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Statistics : Concepts and Applications

Statistics : Concepts and Applications - 95 edition

Statistics : Concepts and Applications - 95 edition

ISBN13: 9780256119350

ISBN10: 025611935X

Statistics : Concepts and Applications by Amir D. Aczel - ISBN 9780256119350
Edition: 95
Copyright: 1995
Publisher: Richard D. Irwin, Inc.
International: No
Statistics : Concepts and Applications by Amir D. Aczel - ISBN 9780256119350

ISBN13: 9780256119350

ISBN10: 025611935X

Edition: 95

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STATISTICS: Concepts and Applications
Amir Aczel, Bentley College
0-256-11935-X / 1995 / Hardcover
January 1995

Statistics Concepts and Applications is a carefully researched general statistics text that covers the latest topics and applications of statistics. Aczel's text has an integrated real world emphasis and maintains a strong cross disciplinary emphasis, punctuated by superior applications. ''The use of magazine and newspaper articles in his examples to illustrate statistical methodology is novel and interesting''--Joe Ibrahim--Northern Illinois University. Integrates sampling and confidence intervals into one chapter. Uses popular and academic press reports for examples and problems. Provides modern coverage of 'hot' statistical topics, such as the use of P-Values, confidence intervals, quality assurance and others. Short, focused coverage (700 pages). 10 chapters, designed for one term courses. A large number of unique and intuitive graphics to assist the non-technical student. Interviews with prominent practitioners and statisticians about the use of statistics in various fields of interest, such as, law, government, politics, economics, and sports.

Table of Contents

Table of Contents

1. Information, Everywhere

1.2 Methods of Displaying Data
1.3 Percentile, Quartiles, and the Median
1.4 Box Plots
1.5 Samples and Populations
1.6 Measures of Central Tendency
1.7 Measures of Variability
1.8 Caution, Care with Numbers, and Ethics

2. What are the Chances?

2.1 Introduction
2.2 Basic Definitions, Events, Sample Space, and Probabilities
2.3 Basic Rules for Probability Mutually Exclusive Events
2.4 Conditional Probability
2.5 Independence of Events Product Rules for Independent Events
2. 6 (Optional) Bayes Theorem

3. Chance Quantities

3.1 Introduction
3.2 Expected Values of Discrete Random Variable
3.3 The Binomial Distribution
3.4 Continuous Random Variable

4. The Bell-Shaped Curve

4.1 Introduction
4.2 The Standard Normal Distribution
4.3 The Transformation of Normal Random Variable
4.4 The Relationship Between X and Z and the Use of the Inverse Transformation
4. 5 (Optional) The Normal Distribution as an Approximation to Other Probability Distributions
4.6 Normal Data

5. Let's Take a Sample

5.1 Introduction
5.2 Sampling Distributions
5.3 The Sampling Distribution of the Sample Mean
5.4 Confidence Intervals
5.5 Confidence Interval for the Population Mean when Sigma is Unknown--the t distribution
5.6 The Sampling Distribution of the Sample Proportion
5.7 Sample Size Determination
5.8 The Polls--Epilogue

6. Trial By Probability

6.1 Introduction
6.2 Statistical Hypothesis Tests
6.3 A Two-Tailed Test for the Population Mean Standard Form of the Test
6.4 A Two-Tailed Test for the Population Proportion Standard Form of the Test
6.5 One-Tailed Tests
6.6 The p-Value

7. Making Comparisons

7.1 Introduction
7.2 Pair-Observations Comparisons
7.3 A Test for the Difference between Two Population Means Using Independent Random Samples
7.4 A Test for the Difference between Two Populations Means Assuming Equal Population Variances
7.5 A Large-Sample Test for the Difference Between Two Population Proportions

8. So Many Choices, So Little Time

8.1 Introduction
8.2 The Hypothesis Test of Analysis of Variance
8.3 The Theory and the Computations of ANOVA
8.4 contingency Table Analysis--a Chi-Square Test for Independence

9. Is There a Relationship?

9.1 Introduction
9.2 The Simple Linear Regression Model
9.3 Estimation: The Method of Least Squares
9.4 Error Variance and the Standard Errors of Regression Estimates
9.5 How Good is the Regression?
9.6 Residual Analysis and checking for Model Inadequacies
9.7 Using the Regression Model for Prediction
9.8 Correlation

10. The Quest for Quality

10.1 Introduction
10.2 The X-Bar Chart
10.3 The R Chart and the S Chart
10.4 The p Chart
10.5 The c Chart