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ISBN 10: 0123743885
ISBN 13: 978-0123743886
Author: Sheldon Ross
Introductory Statistics, Third Edition, presents statistical concepts and techniques in a manner that will teach students not only how and when to utilize the statistical procedures developed, but also to understand why these procedures should be used. This book offers a unique historical perspective, profiling prominent statisticians and historical events in order to motivate learning.
To help guide students towards independent learning, exercises and examples using real issues and real data (e.g., stock price models, health issues, gender issues, sports, scientific fraud) are provided. The chapters end with detailed reviews of important concepts and formulas, key terms, and definitions that are useful study tools. Data sets from text and exercise material are available for download in the text website.
This text is designed for introductory non-calculus based statistics courses that are offered by mathematics and/or statistics departments to undergraduate students taking a semester course in basic Statistics or a year course in Probability and Statistics.
Introductory Statistics 3rd Table of contents:
Chapter 1. Introduction to Statistics
1.1 Introduction
1.2 The Nature of Statistics
1.2.1 Data Collection
1.2.2 Inferential Statistics and Probability Models
1.3 Populations and Samples
*1.3.1 Stratified Random Sampling
1.4 A Brief History of Statistics
Key Terms
The Changing Definition of Statistics
Review Problems
Chapter 2. Describing Data Sets
2.1 Introduction
2.2 Frequency Tables and Graphs
2.2.1 Line Graphs, Bar Graphs, and Frequency Polygons
2.2.2 Relative Frequency Graphs
2.2.3 Pie Charts
Problems
2.3 Grouped Data and Histograms
Problems
2.4 Stem-and-Leaf Plots
Problems
2.5 Sets of Paired Data
Problems
2.6 Some Historical Comments
Key Terms
Summary
Review Problems
Chapter 3. Using Statistics to Summarize Data Sets
3.1 Introduction
3.2 Sample Mean
3.2.1 Deviations
Problems
3.3 Sample Median
Problems
3.3.1 Sample Percentiles
3.4 Sample Mode
Problems
3.5 Sample Variance and Sample Standard Deviation
Problems
3.6 Normal Data Sets and the Empirical Rule
3.7 Sample Correlation Coefficient
Problems
Key Terms
Summary
Review Problems
Chapter 4. Probability
4.1 Introduction
4.2 Sample Space and Events of an Experiment
Problems
4.3 Properties of Probability
Problems
4.4 Experiments Having Equally Likely Outcomes
Problems
4.5 Conditional Probability and Independence
Problems
*4.6 Bayes’ Theorem
Problems
*4.7 Counting Principles
Problems
Key Terms
Summary
Review Problems
Chapter 5. Discrete Random Variables
5.1 Introduction
5.2 Random Variables
Problems
5.3 Expected Value
5.3.1 Properties of Expected Values
Problems
5.4 Variance of Random Variables
5.4.1 Properties of Variances
Problems
5.5 Binomial Random Variables
5.5.1 Expected Value and Variance of a Binomial Random Variable
Problems
*5.6 Hypergeometric Random Variables
Problems
*5.7 Poisson Random Variables
Problems
Key Terms
Summary
Review Problems
Chapter 6. Normal Random Variables
6.1 Introduction
6.2 Continuous Random Variables
Problems
6.3 Normal Random Variables
Problems
6.4 Probabilities Associated with a Standard Normal Random Variable
Problems
6.5 Finding Normal Probabilities: Conversion to the Standard Normal
6.6 Additive Property of Normal Random Variables
Problems
6.7 Percentiles of Normal Random Variables
Problems
Key Terms
Summary
Review Problems
Chapter 7. Distributions of Sampling Statistics
7.1 A Preview
7.2 Introduction
7.3 Sample Mean
Problems
7.4 Central Limit Theorem
7.4.1 Distribution of the Sample Mean
7.4.2 How Large a Sample Is Needed?
Problems
7.5 Sampling Proportions from a Finite Population
7.5.1 Probabilities Associated with Sample Proportions: The Normal Approximation to the Binomial Dis
Problems
7.6 Distribution of the Sample Variance of a Normal Population
Problems
Key Terms
Summary
Review Problems
Chapter 8. Estimation
8.1 Introduction
8.2 Point Estimator of a Population Mean
Problems
8.3 Point Estimator of a Population Proportion
Problems
*8.3.1 Estimating the Probability of a Sensitive Event
Problems
8.4 Estimating a Population Variance
Problems
8.5 Interval Estimators of the Mean of a Normal Population with Known Population Variance
8.5.1 Lower and Upper Confidence Bounds
Problems
8.6 Interval Estimators of the Mean of a Normal Population with Unknown Population Variance
8.6.1 Lower and Upper Confidence Bounds
Problems
8.7 Interval Estimators of a Population Proportion
8.7.1 Length of the Confidence Interval
8.7.2 Lower and Upper Confidence Bounds
Problems
Key Terms
Summary
Review Problems
Chapter 9. Testing Statistical Hypotheses
9.1 Introduction
9.2 Hypothesis Tests and Significance Levels
Problems
9.3 Tests Concerning the Mean of a Normal Population: Case of Known Variance
Problems
9.3.1 One-Sided Tests
9.4 The t Test for the Mean of a Normal Population: Case of Unknown Variance
Problems
9.5 Hypothesis Tests Concerning Population Proportions
9.5.1 Two-Sided Tests of p
Problems
Key Terms
Summary
Review Problems and Proposed Case Studies
Chapter 10. Hypothesis Tests Concerning Two Populations
10.1 Introduction
10.2 Testing Equality of Means of Two Normal Populations: Case of Known Variance
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
Chapter 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
Chapter 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 ß = 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
Chapter 13. Chi-Squared Goodness-of-Fit Tests
13.1 Introduction
13.2 Chi-Squared Goodness-of-Fit Tests
Problems
13.3 Testing for in Dependence 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
Chapter 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
Chapter 15. Quality Control
15.1 Introduction
15.2 The X 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
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