Description

Book Synopsis
Statistics For Dummies, 2nd Edition (9781119293521) was previously published as Statistics For Dummies, 2nd Edition (9780470911082). While this version features a new Dummies cover and design, the content is the same as the prior release and should not be considered a new or updated product.

Table of Contents

Introduction 1

About This Book 1

Conventions Used in This Book 2

What You’re 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

Examining Boxplots 120

Making a boxplot 120

Interpreting a boxplot 121

Tackling Time Charts 127

Interpreting time charts 127

Understanding variability: Time charts versus histograms 128

Spotting misleading time charts 128

Part 3: Distributions And The Central Limit Theorem 133

Chapter 8: Random Variables and the Binomial Distribution 135

Defining a Random Variable 136

Discrete versus continuous 136

Probability distributions 137

The mean and variance of a discrete random variable 138

Identifying a Binomial 139

Checking binomial conditions step by step 140

No fixed number of trials 140

More than success or failure 141

Trials are not independent 141

Probability of success (p) changes 141

Finding Binomial Probabilities Using a Formula 142

Finding Probabilities Using the Binomial Table 144

Finding probabilities for specific values of X 145

Finding probabilities for X greater-than, less-than, or between two values 146

Checking Out the Mean and Standard Deviation of the Binomial 146

CHAPTER 9: The Normal Distribution 149

Exploring the Basics of the Normal Distribution 150

Meeting the Standard Normal (Z-) Distribution 152

Checking out Z 153

Standardizing from X to Z 153

Finding probabilities for Z with the Z-table 155

Finding Probabilities for a Normal Distribution 156

Finding X When You Know the Percent 158

Figuring out a percentile for a normal distribution 159

Translating tricky wording in percentile problems 161

Normal Approximation to the Binomial 162

CHAPTER 10: The t-Distribution 165

Basics of the t-Distribution 165

Comparing the t- and Z-distributions 165

Discovering the effect of variability on t-distributions 167

Using the t-Table 167

Finding probabilities with the t-table 168

Figuring percentiles for the t-distribution 168

Picking out t*-values for confidence intervals 169

Studying Behavior Using the t-Table 170

Chapter 11: Sampling Distributions and the Central Limit Theorem 171

Defining a Sampling Distribution 172

The Mean of a Sampling Distribution 174

Measuring Standard Error 174

Sample size and standard error 175

Population standard deviation and standard error 176

Looking at the Shape of a Sampling Distribution 178

Case 1: The distribution of X is normal 178

Case 2: The distribution of X is not normal—enter the Central Limit Theorem 178

Finding Probabilities for the Sample Mean 181

The Sampling Distribution of the Sample Proportion 183

Finding Probabilities for the Sample Proportion 185

Part 4: Guesstimating And Hypothesizing With Confidence 187

Chapter 12: Leaving Room for a Margin of Error 189

Seeing the Importance of That Plus or Minus 190

Finding the Margin of Error: A General Formula 191

Measuring sample variability 191

Calculating margin of error for a sample proportion 193

Reporting results 194

Calculating margin of error for a sample mean 195

Being confident you’re right 197

Determining the Impact of Sample Size 197

Sample size and margin of error 198

Bigger isn’t always (that much) better! 198

Keeping margin of error in perspective 199

Chapter 13: Confidence Intervals: Making Your Best Guesstimate 201

Not All Estimates Are Created Equal 202

Linking a Statistic to a Parameter 203

Getting with the Jargon 203

Interpreting Results with Confidence 204

Zooming In on Width 205

Choosing a Confidence Level 206

Factoring In the Sample Size 208

Counting On Population Variability 209

Calculating a Confidence Interval for a Population Mean 210

Case 1: Population standard deviation is known 210

Case 2: Population standard deviation is unknown and/or n is small 212

Figuring Out What Sample Size You Need 213

Determining the Confidence Interval for One Population Proportion 214

Creating a Confidence Interval for the Difference of Two Means 216

Case 1: Population standard deviations are known 216

Case 2: Population standard deviations are unknown and/or sample sizes are small 218

Estimating the Difference of Two Proportions 219

Spotting Misleading Confidence Intervals 221

Chapter 14: Claims, Tests, and Conclusions 223

Setting Up the Hypotheses 224

Defining the null 224

What’s the alternative? 225

Gathering Good Evidence (Data) 226

Compiling the Evidence: The Test Statistic 226

Gathering sample statistics 227

Measuring variability using standard errors 227

Understanding standard scores 228

Calculating and interpreting the test statistic 228

Weighing the Evidence and Making Decisions: p-Values 229

Connecting test statistics and p-values 229

Defining a p-value 230

Calculating a p-value 230

Making Conclusions 231

Setting boundaries for rejecting Ho 232

Testing varicose veins 233

Assessing the Chance of a Wrong Decision 233

Making a false alarm: Type-1 errors 234

Missing out on a detection: Type-2 errors 234

Chapter 15: Commonly Used Hypothesis Tests:

