Introductory Statistics / Edition 4by Neil A. Weiss
This book/CD-ROM package is intended for a one- or two-semester course for students who have had a high school algebra course. This sixth edition offers more emphasis on conceptual understanding and less emphasis on computation. Parallel presentations of the critical-value and P-value approaches to hypothesis testing are provided in this edition, to allow for/i>… See more details below
This book/CD-ROM package is intended for a one- or two-semester course for students who have had a high school algebra course. This sixth edition offers more emphasis on conceptual understanding and less emphasis on computation. Parallel presentations of the critical-value and P-value approaches to hypothesis testing are provided in this edition, to allow for independent coverage. Coverage of statistical technology has been expanded to include Minitab, Excel, and TI-83 Plus. Technology sections are integrated as optional subsections. The CD-ROM, new to this edition, contains some 600 exercises, data sets from the book in several electronic formats, three modular chapters, an Excel add-in, and Adobe Acrobat Reader. The author is affiliated with Arizona State University. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Table of Contents
(*indicates an optional section).
Two Kinds of Statistics.
The Technology Center.
Simple Random Sampling.
Other Sampling Designs.
II. DESCRIPTIVE STATISTICS.
Variables and Data.
Graphs and Charts.
Distribution Shapes; Symmetry and Skewness.
3. Descriptive Measures.
Measures of Center.
The Sample Mean.
Measures of Variation; the Sample Standard Deviation.
The Five-Number Summary; Boxplots.
Descriptive Measures for Populations; Use of Samples.
III. PROBABILITY, RANDOM VARIABLES, AND SAMPLING DISTRIBUTIONS.
Some Rules of Probability.
*Contingency Tables; Joint and Marginal Probabilities.
*The Multiplication Rule; Independence.
5. Discrete Random Variables.
*Discrete Random Variables and Probability Distributions.
*The Mean and Standard Deviation of a Discrete Random Variable.
*The Binomial Distribution.
*The Poisson Distribution.
6. The Normal Distribution.
Introducing Normally Distributed Variables.
Areas Under the Standard Normal Curve.
Working With Normally Distributed Variables.
Assessing Normality; Normal Probability Plots.
*Normal Approximation to the Binomial Distribution .
7. The Sampling Distribution of the Sample Mean.
Sampling Error; the Need for Sampling Distributions.
The Mean and Standard Deviation of x.
The Sampling Distribution of the Sample Mean.
IV. INFERENTIAL STATISTICS.
Estimating a Population Mean.
Confidence Intervals for One Population Mean When s Is Known.
Margin of Error.
Confidence Intervals for One Population Mean When s Is Unknown.
9. Hypothesis Tests for One Population Mean.
The Nature of Hypothesis Testing.
Terms, Errors, and Hypotheses.
Hypothesis Tests for One Population Mean When s Is Known.
*Type II Error Probabilities; Power.
Hypothesis Tests for One Population Mean When s Is Unknown.
*The Wilcoxon Signed-Rank Test.
*Which Procedure Should Be Used?
10. Inferences for Two Population Means.
The Sampling Distribution of the Difference Between Two Sample Means for Independent Samples.
Inferences for Two Population Means Using Independent Samples: Standard Deviations Assumed Equal.
Inferences for Two Population Means Using Independent Samples: Standard Deviations Not Assumed Equal.
*The Mann-Whitney Test.
Inferences for Two Population Means Using Paired Samples.
*The Paired Wilcoxon Signed-Rank Test.
*Which Procedure Should Be Used?
11. Inferences for Population Standard Deviations.
*Inferences for One Population Standard Deviation.
*Inferences for Two Population Standard Deviations Using Independent Samples.
12. Inferences for Population Proportions.
Confidence Intervals for One Population Proportion.
Hypothesis Tests for One Population Proportion.
Inferences for Two Population Proportions Using Independent Samples.
13. Chi-Square Procedures.
The Chi-Square Distribution.
Chi-Square Goodness-Of-Fit Test.
Contingency Tables; Association.
Chi-Square Independence Test.
V. REGRESSION, CORRELATION, AND ANOVA.
Linear Equations With One Independent Variable.
The Regression Equation.
The Coefficient of Determination.
15. Inferential Methods in Regression and Correlation.
The Regression Model; Analysis of Residuals.
Inferences for the Slope of the Population Regression Line.
Estimation and Prediction.
Inferences in Correlation.
*Testing for Normality.
16. Analysis of Variance (Anova).
One-Way ANOVA: The Logic.
One-Way ANOVA: The Procedure.
*The Kruskal-Wallis Test.
VI. MULTIPLE REGRESSION AND MODEL BUILDING; EXPERIMENTAL DESIGN AND ANOVA (On Weiss Stats CD).
Estimation of the Regression Parameters.
Inferences Concerning the Utility of the Regression Model.
Inferences Concerning the Utility of Particular Predictor Variables.
Confidence Intervals for Mean Response; Prediction.
Intervals for Response.
Checking Model Assumptions and Residual Analysis.
Module B. Model Building in Regression.
Polynomial Regression Model.
Qualitative Predictor Variables.
Model Selection: Stepwise Regression.
Model Selection: All Subsets Regression.
Pitfalls and Warnings.
Module C. Design Of Experiments and Analysis of Variance.
Two-Way ANOVA: The Logic.
Two-Way ANOVA: The Procedure.
Two-Way ANOVA: Multiple Comparisons.
Randomized Block Designs.
Randomized Block ANOVA: The Logic.
Randomized Block ANOVA: The Procedure.
Randomized Block ANOVA: Multiple Comparisons.
*Friedman's Nonparametric Test for the Randomized Block Design.
Appendix B. Answers To Selected Exercises.
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