Statistics

(cover)
Preface
Applications Index
CHAPTER 1: Statistics, Data, and Statistical Thinking
	Chapter Opener
	1.1 The Science of Statistics
	1.2 Types of Statistical Applications
	1.3 Fundamental Elements of Statistics
	1.4 Types of Data
	1.5 Collecting Data
	1.6 The Role of Statistics in Critical Thinking and Ethics
	Statistics in Action: Social Media Networks and the Millennial Generation
	Using Technology: Accessing and Listing Data
CHAPTER 2: Methods for Describing Sets of Data
	Chapter Opener
	2.1 Describing Qualitative Data
	2.2 Graphical Methods for Describing Quantitative Data
	2.3 Summation Notation
	2.4 Numerical Measures of Central Tendency
	2.5 Numerical Measures of Variability
	2.6 Interpreting the Standard Deviation
	2.7 Numerical Measures of Relative Standing
	2.8 Methods for Detecting Outliers: Box Plots and z-Scores
	2.9 Graphing Bivariate Relationships (Optional)
	2.10 Distorting the Truth with Descriptive Statistics
	Statistics in Action: Body Image Dissatisfaction: Real or Imagined?
	Using Technology: Describing Data
CHAPTER 3: Probability
	Chapter Opener
	3.1 Events, Sample Spaces, and Probability
	3.2 Unions and Intersections
	3.3 Complementary Events
	3.4 The Additive Rule and Mutually Exclusive Events
	3.5 Conditional Probability
	3.6 The Multiplicative Rule and Independent Events
	3.7 Random Sampling
	3.8 Some Additional Counting Rules (Optional)
	3.9 Bayesˇs Rule (Optional)
	Statistics in Action: Lotto Buster! Can You Improve Your Chance of Winning?
	Using Technology: Generating a Random Sample; Combinations and Permutations
CHAPTER 4: Discrete Random Variables
	Chapter Opener
	4.1 Two Types of Random Variables
	4.2 Probability Distributions for Discrete Random Variables
	4.3 Expected Values of Discrete Random Variables
	4.4 The Binomial Random Variable
	4.5 The Poisson Random Variable (Optional)
	4.6 The Hypergeometric Random Variable (Optional)
	Statistics in Action: Probability in a Reverse Cocaine Sting: Was Cocaine Really Sold?
	Using Technology: Discrete Random Variables and Probabilities
CHAPTER 5: Continuous Random Variables
	Chapter Opener
	5.1 Continuous Probability Distributions
	5.2 The Uniform Distribution
	5.3 The Normal Distribution
	5.4 Descriptive Methods for Assessing Normality
	5.5 Approximating a Binomial Distribution with a Normal Distribution (Optional)
	5.6 The Exponential Distribution (Optional)
	Statistics in Action: Super Weapons DevelopmentIs the Hit Ratio Optimized?
	Using Technology: Continuous Random Variables, Probabilities, and Normal Probability Plots
CHAPTER 6: Sampling Distributions
	Chapter Opener
	6.1 The Concept of a Sampling Distribution
	6.2 Properties of Sampling Distributions: Unbiasedness and Minimum Variance
	6.3 The Sampling Distribution of x¯ and the Central Limit Theorem
	Statistics in Action: The Insomnia Pill: Is It Effective?
	Using Technology: Simulating a Sampling Distribution
CHAPTER 7: Inferences Based on a Single Sample: Estimation with Confidence Intervals
	Chapter Opener
	7.1 Identifying and Estimating the Target Parameter
	7.2 Confidence Interval for a Population Mean: Normal (z) Statistic
	7.3 Confidence Interval for a Population Mean: Studentˇs t-Statistic
	7.4 Large-Sample Confidence Interval for a Population Proportion
	7.5 Determining the Sample Size
	7.6 Confidence Interval for a Population Variance (Optional)
	Statistics in Action: Medicare Fraud Investigations
	Using Technology: Confidence Intervals
CHAPTER 8: Inferences Based on a Single Sample: Tests of Hypothesis
	Chapter Opener
	8.1 The Elements of a Test of Hypothesis
	8.2 Formulating Hypotheses and Setting Up the Rejection Region
	8.3 Test of Hypothesis about a Population Mean: Normal (z) Statistic
	8.4 Observed Significance Levels: p-Values
	8.5 Test of Hypothesis about a Population Mean: Studentˇs t-Statistic
	8.6 Large-Sample Test of Hypothesis about a Population Proportion
	8.7 Calculating Type II Error Probabilities: More about ² (Optional)
	8.8 Test of Hypothesis about a Population Variance (Optional)
	Statistics in Action: Diary of a KLEENEX® UserHow Many Tissues in a Box?
