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Edition: 8TH 01

Copyright: 2001

Publisher: Addison-Wesley Longman, Inc.

Published: 2001

International: No

Copyright: 2001

Publisher: Addison-Wesley Longman, Inc.

Published: 2001

International: No

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**Triola, Mario F.: Dutchess Community College**

**1. Introduction to Statistics. **

Overview.

The Nature of Data.

Uses and Abuses of Statistics.

Design of Experiments.

**2. Describing, Exploring, and Comparing Data. **

Overview.

Summarizing Data with Frequency Tables.

Pictures of Data.

Measures of Center.

Measures of Variation.

Measures of Position.

Exploratory Data Analysis (EDA).

**3. Probability. **

Overview.

Fundamentals.

Addition Rule.

Multiplication Rule: Basics.

Multiplication Rule: Complements and Conditional Probability.

Probabilities Through Simulations.

Counting.

**4. Probability Distributions. **

Overview.

Random Variables.

Binomial Probability Distributions.

Mean, Variance, and Standard Deviation for the BinomialDistribution.

The Poisson Distribution.

**5. Normal Probability Distributions. **

Overview.

The Standard Normal Distribution.

Nonstandard Normal Distributions: Finding Probabilities.

Nonstandard Normal Distributions: Finding Values.

The Central Limit Theorem.

Normal Distribution as Approximation to Binomial Distribution.

Determining Normality.

**6. Estimates and Sample Sizes. **

Overview.

Estimating a Population Mean: Large Samples.

Estimating a Population Mean: Small Samples.

Determining Sample Size.

Estimating a Population Proportion.

Estimating a Population Variance.

**7. Hypothesis Testing. **

Overview.

Fundamentals of Hypothesis Testing.

Testing a Claim about a Mean: Large Samples.

Testing a Claim about a Mean: Small Samples.

Testing a Claim about a Proportion.

Testing a Claim about a Standard Deviation or Variance.

**8. Inferences from Two Samples. **

Overview.

Inferences about Two Means: Independent and Large Samples.

Inferences about Two Means: Matched Pairs.

Inferences about Two Proportions.

Comparing Variation in Two Samples.

Inferences about Two Means: Independent and Small Samples.

**9. Correlation and Regression. **

Overview.

Correlation.

Regression.

Variation and Prediction Intervals.

Multiple Regression.

Modeling.

**10. Multinomial Experiments and Contingency Tables. **

Overview.

Multinomial Experiments: Goodness-Of-Fit.

Contingency Tables: Independence and Homogeneity.

**11. Analysis of Variance. **

Overview.

One-Way ANOVA.

Two-Way ANOVA.

**12. Statistical Process Control. **

Overview.

Control Charts for Variation and Mean.

Control Charts for Attributes.

**13. Nonparametric Statistics. **

Overview.

Sign Test.

Wilcoxon Signed-Ranks Test for Matched Pairs.

Wilcoxon Rank-Sum Test for Two Independent Samples.

Kruskal-Wallis Test.

Rank Correlation.

Runs Test for Randomness.

**14. Projects, Procedures, Perspectives. **

A Statistics Group Project.

Which Procedure Applies?

A Perspective.

**Appendices. **

Appendix A: Tables.

Appendix B: Data Sets.

Appendix C: TI-83 Plus Reference.

Appendix D: Glossary.

Appendix E: Bibliography.

Appendix F: Answers to Odd-Numbered Exercises (and All ReviewExercises and All Cumulative Review Exercises)

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Author Bio

**Triola, Mario F.: Dutchess Community College**

Table of Contents

**1. Introduction to Statistics. **

Overview.

The Nature of Data.

Uses and Abuses of Statistics.

Design of Experiments.

**2. Describing, Exploring, and Comparing Data. **

Summarizing Data with Frequency Tables.

Pictures of Data.

Measures of Center.

Measures of Variation.

Measures of Position.

Exploratory Data Analysis (EDA).

**3. Probability. **

Fundamentals.

Addition Rule.

Multiplication Rule: Basics.

Multiplication Rule: Complements and Conditional Probability.

Probabilities Through Simulations.

Counting.

**4. Probability Distributions. **

Random Variables.

Binomial Probability Distributions.

Mean, Variance, and Standard Deviation for the BinomialDistribution.

The Poisson Distribution.

**5. Normal Probability Distributions. **

The Standard Normal Distribution.

Nonstandard Normal Distributions: Finding Probabilities.

Nonstandard Normal Distributions: Finding Values.

The Central Limit Theorem.

Normal Distribution as Approximation to Binomial Distribution.

Determining Normality.

**6. Estimates and Sample Sizes. **

Estimating a Population Mean: Large Samples.

Estimating a Population Mean: Small Samples.

Determining Sample Size.

Estimating a Population Proportion.

Estimating a Population Variance.

**7. Hypothesis Testing. **

Fundamentals of Hypothesis Testing.