Formulas and Examples 237

Testing One Population Mean 238

Handling Small Samples and Unknown Standard Deviations: The t-Test 240

Putting the t-test to work 241

Relating t to Z 241

Handling negative t-values 242

Examining the not-equal-to alternative 242

Testing One Population Proportion 243

Comparing Two (Independent) Population Averages 245

Testing for an Average Difference (The Paired t-Test) 247

Comparing Two Population Proportions 251

Part 5: Statistical Studies And The Hunt For A Meaningful Relationship 255

Chapter 16: Polls, Polls, and More Polls 257

Recognizing the Impact of Polls 258

Getting to the source 258

Surveying what’s hot 260

Impacting lives 260

Behind the Scenes: The Ins and Outs of Surveys 262

Planning and designing a survey 263

Selecting the sample 266

Carrying out a survey 268

Interpreting results and finding problems 271

Chapter 17: Experiments: Medical Breakthroughs or Misleading Results? 275

Boiling Down the Basics of Studies 276

Looking at the lingo of studies 276

Observing observational studies 277

Examining experiments 278

Designing a Good Experiment 278

Designing the experiment to make comparisons 279

Selecting the sample size 281

Choosing the subjects 283

Making random assignments 283

Controlling for confounding variables 284

Respecting ethical issues 286

Collecting good data 287

Analyzing the data properly 289

Making appropriate conclusions 290

Making Informed Decisions 292

Chapter 18: Looking for Links: Correlation and Regression 293

Picturing a Relationship with a Scatterplot 294

Making a scatterplot 295

Interpreting a scatterplot 296

Quantifying Linear Relationships Using the Correlation 297

Calculating the correlation 297

Interpreting the correlation 298

Examining properties of the correlation 300

Working with Linear Regression 301

Figuring out which variable is X and which is Y 301

Checking the conditions 302

Calculating the regression line 302

Interpreting the regression line 304

Putting it all together with an example: The regression line for the crickets 306

Making Proper Predictions 306

Explaining the Relationship: Correlation versus Cause and Effect 308

Chapter 19: Two-Way Tables and Independence 311

Organizing a Two-Way Table 312

Setting up the cells 313

Figuring the totals 314

Interpreting Two-Way Tables 315

Singling out variables with marginal ­distributions 315

Examining all groups — a joint distribution 317

Comparing groups with conditional distributions 321

Checking Independence and Describing Dependence 324

Checking for independence 324

Describing a dependent relationship 327

Cautiously Interpreting Results 329

Checking for legitimate cause and effect 329

Projecting from sample to population 330

Making prudent predictions 331

Resisting the urge to jump to conclusions 332

Part 6: The Part Of Tens 333

Chapter 20: Ten Tips for the Statistically Savvy Sleuth 335

Pinpoint Misleading Graphs 335

Pie charts 336

Bar graphs 336

Time charts 337

Histograms 339

Uncover Biased Data 339

Search for a Margin of Error 340

Identify Non-Random Samples 341

Sniff Out Missing Sample Sizes 342

Detect Misinterpreted Correlations 343

Reveal Confounding Variables 344

Inspect the Numbers 344

Report Selective Reporting 345

Expose the Anecdote 346

Chapter 21: Ten Surefire Exam Score Boosters 349

Know What You Don’t Know, and then Do Something about It 350

Avoid “Yeah-Yeah” Traps 351

Yeah-yeah trap #1 352

Yeah-yeah trap #2 352

Make Friends with Formulas 354

Make an “If-Then-How” Chart 355

Figure Out What the Question Is Asking 357

Label What You’re Given 358

Draw a Picture 360

Make the Connection and Solve the Problem 361

Do the Math — Twice 362

Analyze Your Answers 363

Appendix: Tables For Reference 365

Index 375

Statistics For Dummies

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    A Paperback / softback by Deborah J. Rumsey

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      View other formats and editions of Statistics For Dummies by Deborah J. Rumsey

      Publisher: John Wiley & Sons Inc
      Publication Date: 19/07/2016
      ISBN13: 9781119293521, 978-1119293521
      ISBN10: 1119293529

      Description

      Book Synopsis
      Statistics For Dummies, 2nd Edition (9781119293521) was previously published as Statistics For Dummies, 2nd Edition (9780470911082). While this version features a new Dummies cover and design, the content is the same as the prior release and should not be considered a new or updated product.