	Using Technology: Tests of Hypotheses
CHAPTER 9: Inferences Based on a Two Samples: Confidence Intervals and Tests of Hypotheses
	Chapter Opener
	9.1 Identifying the Target Parameter
	9.2 Comparing Two Population Means: Independent Sampling
	9.3 Comparing Two Population Means: Paired Difference Experiments
	9.4 Comparing Two Population Proportions: Independent Sampling
	9.5 Determining the Sample Size
	9.6 Comparing Two Population Variances: Independent Sampling (Optional)
	Statistics in Action: ZixIt Corp. v. Visa USA Inc.A Libel Case
	Using Technology: Two-Sample Inferences
CHAPTER 10: Analysis of Variance: Comparing More than Two Means
	Chapter Opener
	10.1 Elements of a Designed Study
	10.2 The Completely Randomized Design: Single Factor
	10.3 Multiple Comparisons of Means
	10.4 The Randomized Block Design
	10.5 Factorial Experiments: Two Factors
	Statistics in Action: On the Trail of the Cockroach: Do Roaches Travel at Random?
	Using Technology: Analysis of Variance
CHAPTER 11: Simple Linear Regression
	Chapter Opener
	11.1 Probabilistic Models
	11.2 Fitting the Model: The Least Squares Approach
	11.3 Model Assumptions
	11.4 Assessing the Utility of the Model: Making Inferences about the Slope ß1
	11.5 The Coefficients of Correlation and Determination
	11.6 Using the Model for Estimation and Prediction
	11.7 A Complete Example
	Statistics in Action: Can Dowsers Really Detect Water?
	Using Technology: Simple Linear Regression
CHAPTER 12: Multiple Regression and Model Building
	Chapter Opener
	12.1 Multiple-Regression Models
	PART I: First-Order Models with Quantitative Independent Variables
	12.2 Estimating and Making Inferences about the ß Parameters
	12.3 Evaluating Overall Model Utility
	12.4 Using the Model for Estimation and Prediction
	PART II: Model Building in Multiple Regression
	12.5 Interaction Models
	12.6 Quadratic and Other Higher Order Models
	12.7 Qualitative (Dummy) Variable Models
	12.8 Models with Both Quantitative and Qualitative Variables (Optional)
	12.9 Comparing Nested Models (Optional)
	12.10 Stepwise Regression (Optional)
	PART III: Multiple Regression Diagnostics
	12.11 Residual Analysis: Checking the Regression Assumptions
	12.12 Some Pitfalls: Estimability, Multicollinearity, and Extrapolation
	Statistics in Action: Modeling Condominium Sales: What Factors Affect Auction Price?
	Using Technology: Multiple Regression
CHAPTER 13: Categorical Data Analysis
	Chapter Opener
	13.1 Categorical Data and the Multinomial Experiment
	13.2 Testing Categorical Probabilities: One-Way Table
	13.3 Testing Categorical Probabilities: Two-Way (Contingency) Table
	13.4 A Word of Caution about Chi-Square Tests
	Statistics in Action: College Students and Alcohol: Is Amount Consumed Related to Drinking Frequency?
	Using Technology: Chi-Square Analyses
CHAPTER 14: Nonparametric Statistics (available on CD)
	Chapter Opener
	14.1 Introduction: Distribution-Free Tests
	14.2 Single-Population Inferences
	14.3 Comparing Two Populations: Independent Samples
	14.4 Comparing Two Populations: Paired Difference Experiment
	14.5 Comparing Three or More Populations: Completely Randomized Design
	14.6 Comparing Three or More Populations: Randomized Block Design
	14.7 Rank Correlation
	Statistics in Action: How Vulnerable Are New Hampshire Wells to Groundwater Contamination?
	Using Technology: Nonparametric Tests
Appendices
	Appendix A: Tables
		Table I Random Numbers
		Table II Binomial Probabilities
		Table III Poisson Probabilities
		Table IV Normal Curve Areas
		Table V Exponentials
		Table VI Critical Values of t
		Table VII Critical Values of Ç2
		Table VIII Percentage Points of the F-Distribution, ± = .10
		Table IX Percentage Points of the F-Distribution, ± = .05
		Table X Percentage Points of the F-Distribution, ± = .025
		Table XI Percentage Points of the F-Distribution, ± = .01
		Table XII Critical Values of TL and TU for the Wilcoxon Rank Sum Test: Independent Samples
		Table XIII Critical Values of To in the Wilcoxon Paired Difference Signed Rank Test
		Table XIV Critical Values of Spearmanˇs Rank Correlation Coefficient
		Table XV Critical Values of the Studentized Range, ± = 0.5
		Table XVI Critical Values of the Studentized Range, ± = 0.1
	Appendix B Calculation Formulas for Analysis of Variance
Short Answers to Selected Odd Exercises
Index
Photo Credits