Testing a Claim about a Mean: Large Samples.

Testing a Claim about a Mean: Small Samples.

Testing a Claim about a Proportion.

Testing a Claim about a Standard Deviation or Variance.

**8. Inferences from Two Samples. **

Inferences about Two Means: Independent and Large Samples.

Inferences about Two Means: Matched Pairs.

Inferences about Two Proportions.

Comparing Variation in Two Samples.

Inferences about Two Means: Independent and Small Samples.

**9. Correlation and Regression. **

Correlation.

Regression.

Variation and Prediction Intervals.

Multiple Regression.

Modeling.

**10. Multinomial Experiments and Contingency Tables. **

Multinomial Experiments: Goodness-Of-Fit.

Contingency Tables: Independence and Homogeneity.

**11. Analysis of Variance. **

Overview.

One-Way ANOVA.

Two-Way ANOVA.

**12. Statistical Process Control. **

Overview.

Control Charts for Variation and Mean.

Control Charts for Attributes.

**13. Nonparametric Statistics. **

Sign Test.

Wilcoxon Signed-Ranks Test for Matched Pairs.

Wilcoxon Rank-Sum Test for Two Independent Samples.

Kruskal-Wallis Test.

Rank Correlation.

Runs Test for Randomness.

**14. Projects, Procedures, Perspectives. **

A Statistics Group Project.

Which Procedure Applies?

A Perspective.

**Appendices. **

Appendix B: Data Sets.

Appendix C: TI-83 Plus Reference.

Appendix D: Glossary.

Appendix E: Bibliography.

Appendix F: Answers to Odd-Numbered Exercises (and All ReviewExercises and All Cumulative Review Exercises)

Publisher Info

Publisher: Addison-Wesley Longman, Inc.

Published: 2001

International: No

Published: 2001

International: No

**Triola, Mario F.: Dutchess Community College**

**1. Introduction to Statistics. **

Overview.

The Nature of Data.

Uses and Abuses of Statistics.

Design of Experiments.

**2. Describing, Exploring, and Comparing Data. **

Summarizing Data with Frequency Tables.

Pictures of Data.

Measures of Center.

Measures of Variation.

Measures of Position.

Exploratory Data Analysis (EDA).

**3. Probability. **

Fundamentals.

Addition Rule.

Multiplication Rule: Basics.

Multiplication Rule: Complements and Conditional Probability.

Probabilities Through Simulations.

Counting.

**4. Probability Distributions. **

Random Variables.

Binomial Probability Distributions.

Mean, Variance, and Standard Deviation for the BinomialDistribution.

The Poisson Distribution.

**5. Normal Probability Distributions. **

The Standard Normal Distribution.

Nonstandard Normal Distributions: Finding Probabilities.

Nonstandard Normal Distributions: Finding Values.

The Central Limit Theorem.

Normal Distribution as Approximation to Binomial Distribution.

Determining Normality.

**6. Estimates and Sample Sizes. **

Estimating a Population Mean: Large Samples.

Estimating a Population Mean: Small Samples.

Determining Sample Size.

Estimating a Population Proportion.

Estimating a Population Variance.

**7. Hypothesis Testing. **

Fundamentals of Hypothesis Testing.

Testing a Claim about a Mean: Large Samples.

Testing a Claim about a Mean: Small Samples.

Testing a Claim about a Proportion.

Testing a Claim about a Standard Deviation or Variance.

**8. Inferences from Two Samples. **

Inferences about Two Means: Independent and Large Samples.

Inferences about Two Means: Matched Pairs.

Inferences about Two Proportions.

Comparing Variation in Two Samples.

Inferences about Two Means: Independent and Small Samples.

**9. Correlation and Regression. **

Correlation.

Regression.

Variation and Prediction Intervals.

Multiple Regression.

Modeling.

**10. Multinomial Experiments and Contingency Tables. **

Multinomial Experiments: Goodness-Of-Fit.

Contingency Tables: Independence and Homogeneity.

**11. Analysis of Variance. **

Overview.

One-Way ANOVA.

Two-Way ANOVA.

**12. Statistical Process Control. **

Overview.

Control Charts for Variation and Mean.

Control Charts for Attributes.

**13. Nonparametric Statistics. **

Sign Test.

Wilcoxon Signed-Ranks Test for Matched Pairs.

Wilcoxon Rank-Sum Test for Two Independent Samples.

Kruskal-Wallis Test.

Rank Correlation.

Runs Test for Randomness.

**14. Projects, Procedures, Perspectives. **

A Statistics Group Project.

Which Procedure Applies?

A Perspective.

**Appendices. **

Appendix B: Data Sets.

Appendix C: TI-83 Plus Reference.

Appendix D: Glossary.

Appendix E: Bibliography.

Appendix F: Answers to Odd-Numbered Exercises (and All ReviewExercises and All Cumulative Review Exercises)