Statistics / With CD-ROM

For courses in Statistics.

This introduction to statistics presents balanced coverage of both the theory and application of statistics and at the same time helps students develop and enhance their critical thinking skills. It shows students how to analyze data that appear in situations in the world around them and features an abundance of examples and exercises -- nearly all based on current, real-world applications pulled from journals, magazines, news articles, and commerce.

Features

• NEW -- Three types of Applying the Concepts exercise sets -- Contains simple word problems based on real data; typical word problems based on real data encountered in the real world; and more advanced problems requiring a higher level of statistical thinking.
  • Challenges students at different levels of understanding and application.
• NEW -- Updated statistical software printouts -- i.e., SAS, SPSS, MINITAB, STATISTIX, and the TI graphing calculator. Reflects the latest editions of the software.
  • Exposes students to more statistical packages than any other book or the market, and allows them to spend time analyzing data results -- which will prove helpful in future classes and on the job.
• NEW -- Updated exercises -- 20% revised.
  • Provides instructors with a greater variety of exercise choices, allowing flexibility in matching exercise difficulty and focus to their course emphasis and their students' needs, interests, and abilities.
• NEW -- Added introductory sections on "categorical data" and multinomial distribution, and "distribution-free tests."
• NEW -- Technology Manuals.
• Manuals for MINITAB, Excel, and the TI graphing calculator can be packaged to the text for no additional charge.
• Over 1200 exercises -- Divided into two types: "Learning the Mechanics" and "Applying the Concepts."
• Gives students the opportunity to test their mastery of definitions, concepts, and basic computation, and apply statistical techniques in solving real world problems.
• "Statistics in Action" case studies incorporated throughout -- Concluding each chapter, each case revolves around a controversial, contemporary issue and is followed by problems using real data.
  • Motivates students' interest in the subject, and guides them in evaluating findings of recent, published studies.
• Student projects -- Provides a challenging means for further exploration of the material by an individual student or a group of students.
  • Gives students good practice gathering and analyzing data and building report-writing skills that will be important in future classes and the workplace.
• Comprehensive, chapter-end reviews -- Provides key terms and formulas; a language lab that helps students learn the language of statistics through pronunciation guides, descriptions of symbols, names, etc.; and supplementary exercises that review all of the important topics covered in the chapter.
  • Presents students with an all-in-one-place resource for quick review during study and exam prep time.
• TI-83 graphing calculator application boxes.
  • Provides detailed instructions for students on how to use the TI-83 graphing calculator.
• Emphasis on ethical issues in statistics.
  • Ensures that students become aware of and think critically about the potential uses and abuses of statistics.
• A choice in level of coverage of Probability.
  • Enables instructors to be flexible in meeting their course needs and student abilities.

