Make studying statistics simple with this easy-to-read resource Wouldn't it be wonderful if studying statistics were easier? With U Can: Statistics I For Dummies, it is! This one-stop resource combines lessons, practical examples, study questions, and online practice problems to provide you with the ultimate guide to help you score higher in your statistics course. Foundational statistics skills are a must for students of many disciplines, and leveraging study materials such as this one to supplement your statistics course can be a life-saver. Because U Can: Statistics I For Dummies contains both the lessons you need to learn and the practice problems you need to put the concepts into action, you'll breeze through your scheduled study time. Statistics is all about collecting and interpreting data, and is applicable in a wide range of subject areas—which translates into its popularity among students studying in diverse programs. So, if you feel a bit unsure in class, rest assured that there is an easy way to help you grasp the nuances of statistics! Understand statistical ideas, techniques, formulas, and calculations Interpret and critique graphs and charts, determine probability, and work with confidence intervals Critique and analyze data from polls and experiments Combine learning and applying your new knowledge with practical examples, practice problems, and expanded online resources U Can: Statistics I For Dummies contains everything you need to score higher in your fundamental statistics course!

Table of Contents:
Introduction 1 About This Book 1 Foolish Assumptions 2 Beyond the Book 3 Where to Go from Here 4 Part I Getting Started With Statistics 5 Chapter 1: The Statistics of Everyday Life 7 Statistics and the Media: More Questions than Answers? 7 Probing popcorn problems 8 Venturing into viruses 8 Comprehending crashes 8 Mulling malpractice 9 Belaboring the loss of land 9 Scrutinizing schools 10 Studying sports 11 Banking on business news 11 Touring the travel news 12 Surveying sexual stats 12 Breaking down weather reports 12 Using Statistics at Work 13 Delivering babies — and information 13 Posing for pictures 14 Poking through pizza data 14 Statistics in the office 14 Chapter 2: Taking Control: So Many Numbers, So Little Time 15 Detecting Errors, Exaggerations, and Just Plain Lies 15 Checking the math 16 Uncovering misleading statistics 16 Looking for lies in all the right places 22 Feeling the Impact of Misleading Statistics 23 Chapter 3: Tools of the Trade 25 Thriving in a Statistical World 25 Statistics: More than Just Numbers 26 Designing Appropriate Studies 28 Surveys (Polls) 28 Experiments 28 Collecting Quality Data 30 Sample, random, or otherwise 30 Bias 32 Grabbing Some Basic Statistical Jargon 32 Data 33 Data set 34 Variable 34 Population 34 Statistic 35 Parameter 35 Mean (Average) 35 Median 36 Standard deviation 36 Percentile 37 Standard score 37 Distribution and normal distribution 38 Central Limit Theorem 39 z‐values 39 Margin of error 39 Confidence interval 40 Hypothesis testing 41 p‐values 41 Statistical significance 42 Correlation, regression, and two‐way tables 43 Drawing Credible Conclusions 44 Reeling in overstated results 44 Questioning claims of cause and effect 44 Becoming a Sleuth, Not a Skeptic 45 Part II Number‐Crunching Basics 47 Chapter 4: Crunching Categorical Data 49 Summing Up Data with Descriptive Statistics 49 Crunching Categorical Data: Tables and Percents 50 Counting on the frequency 50 Relating with percentages 52 Two‐way tables: Summarizing multiple measures 55 Interpreting counts and percents with caution 57 Chapter 5: Means, Medians, and More 61 Measuring the Center with Mean and Median 61 Averaging out to the mean 61 Splitting your data down the median 64 Comparing means and medians: Histograms 67 Accounting for Variation 73 Reporting the standard deviation 73 Being out of range 76 Examining the Empirical Rule (68‐95‐99.7) 78 Measuring Relative Standing with Percentiles 84 Calculating percentiles 85 Interpreting percentiles 86 Gathering a five‐number summary 90 Exploring interquartile range 91 Chapter 6: Getting the Picture: Graphing Categorical Data 93 Take Another Little Piece of My Pie Chart 93 Tallying personal expenses 94 Bringing in a lotto revenue 95 Ordering takeout 96 Projecting age trends 96 Raising the Bar on Bar Graphs 105 Tracking transportation expenses 105 Making a lotto profit 106 Tipping the scales on a bar graph 107 Pondering pet peeves 109 Chapter 7: Going by the Numbers: Graphing Numerical Data 117 Handling Histograms 117 Making a histogram 117 Interpreting a histogram 123 Putting numbers with pictures 130 Detecting misleading histograms 134 Examining Boxplots 139 Making a boxplot 139 Interpreting a boxplot 143 Tackling