Introduction 1 About This Book 1 Foolish Assumptions 3 Icons Used in This Book 3 Beyond the Book 4 Where to Go from Here 4 Part 1: Tackling Data Analysis and Model-Building Basics 7 Chapter 1: Beyond Number Crunching: The Art and Science of Data Analysis 9 Data Analysis: Looking before You Crunch 9 Nothing (not even a straight line) lasts forever 10 Data snooping isn''t cool 11 No (data) fishing allowed 12 Getting the Big Picture: An Overview of Stats II 13 Population parameter 13 Sample statistic 13 Confidence interval 14 Hypothesis test 14 Analysis of variance (ANOVA) 15 Multiple comparisons 15 Interaction effects 16 Correlation 16 Linear regression 17 Chi-square tests 18 Chapter 2: Finding the Right Analysis for the Job 21 Categorical versus Quantitative Variables 22 Statistics for Categorical Variables 23 Estimating a proportion 23 Comparing proportions 24 Looking for relationships between categorical variables 25 Building models to make predictions 26 Statistics for Quantitative Variables 27 Making estimates 27 Making comparisons 28 Exploring relationships 28 Predicting y using x 30 Avoiding Bias 31 Measuring Precision with Margin of Error 33 Knowing Your Limitations 35 Chapter 3: Having the Normal and Sampling Distributions in Your Back Pocket 37 Recognizing the VIP Distribution -- the Normal 38 Characterizing the normal 38 Standardizing to the standard normal (Z-) distribution 38 Using the normal table 40 Finding probabilities for the normal distribution 41 Finally Getting Comfortable with Sampling Distributions 42 The mean and standard error of a sampling distribution 42 Sampling distribution of X 43 Sampling distribution of ^ p 44 Heads Up! Building Confidence Intervals and Hypothesis Tests 45 Confidence interval for the population mean 45 Confidence interval for the population proportion 46 Hypothesis test for population mean 46 Hypothesis test for the population proportion 47 Chapter 4: Reviewing Confidence Intervals and Hypothesis Tests 49 Estimating Parameters by Using Confidence Intervals 50 Getting the basics: The general form of a confidence interval 50 Finding the confidence interval for a population mean 51 What changes the margin of error? 52 Interpreting a confidence interval 55 What''s the Hype about Hypothesis Tests? 56 What Ho and Ha really represent 56 Gathering your evidence into a test statistic 57 Determining strength of evidence with a p-value 57 False alarms and missed opportunities: Type I and II errors 58 The power of a hypothesis test 60 Part 2: Using Different Types of Regression to Make Predictions 65 Chapter 5: Getting in Line with Simple Linear Regression 67 Exploring Relationships with Scatterplots and Correlations 68 Using scatterplots to explore relationships 69 Collating the information by using the correlation coefficient 70 Building a Simple Linear Regression Model 71 Finding the best-fitting line to model your data 72 The y-intercept of the regression line 73 The slope of the regression line 74 Making point estimates by using the regression line 75 No Conclusion Left Behind: Tests and Confidence Intervals for Regression 75 Scrutinizing the slope 76 Inspecting the y-intercept 78 Building confidence intervals for the average response 80 Making the band with prediction intervals 81 Checking the Model''s Fit (The Data, Not the Clothes!) 83 Defining the conditions 84 Finding and exploring the residuals 85 Using r2 to measure model fit 89 Scoping for outliers 90 Knowing the Limitations of Your Regression Analysis 92 Avoiding slipping into cause-and-effect mode 92 Extrapolation: The ultimate no-no 93 Sometimes you need more than one variable 94 Chapter 6: Multiple Regression with Two X Variables 95 Getting to Know the Multiple Regression Model 96 Discovering the uses of multiple regression 96 Looking at the general form of the multiple regression model 96 Stepping through the analysis 97 Looking at x''s and y''s 97 Collecting the Data 98 Pinpointing Possible Relationships 100 Making scatterplots 100 Correlations: Examining the bond 101 Checking for Multicolinearity 104 Finding the Best-Fitting Model for Two x Variables 105 Getting