1. Statistics, Data, and Statistical Thinking.
The Science of Statistics. Types of Statistical Applications. Fundamental Elements of Statistics. Types of Data. Collecting Data. The Role of Statistics in Critical Thinking.
2. Methods for Describing Sets of Data.
Describing Qualitative Data. Graphical Methods for Describing Quantitative Data. Summation Notation. Numerical Measures of Central Tendency. Numerical Measures of Variability. Interpreting the Standard Deviation. Numerical Measures of Relative Standing. Methods for Detecting Outliers (Optional). Graphing Bivariate Relationships (Optional). Distorting the Truth with Descriptive Techniques.
3. Probability.
Events, Sample Spaces, and Probability. Unions and Intersections. Complementary Events. The Additive Rule and Mutually Exclusive Events. Conditional Probability. The Multiplicative Rule and Independent Events. Random Sampling. Some Counting Rules (Optional).
4. Discrete Random Variables.
Two Types of Random Variables. Probability Distributions for Discrete Random Variables. Expected Values of Discrete Random Variables. The Binomial Random Variable. The Poisson Random Variable (Optional). The Hypergeometric Random Variable (Optional).
5. Continuous Random Variables.
Continuous Probability Distributions. The Uniform Distribution. The Normal Distribution. Descriptive Methods for Assessing Normality. Approximating a Binomial Distribution with a Normal Distribution (Optional). The Exponential Distribution (Optional).
6. Sampling Distributions.
What Is a Sampling Distribution? Properties of Sampling Distributions: Unbiasedness and Minimum Variance (Optional). The Central Limit Theorem.
7. Inferences Based on a Single Sample: Estimation with Confidence Intervals.
Large-Sample Confidence Interval for a Population Mean. Small-Sample Confidence Interval for a Population Mean. Large-Sample Confidence Interval for a Population Proportion. Determining the Sample Size.
8. Inferences Based on a Single Sample: Tests of Hypotheses.
The Elements of a Test of Hypothesis. Large-Sample Test of Hypothesis about a Population Mean. Observed Significance Levels: p-Values. Small-Sample Test of Hypothesis about a Population Mean. Large-Sample Test of Hypothesis about a Population Proportion. Calculating Type II Error Probabilities: More about …b (Optional). Test of Hypothesis about a Population Proportion.
9. Inferences Based on Two Samples: Confidence Intervals and Tests of Hypotheses.
Comparing Two Population Means: Independent Sampling. Comparing Two Population Means: Paired Difference Experiments. Comparing Two Population Proportions: Independent Sampling. Determining the Sample Size. Comparing Two Population Variances: Independent Sampling (Optional).
10. Analysis of Variance: Comparing More Than Two Means.
Elements of a Designed Experiment. The Completely Randomized Design. Multiple Comparisons of Means. The Randomized Block Design. Factorial Experiments.
11. Simple Linear Regression.
Probabalistic Models. Fitting the Model: The Least Squares Approach. Model Assumptions. An Estimator of …s2. Assessing the Utility of the Model: Making Inferences about the Slope …b1. The Coefficient of Correlation. The Coefficient of Determination. Using the Model for Estimation and Prediction. A Complete Example.
12. Multiple Regression and Model Building.
Multiple Regression Models. The First-Order Model: Estimating and Interpreting the …b Parameters. Model Assumptions. Inferences About the Individual …b Parameters. Checking the Overall Utility of a Model. Using the Model for Estimation and Prediction. Model Building: Interaction Models. Model Building: Quadratic and Other Higher-Order Models. Model Building: Qualitative (Dummy) Variable Models. Model Building: Models with Both Quantitative and Qualitative Variables. Model Building: Comparing Nested Models. Model Building: Stepwise Regression. Residual Analysis: Checking the Regression Assumptions. Some Pitfalls: Estimability, Multicollinearity, and Extrapolation.
13. Categorical Data Analysis.
Categorical Data and the Multinomial Distribution. Testing Categorical Probabilities: One-Way Table. Testing Categorical Probabilities: Two-Way (Contingency) Table. A Word of Caution about Chi-Square Tests.
14. Nonparametric Statistics.
Introduction: Distribution-Free Tests. Single Population Inferences: The Sign Test. Comparing Two Populations: The Wilcoxon Rank Sum Test for Independent Samples. Comparing Two Populations: The Wilcoxon Signed Rank Test for the Paired Difference Experiment. The Kruskal-Wallis H-Test for a Completely Randomized Design. The Friedman Fr-Test for a Randomized Block Design. Spearman's Rank Correlation Coefficient.

Appendix A. Tables.
Random Numbers. Binomial Probabilities. Poisson Probabilities. Normal Curve Areas. Exponentials. Critical Values of t. Critical Values of …c2. Percentage Points of the F Distribution, …a= .10. Percentage Points of the F Distribution, …a=.05. Percentage Points of the F Distribution, …a=.025. Percentage Points of the F Distribution, …a=.01. Critical Values of TL and TU for the Wilcoxon Rank Sum Test: Independent Samples. Critical Values of TO in the Wilcoxon Paired Difference Signed Rank Test. Critical Values of Spearman's Rank Correlation Coefficient.
Appendix B. Data Sets.
Coronary Artery Patients' Blood Loss Data. Car & Driver Data. Starting Salaries of USF Graduates. Sealed Milk Bids Data. Federal Trade Commission Rankings of Domestic Cigarette Brands.
Appendix C. Calculation Formulas for Analysis of Variance.
Short Answers to Selected Odd-Numbered Exercises.
Index.