976 until 2004. He has published more than 100 articles and a variety of textbooks in the areas of statistics and applied probability, including Topics in Finite and Discrete Mathematics (2000), Introduction to Probability and Statistics for Engineers and Scientists, 4th edition (2009), A First Course in Probability, 8th edition (2009), and Introduction to Probability Models, 10th edition (2009), among others. Dr Ross serves as the editor for Probability in the Engineering and Informational Sciences.

Reviews

[Cameryn · Rating 1 out of 5]

Made it through 70% of this textbook. Likely a much higher percentage than what I’ll be scoring for my stats course.

This book had a strong start. With probability formulas and fancy calculations I was hooked from the beginning. Oh how naive I was.

We move onto estimation. Now this is where I began to lose the storyline. There were plot holes and unexplained characters (where did confidence intervals and t-statistics come from??) and honestly the calculations just weren’t doing it for me anymore.

Next came the hypothesis testing. With the null and alternative hypotheses and p-values I thought we were back on track - stats was saved! Until testing on two populations showed up and killed off all hope for a happy ending to this book. Sorry, should’ve prefaced that with a spoiler warning.

In summary, if this was a hypothesis test I would say there is statistical evidence to reject the null hypothesis that this was an enjoyable book. I can almost guarantee that this book - and statistics as a whole - is not something you wish to pursue.

My tears shed throughout this book followed a normal distribution because the sample size was that large. Maybe keep that in mind before picking up this book.

[el. · Rating 2 out of 5]

realizzati molto bene i primi capitoli.
ad un certo punto c'è uno stacco e sembra quasi manchino delle pagine.
alcuni contenuti riportati in modo molto, molto, molto sintetico.
sono presenti molti esercizi ma fondamentale poco utili in quanto quasi tutti senza svolgimento o risultati di qualsiasi tipo.

[Teo · Rating 3 out of 5]

2017.05.11–2017.06.19

Basic introduction to statistics. I read chapters 1–9 for a course.

Contents

Ross SM (2010) Introductory Statistics

About the Author
Preface
Acknowledgments

01. Introduction to Statistics
01.1. Introduction
01.2. The Nature of Statistics
01.2.1. Data Collection
01.2.2. Inferential Statistics and Probability Models
01.3. Populations and Samples
01.3.1. Stratified Random Sampling
01.4. A Brief History of Statistics
Key Terms
The Changing Defnition of Statistics
Review Problems

02. Describing Data Sets
02.1. Introduction
02.2. Frequency Tables and Graphs
02.2.1. Line Graphs, Bar Graphs, and Frequency Polygons
02.2.2. Relative Frequency Graphs
02.3.3. Pie Charts
Problems
02.3. Grouped Data and Histograms
Problems
02.4. Stem-and-Leaf Plots
Problems
02.5. Sets of Paired Data
Problems
02.6. Some Historical Comments
Key Terms
Summary
Review Problems

03. Using Statistics to Summarize Data Sets
03.1. Introduction
03.2. Sample Mean
03.2.1. Deviations
Problems
03.3. Sample Median
Problems
03.3.1. Sample Percentiles
03.4. Sample Mode
Problems
03.5. Sample Variance and Sample Standard Deviation
Problems
03.6. Normal Data Sets and the Empirical Rule
Problems
03.7. Sample Correlation Coefficient
Problems
Key Terms
Summary
Review Problems

04. Probability
04.1. Introduction
04.2. Sample Space and Events of an Experiment
Problems
04.3. Properties of Probability
Problems
04.4. Experiments Having Equally Likely Outcomes
Problems
04.5. Conditional Probability and Independence
Problems
04.6. Bayes Theorem
Problems
04.7. Counting Principles
Problems
Key Terms
Summary
Review Problems

05. Discrete Random Variables
05.1. Introduction
05.2. Random Variable
Problems
05.3. Expected Value
05.3.1. Properties of Expected Values
Problems
05.4. Variance of Random Variables
05.4.1. Properties of Variances
Problems
05.5. Binomial Random Variables
05.5.1. Expected Value and Variance of a Binomial Random Variable
Problems
05.6. Hypergeometric Random Variables
Problems
05.7. Poisson Random Variables
Problems
Key Terms
Summary
Review Problems

06. Normal Random Variables
06.1. Introduction
06.2. Continuous Random Variables
Problems
06.3. Normal Random Variables
Problems
06.4. Probabilities Associated with a Standard Normal Random Variable
Problems
06.5. Finding Normal Probabilities: Conversion to the Standard Normal
06.6. Additive Property of Normal Random Variables
Problems
06.7. Percentiles of Normal Random Variables
Problems
Key Terms
Summary
Review Problems

07. Distributions of Sampling Statistics
07.1. A Preview
07.2. Introduction
07.3. Sample Mean
Problems
07.4. Central Limit Theorem
07.4.1. Distribution of the Sample Mean
07.4.2. How Large a Sample Is Needed?
Problems
07.5. Sampling Proportions from a Finite Population
07.5.1. Probabilities Associated with Sample Proportions: The Normal Approximation to the Binomial Distribution
Problems
07.6. Distribution of the Sample Variance of a Normal Population
Problems
Key Terms
Summary
Review Problems