      Table of Contents

      Introduction 1

      About This Book 1

      Conventions Used in This Book 2

      What You’re 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

      Examining Boxplots 120

      Making a boxplot 120

      Interpreting a boxplot 121

      Tackling Time Charts 127

      Interpreting time charts 127

      Understanding variability: Time charts versus histograms 128

      Spotting misleading time charts 128

      Part 3: Distributions And The Central Limit Theorem 133

      Chapter 8: Random Variables and the Binomial Distribution 135

      Defining a Random Variable 136

      Discrete versus continuous 136

      Probability distributions 137

      The mean and variance of a discrete random variable 138

      Identifying a Binomial 139

      Checking binomial conditions step by step 140

      No fixed number of trials 140

      More than success or failure 141

      Trials are not independent 141

      Probability of success (p) changes 141

      Finding Binomial Probabilities Using a Formula 142

      Finding Probabilities Using the Binomial Table 144

      Finding probabilities for specific values of X 145

      Finding probabilities for X greater-than, less-than, or between two values 146

      Checking Out the Mean and Standard Deviation of the Binomial 146

      CHAPTER 9: The Normal Distribution 149

      Exploring the Basics of the Normal Distribution 150

      Meeting the Standard Normal (Z-) Distribution 152

      Checking out Z 153

      Standardizing from X to Z 153

      Finding probabilities for Z with the Z-table 155

      Finding Probabilities for a Normal Distribution 156

      Finding X When You Know the Percent 158

      Figuring out a percentile for a normal distribution 159

      Translating tricky wording in percentile problems 161

      Normal Approximation to the Binomial 162

      CHAPTER 10: The t-Distribution 165

      Basics of the t-Distribution 165

      Comparing the t- and Z-distributions 165

      Discovering the effect of variability on t-distributions 167

      Using the t-Table 167

      Finding probabilities with the t-table 168

      Figuring percentiles for the t-distribution 168

      Picking out t*-values for confidence intervals 169

      Studying Behavior Using the t-Table 170

      Chapter 11: Sampling Distributions and the Central Limit Theorem 171

      Defining a Sampling Distribution 172

      The Mean of a Sampling Distribution 174

      Measuring Standard Error 174

      Sample size and standard error 175

      Population standard deviation and standard error 176

      Looking at the Shape of a Sampling Distribution 178

      Case 1: The distribution of X is normal 178

      Case 2: The distribution of X is not normal—enter the Central Limit Theorem 178

      Finding Probabilities for the Sample Mean 181

      The Sampling Distribution of the Sample Proportion 183

      Finding Probabilities for the Sample Proportion 185

      Part 4: Guesstimating And Hypothesizing With Confidence 187

      Chapter 12: Leaving Room for a Margin of Error 189

      Seeing the Importance of That Plus or Minus 190

      Finding the Margin of Error: A General Formula 191

      Measuring sample variability 191

      Calculating margin of error for a sample proportion 193

      Reporting results 194

      Calculating margin of error for a sample mean 195

      Being confident you’re right 197

      Determining the Impact of Sample Size 197

      Sample size and margin of error 198

      Bigger isn’t always (that much) better! 198

      Keeping margin of error in perspective 199

      Chapter 13: Confidence Intervals: Making Your Best Guesstimate 201

      Not All Estimates Are Created Equal 202

      Linking a Statistic to a Parameter 203

      Getting with the Jargon 203

      Interpreting Results with Confidence 204

      Zooming In on Width 205

      Choosing a Confidence Level 206

      Factoring In the Sample Size 208

      Counting On Population Variability 209

      Calculating a Confidence Interval for a Population Mean 210

      Case 1: Population standard deviation is known 210

      Case 2: Population standard deviation is unknown and/or n is small 212

      Figuring Out What Sample Size You Need 213

      Determining the Confidence Interval for One Population Proportion 214

      Creating a Confidence Interval for the Difference of Two Means 216

      Case 1: Population standard deviations are known 216

      Case 2: Population standard deviations are unknown and/or sample sizes are small 218

