Statistics For Dummies

Deborah J. Rumsey, PhD, is Professor of Statistics and Statistics Education Specialist at The Ohio State University. She is the author of Statistics Workbook For Dummies, Statistics II For Dummies, and Probability For Dummies.

Introduction 1 About This Book 1 Conventions Used in This Book 2 What Youre Not to Read 3 Foolish Assumptions 3 How This Book Is Organized 3 Part 1: Vital Statistics about Statistics 3 Part 2: Number-Crunching Basics 4 Part 3: Distributions and the Central Limit Theorem 4 Part 4: Guesstimating and Hypothesizing with Confidence 4 Part 5: Statistical Studies and the Hunt for a Meaningful Relationship 5 Part 6: The Part of Tens 5 Icons Used in This Book 6 Where to Go from Here 6 Part 1: Vital Statistics About Statistics 7 Chapter 1: Statistics in a Nutshell 9 Thriving in a Statistical World 10 Designing Appropriate Studies 11 Surveys 11 Experiments 12 Collecting Quality Data 13 Selecting a good sample 13 Avoiding bias in your data 14 Creating Effective Summaries 14 Descriptive statistics 15 Charts and graphs 15 Determining Distributions 16 Performing Proper Analyses 17 Margin of error and confidence intervals 18 Hypothesis tests 19 Correlation, regression, and two-way tables 20 Drawing Credible Conclusions 21 Reeling in overstated results 21 Questioning claims of cause and effect 21 Becoming a Sleuth, Not a Skeptic 22 Chapter 2: The Statistics of Everyday Life 23 Statistics and the Media: More Questions than Answers? 24 Probing popcorn problems 24 Venturing into viruses 24 Comprehending crashes 25 Mulling malpractice 26 Belaboring the loss of land 26 Scrutinizing schools 27 Studying sports 28 Banking on business news 28 Touring the travel news 29 Surveying sexual stats 29 Breaking down weather reports 30 Musing about movies 30 Highlighting horoscopes 31 Using Statistics at Work 31 Delivering babies and information 31 Posing for pictures 32 Poking through pizza data 32 Statistics in the office 33 Chapter 3: Taking Control: So Many Numbers, So Little Time 35 Detecting Errors, Exaggerations, and Just Plain Lies 36 Checking the math 36 Uncovering misleading statistics 37 Looking for lies in all the right places 44 Feeling the Impact of Misleading Statistics 44 Chapter 4: Tools of the Trade 47 Statistics: More than Just Numbers 47 Grabbing Some Basic Statistical Jargon 49 Data 50 Data set 51 Variable 51 Population 51 Sample, random, or otherwise 52 Statistic 54 Parameter 54 Bias 55 Mean (Average) 55 Median 56 Standard deviation 56 Percentile 57 Standard score 57 Distribution and normal distribution 58 Central Limit Theorem 59 z-values 60 Experiments 60 Surveys (Polls) 62 Margin of error 62 Confidence interval 63 Hypothesis testing 64 p-values 65 Statistical significance 66 Correlation versus causation 67 Part 2: Number-Crunching Basics 69 Chapter 5: Means, Medians, and More 71 Summing Up Data with Descriptive Statistics 71 Crunching Categorical Data: Tables and Percents 72 Measuring the Center with Mean and Median 75 Averaging out to the mean 75 Splitting your data down the median 77 Comparing means and medians: Histograms 78 Accounting for Variation 80 Reporting the standard deviation 81 Being out of range 84 Examining the Empirical Rule (68-95-99.7) 85 Measuring Relative Standing with Percentiles 87 Calculating percentiles 88 Interpreting percentiles 89 Gathering a five-number summary 93 Exploring interquartile range 94 Chapter 6: Getting the Picture: Graphing Categorical Data 95 Take Another Little Piece of My Pie Chart 96 Tallying personal expenses 96 Bringing in a lotto revenue 97 Ordering takeout 98 Projecting age trends 99 Raising the Bar on Bar Graphs 101 Tracking transportation expenses 101 Making a lotto profit 103 Tipping the scales on a bar graph 104 Pondering pet peeves 105 Chapter 7: Going by the Numbers: Graphing Numerical Data 107 Handling Histograms 108 Making a histogram 108 Interpreting a histogram 111 Putting numbers with pictures 115 Detecting misleading histograms 117