08. Estimation
08.1. Introduction
08.2. Point Estimator of a Population Mean
Problems
08.3. Point Estimator of a Population Proportion
Problems
08.3.1. Estimating the Probability of a Sensitive Event
Problems
08.4. Estimating a Population Variance
Problems
08.5. Interval Estimators of the Mean of a Normal Population with Known Population Variance
08.5.1. Lower and Upper Confidence Bounds
Problems
08.6. Interval Estimators of the Mean of a Normal Population with Unknown Population Variance
08.6.1. Lower and Upper Confidence Bounds
Problems
08.7. Interval Estimators of a Population Proportion
08.7.1. Length of the Confidence Interval
08.7.2. Lower and Upper Confidence Bounds
Problems
Key Terms
Summary
Review Problems

09. Testing Statistical Hypotheses
09.1. Introduction
09.2. Hypotheses Tests and Significance Levels
Problems
09.3. Tests Concerning the Mean of a Normal Population: Case of Known Variance
Problems
09.3.1. One-Sided Tests
09.4. The t Test for the Mean of a Normal Population: Case of Unknown Variance
Problems
09.5. Hypothesis Tests Concerning Population Proportions
09.5.1. Two-Sided Tests of p
Problems
Key Terms
Summary
Review Problems and Proposed Case Studies

10. Hypothesis Tests Concerning Two Populations
10.1. Introduction
10.2. Testing Equality of Means of Two Normal Populations: Case of Known Variances
Problems
10.3. Testing Equality of Means: Unknown Variances and Large Sample Sizes
Problems
10.4. Testing Equality of Means: Small-Sample Tests when the Unknown Population Variances Are Equal
Problems
10.5. Paired-Sample t Test
Problems
10.6. Testing Equality of Population Proportions
Problems
Key Terms
Summary
Review Problems

11. Analysis of Variance
11.1. Introduction
11.2. One-Factor Analysis of Variance
A Remark on the Degrees of Freedom
Problems
11.3. Two-Factor Analysis of Variance: Introduction and Parameter Estimation
Problems
11.4. Two-Factor Analysis of Variance: Testing Hypotheses
Problems
11.5. Final Comments
Key Terms
Summary
Review Problems

12. Linear Regression
12.1. Introduction
12.2. Simple Linear Regression Model
Problems
12.3. Estimating the Regression Parameters
Problems
12.4. Error Random Variable
Problems
12.5. Testing the Hypothesis that β = 0
Problems
12.6. Regression to the Mean
12.6.1. Why Biological Data Sets Are Often Normally Distributed
Problems
12.7. Prediction Intervals for Future Responses
Problems
12.8. Coefficient of Determination
Problems
12.9. Sample Correlation Coefficient
Problems
12.10. Analysis of Residuals: Assessing the Model
Problems
12.11. Multiple Linear Regression Model
12.11.1. Dummy Variables for Categorical Data
Problems
Key Terms
Summary
Review Problems

13. Chi-Squared Goodness-of-Fit Tests
13.1. Introduction
13.2. Chi-Squared Goodness-of-Fit Tests
Problems
13.3. Testing for Independence in Populations Classified According to Two Characteristics
Problems
13.4. Testing for Independence in Contingency Tables with Fixed Marginal Totals
Problems
Key Terms
Summary
Review Problems

14. Nonparametric Hypotheses Tests
14.1. Introduction
14.2. Sign Test
14.2.1. Testing the Equality of Population Distributions when Samples Are Paired
14.2.2. One-Sided Tests
Problems
14.3. Signed-Rank Test
14.3.1. Zero Differences and Ties
Problems
14.4. Rank-Sum Test for Comparing Two Populations
14.4.1. Comparing Nonparametric Tests with Tests that Assume Normal Distributions
Problems
14.5. Runs Test for Randomness
Problems
14.6. Testing the Equality of Multiple Probability Distributions
14.6.1. When the Data Are a Set of Comparison Rankings
Problems
14.7. Permutation Tests
Problems
Key Terms
Summary
Review Problems

15. Quality Control
15.1. Introduction
15.2. The X-bar Control Chart for Detecting a Shift in the Mean
Problems
15.2.1. When the Mean and Variance Are Unknown
15.2.2. S Control Charts
Problems
15.3. Control Charts for Fraction Defective
Problems
15.4. Exponentially Weighted Moving-Average Control Charts
Problems
15.5. Cumulative-Sum Control Charts
Problems
Key Terms
Summary
Review Problems

Appendices
• Appendix A. A Data Set
• Appendix B. Mathematical Preliminaries
• • B.1. Summation
• • B.2. Absolute Value
• • B.3. Set Notation
• Appendix C. How to Choose a Random Sample
• Appendix D. Tables
• • Table D.1. Standard Normal Probabilities
• • Table D.2. Percentiles t sub n,α of t Distributions
• • Table D.3. Percentiles χ^2 sub n,α of the Chi-Squared Distributions
• • Table D.4. Percentiles of F Distributions
• • Table D.5. Binomial Distribution Function
• Appendix E. Programs

Answers to Odd-Numbered Problems
Index

[Calvin · Rating 4 out of 5]

Overall not a bad book, this was used as the textbook for a first year advanced statistics course I took in my 2nd semester.

The only thing I didn't really like was how inconsistent the answers are, in the sense that some sections have answers and some don't. For example, there are no answers for chapter reviews. Also, I wish there was more than just the numerical answer, it doesn't really help much and I got stuck trying to find the right answer (at least, the one given in the textbook) for a handful of problems.

Other than that, the explanations are fine and the examples are good.