the multiple regression coefficients 106 Interpreting the coefficients 107 Testing the coefficients 108 Predicting y by Using the x Variables 110 Checking the Fit of the Multiple Regression Model 111 Noting the conditions 112 Plotting a plan to check the conditions 112 Checking the three conditions 114 Chapter 7: How Can I Miss You If You Won''t Leave? Regression Model Selection 117 Getting a Kick out of Estimating Punt Distance 118 Brainstorming variables and collecting data 118 Examining scatterplots and correlations 120 Just Like Buying Shoes: The Model Looks Nice, But Does It Fit? 123 Assessing the fit of multiple regression models 124 Model selection procedures 125 Chapter 8: Getting Ahead of the Learning Curve with Nonlinear Regression 129 Anticipating Nonlinear Regression 130 Starting Out with Scatterplots 131 Handling Curves in the Road with Polynomials 133 Bringing back polynomials 134 Searching for the best polynomial model 136 Using a second-degree polynomial to pass the quiz 138 Assessing the fit of a polynomial model 141 Making predictions 143 Going Up? Going Down? Go Exponential! 145 Recollecting exponential models 145 Searching for the best exponential model 146 Spreading secrets at an exponential rate 148 Chapter 9: Yes, No, Maybe So: Making Predictions by Using Logistic Regression 153 Understanding a Logistic Regression Model 154 How is logistic regression different from other regressions? 154 Using an S-curve to estimate probabilities 155 Interpreting the coefficients of the logistic regression model 156 The logistic regression model in action 157 Carrying Out a Logistic Regression Analysis 158 Running the analysis in Minitab 158 Finding the coefficients and making the model 160 Estimating p 161 Checking the fit of the model 162 Fitting the movie model 162 Part 3: Analyzing Variance with Anova 167 Chapter 10: Testing Lots of Means? Come On Over to ANOVA! 169 Comparing Two Means with a t-Test 170 Evaluating More Means with ANOVA 171 Spitting seeds: A situation just waiting for ANOVA 172 Walking through the steps of ANOVA 173 Checking the Conditions 174 Verifying independence 174 Looking for what''s normal 174 Taking note of spread 176 Setting Up the Hypotheses 178 Doing the F-Test 179 Running ANOVA in Minitab 180 Breaking down the variance into sums of squares 180 Locating those mean sums of squares 182 Figuring the F-statistic 183 Making conclusions from ANOVA 184 What''s next? 186 Checking the Fit of the ANOVA Model 186 Chapter 11: Sorting Out the Means with Multiple Comparisons 189 Following Up after ANOVA 190 Comparing cellphone minutes: An example 190 Setting the stage for multiple comparison procedures 192 Pinpointing Differing Means with Fisher and Tukey .193 Fishing for differences with Fisher''s LSD 194 Separating the turkeys with Tukey''s test 197 Examining the Output to Determine the Analysis 198 So Many Other Procedures, So Little Time! 199 Controlling for baloney with the Bonferroni adjustment 200 Comparing combinations by using Scheffé''s method 201 Finding out whodunit with Dunnett''s test 202 Staying cool with Student Newman-Keuls 202 Duncan''s multiple range test 202 Chapter 12: Finding Your Way through Two-Way ANOVA 205 Setting Up the Two-Way ANOVA Model 206 Determining the treatments 206 Stepping through the sums of squares 207 Understanding Interaction Effects 209 What is interaction, anyway? 209 Interacting with interaction plots 210 Testing the Terms in Two-Way ANOVA .213 Running the Two-Way ANOVA Table 214 Interpreting the results: Numbers and graphs 214 Are Whites Whiter in Hot Water? Two-Way ANOVA Investigates 217 Chapter 13: Regression and ANOVA: Surprise Relatives! 221 Seeing Regression through the Eyes of Variation 222 Spotting variability and finding an "x-planation" 222 Getting results with regression 223 Assessing the fit of the regression model 225 Regression and ANOVA: A Meeting of the Models 226 Comparing sums of squares 226 Dividing up the degrees of freedom 228 Bringing regression to the ANOVA table 229 Relating the F- and t-statistics: The final frontier 230 Part 4: Building Strong Connections with Chi-Square T.