      Estimating the Difference of Two Proportions 219

      Spotting Misleading Confidence Intervals 221

      Chapter 14: Claims, Tests, and Conclusions 223

      Setting Up the Hypotheses 224

      Defining the null 224

      What’s the alternative? 225

      Gathering Good Evidence (Data) 226

      Compiling the Evidence: The Test Statistic 226

      Gathering sample statistics 227

      Measuring variability using standard errors 227

      Understanding standard scores 228

      Calculating and interpreting the test statistic 228

      Weighing the Evidence and Making Decisions: p-Values 229

      Connecting test statistics and p-values 229

      Defining a p-value 230

      Calculating a p-value 230

      Making Conclusions 231

      Setting boundaries for rejecting Ho 232

      Testing varicose veins 233

      Assessing the Chance of a Wrong Decision 233

      Making a false alarm: Type-1 errors 234

      Missing out on a detection: Type-2 errors 234

      Chapter 15: Commonly Used Hypothesis Tests:

      Formulas and Examples 237

      Testing One Population Mean 238

      Handling Small Samples and Unknown Standard Deviations: The t-Test 240

      Putting the t-test to work 241

      Relating t to Z 241

      Handling negative t-values 242

      Examining the not-equal-to alternative 242

      Testing One Population Proportion 243

      Comparing Two (Independent) Population Averages 245

      Testing for an Average Difference (The Paired t-Test) 247

      Comparing Two Population Proportions 251

      Part 5: Statistical Studies And The Hunt For A Meaningful Relationship 255

      Chapter 16: Polls, Polls, and More Polls 257

      Recognizing the Impact of Polls 258

      Getting to the source 258

      Surveying what’s hot 260

      Impacting lives 260

      Behind the Scenes: The Ins and Outs of Surveys 262

      Planning and designing a survey 263

      Selecting the sample 266

      Carrying out a survey 268

      Interpreting results and finding problems 271

      Chapter 17: Experiments: Medical Breakthroughs or Misleading Results? 275

      Boiling Down the Basics of Studies 276

      Looking at the lingo of studies 276

      Observing observational studies 277

      Examining experiments 278

      Designing a Good Experiment 278

      Designing the experiment to make comparisons 279

      Selecting the sample size 281

      Choosing the subjects 283

      Making random assignments 283

      Controlling for confounding variables 284

      Respecting ethical issues 286

      Collecting good data 287

      Analyzing the data properly 289

      Making appropriate conclusions 290

      Making Informed Decisions 292

      Chapter 18: Looking for Links: Correlation and Regression 293

      Picturing a Relationship with a Scatterplot 294

      Making a scatterplot 295

      Interpreting a scatterplot 296

      Quantifying Linear Relationships Using the Correlation 297

      Calculating the correlation 297

      Interpreting the correlation 298

      Examining properties of the correlation 300

      Working with Linear Regression 301

      Figuring out which variable is X and which is Y 301

      Checking the conditions 302

      Calculating the regression line 302

      Interpreting the regression line 304

      Putting it all together with an example: The regression line for the crickets 306

      Making Proper Predictions 306

      Explaining the Relationship: Correlation versus Cause and Effect 308

      Chapter 19: Two-Way Tables and Independence 311

      Organizing a Two-Way Table 312

      Setting up the cells 313

      Figuring the totals 314

      Interpreting Two-Way Tables 315

      Singling out variables with marginal ­distributions 315

      Examining all groups — a joint distribution 317

      Comparing groups with conditional distributions 321

      Checking Independence and Describing Dependence 324

      Checking for independence 324

      Describing a dependent relationship 327

      Cautiously Interpreting Results 329

      Checking for legitimate cause and effect 329

      Projecting from sample to population 330

      Making prudent predictions 331

      Resisting the urge to jump to conclusions 332

      Part 6: The Part Of Tens 333

      Chapter 20: Ten Tips for the Statistically Savvy Sleuth 335

      Pinpoint Misleading Graphs 335

      Pie charts 336

      Bar graphs 336

      Time charts 337

      Histograms 339

      Uncover Biased Data 339

      Search for a Margin of Error 340

      Identify Non-Random Samples 341

      Sniff Out Missing Sample Sizes 342

      Detect Misinterpreted Correlations 343

      Reveal Confounding Variables 344

      Inspect the Numbers 344

      Report Selective Reporting 345

      Expose the Anecdote 346

      Chapter 21: Ten Surefire Exam Score Boosters 349

      Know What You Don’t Know, and then Do Something about It 350

      Avoid “Yeah-Yeah” Traps 351

      Yeah-yeah trap #1 352

      Yeah-yeah trap #2 352

      Make Friends with Formulas 354

      Make an “If-Then-How” Chart 355

      Figure Out What the Question Is Asking 357

      Label What You’re Given 358

      Draw a Picture 360

      Make the Connection and Solve the Problem 361

      Do the Math — Twice 362

      Analyze Your Answers 363

      Appendix: Tables For Reference 365

      Index 375

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