Time Charts 150 Interpreting time charts 150 Understanding variability: Time charts versus histograms 151 Spotting misleading time charts 151 Part III Distributions and The Central Limit Theorem 159 Chapter 8: Coming to Terms with Probability 161 A Set Notation Overview 161 Noting outcomes: Sample spaces 161 Noting subsets of sample spaces: Events 162 Noting a void in the set: Empty sets 164 Putting sets together: Unions, intersections, and complements 164 Probabilities of Events Involving A and/or B 165 Probability notation 165 Marginal probabilities 167 Union probabilities 167 Intersection (joint) probabilities 167 Complement probabilities 168 Conditional probabilities 168 Understanding and Applying the Rules of Probability 169 The complement rule (for opposites, not for flattering a date) 170 The multiplication rule (for intersections, not for rabbits) 171 The addition rule (for unions of the nonmarital nature) 172 Recognizing Independence in Multiple Events 175 Checking independence for two events with the definition 175 Using the multiplication rule for independent events 176 Including Mutually Exclusive Events 177 Recognizing mutually exclusive events 177 Simplifying the addition rule with mutually exclusive events 178 Distinguishing Independent from Mutually Exclusive Events 179 Comparing and contrasting independence and exclusivity 179 Checking for independence or exclusivity in a 52‐card deck 179 Avoiding Probability Misconceptions 183 Predictions Using Probability 185 Chapter 9: Random Variables and the Binomial Distribution 187 Defining a Random Variable 187 Discrete versus continuous 188 Probability distributions 190 The mean and variance of a discrete random variable 191 Identifying a Binomial 192 Checking binomial conditions step by step 192 No fixed number of trials 193 More than success or failure 193 Trials are not independent 193 Probability of success (p) changes 194 Finding Binomial Probabilities Using a Formula 196 Finding Probabilities Using the Binomial Table 200 Finding probabilities for specific values of X 201 Finding probabilities for X greater‐than, less‐than, or between two values 201 Checking Out the Mean and Standard Deviation of the Binomial 203 Chapter 10: The Normal Distribution 205 Exploring the Basics of the Normal Distribution 205 Meeting the Standard Normal (Z‐) Distribution 211 Checking out Z 211 Standardizing from X to Z 212 Finding probabilities for Z with the Z‐table 213 Finding Probabilities for a Normal Distribution 216 Knowing Where You Stand with Percentiles 222 Finding X When You Know the Percent 224 Figuring out a percentile for a normal distribution 224 Translating tricky wording in percentile problems 226 Normal Approximation to the Binomial 229 Chapter 11: The t‐Distribution 233 Basics of the t‐Distribution 233 Comparing the t‐ and Z‐distributions 233 Discovering the effect of variability on t‐distributions 234 Using the t‐Table 235 Finding probabilities with the t‐table 235 Figuring percentiles for the t‐distribution 238 Picking out t*‐values for confidence intervals 240 Studying Behavior Using the t‐Table 241 Chapter 12: Sampling Distributions and the Central Limit Theorem 243 Defining a Sampling Distribution 243 The Mean of a Sampling Distribution 245 Measuring Standard Error 245 Sample size and standard error 246 Population standard deviation and standard error 247 Looking at the Shape of a Sampling Distribution 248 Case 1: The distribution of X is normal 248 Case 2: The distribution of X is not normal — Enter the Central Limit Theorem 249 Finding Probabilities for the Sample Mean 252 The Sampling Distribution of the Sample Proportion 256 Finding Probabilities for the Sample Proportion 260 Part IV Guesstimating And Hypothesizing With Confidence 263 Chapter 13: Leaving Room for a Margin of Error 265 Seeing the Importance of That Plus or Minus 265 Finding the Margin of Error: A General Formula 266 Measuring sample variability 267 Calculating margin of error for a sample proportion 269 Reporting results 270 Calculating margin of error for a sample mean 271 Being confident you’re right 272 Determining the Impact of Sample Size 275 Sample size and margin of error 276 Bigger isn’t always (that much) better! 276 Keeping margin of error in perspective 277 Chapter 14: Confidence Intervals: Making Your Best Guesstimate 281 Not All Estimates Are Created Equal 281 Linking a Statistic to a Parameter 282 Getting with the Jargon 283 Interpreting Results with Confidence 283 Zooming In on Width 286 Choosing a Confidence Level 287 Factoring In the Sample Size 288 Counting On Population Variability 289 Calculating a Confidence Interval for a Population Mean 291 Case 1: Population standard deviation is known 291 Case 2: Population standard deviation is unknown and/or nis small 293 Figuring Out What Sample Size You Need 295 Determining the Confidence Interval for One Population Proportion 297 Creating a Confidence Interval for the Difference of Two Means 300 Case 1: Population standard deviations are known 301 Case 2: Population standard deviations are unknown and/or sample sizes are small 302 Estimating the Difference of Two Proportions 306 Spotting Misleading Confidence Intervals 311 Chapter 15: Claims, Tests, and Conclusions 313 Setting Up the Hypotheses 314 Defining the null 314 What’s the alternative? 314 Gathering Good Evidence (Data) 315 Compiling the Evidence: The Test Statistic 316 Gathering sample statistics 316 Measuring variability using standard errors 316 Understanding standard scores 317 Calculating and interpreting the test statistic 317 Weighing the Evidence and Making Decisions: p‐Values 317 Connecting test statistics and p‐values 318 Defining a p‐value 319 Calculating a p‐value 319 Making Conclusions 322 Setting boundaries for rejecting H0 322 Testing varicose veins 323 Assessing the Chance of a Wrong Decision 325 Making a false alarm: Type I errors 325 Missing out on a detection: Type II errors 326 Chapter 16: Commonly Used Hypothesis Tests: Formulas and Examples 331 Testing One Population Mean 331 Handling Small Samples and Unknown Standard Deviations: The t‐Test 333 Putting the t‐test to work 334 Relating t to Z 334 Handling negative t‐values 335 Examining the not‐equal‐to alternative 335 Drawing conclusions using the critical value 335 Testing One Population Proportion 339 Comparing Two (Independent) Population Averages 342 Testing for an Average Difference (The Paired t‐Test) 346 Comparing Two Population Proportions 351 Part V Statistical Studies And The Hunt For A Meaningful Relationship 355 Chapter 17: Polls, Polls, and More Polls 357 Recognizing the Impact of Polls 357 Getting to the source 358 Surveying what’s hot 358 Impacting lives 360 Behind the Scenes: The Ins and Outs of Surveys 361 Planning and designing a survey 361 Selecting the sample 366 Carrying out a survey 369 Interpreting results and finding problems 373 Chapter 18: Experiments: Medical Breakthroughs or Misleading Results? 377 Boiling Down the Basics of Studies 377 Looking at the lingo of studies 378 Observing observational studies 379 Examining experiments 379 Designing a Good Experiment 381 Designing the experiment to make comparisons 382 Selecting the sample size 384 Choosing the subjects 385 Making random assignments 385 Controlling for confounding variables 386 Respecting ethical issues 388 Collecting good data 388 Analyzing the data properly 390 Interpreting Experiment Results 392 Making appropriate conclusions 393 Making informed decisions 394 Chapter 19: Looking for Links: Correlation and Regression 397 Picturing a Relationship with a Scatterplot 397 Making a scatterplot 398 Interpreting a scatterplot 398 Quantifying Linear Relationships Using the Correlation 402 Calculating the correlation 402 Interpreting the correlation 404 Examining properties of the correlation 406 Working with Linear Regression 408 Figuring out which variable is X and which is Y 409 Checking the conditions 409 Calculating the regression line 410 Interpreting the regression line 414 Putting it all together with an example: The regression line for the crickets 416 Making Proper Predictions 419 Checking the conditions 420 Staying in‐bounds 420 Explaining the Relationship: Correlation versus Cause and Effect 423 Chapter 20: Two‐Way Tables and Independence 425 Organizing a Two‐Way Table 425 Setting up the cells 426 Figuring the totals 427 Interpreting Two‐Way Tables 431 Singling out variables with marginal distributions 431 Examining all groups — a joint distribution 436 Comparing groups with conditional distributions 438 Checking Independence and Describing Dependence 445 Checking for independence 445 Describing a dependent relationship 448 Cautiously Interpreting Results 452 Checking for legitimate cause and effect 452 Projecting from sample to population 453 Making prudent predictions 454 Resisting the urge to jump to conclusions 455 Part VI The Part Of Tens 457 Chapter 21: Ten Tips for the Statistically Savvy Sleuth 459 Pinpoint Misleading Graphs 459 Pie charts 459 Bar graphs 460 Time charts 461 Histograms 462 Uncover Biased Data 462 Search for a Margin of Error 463 Identify NonRandom Samples 463 Sniff Out Missing Sample Sizes 464 Detect Misinterpreted Correlations 465 Reveal Confounding Variables 466 Inspect the Numbers 466 Report Selective Reporting 467 Expose the Anecdote 468 Chapter 22: Ten Surefire Exam Score Boosters 469 Know What You Don’t Know, and then Do Something about It 469 Avoid “Yeah‐Yeah” Traps 471 Yeah‐yeah trap #1 471 Yeah‐yeah trap #2 471 Make Friends with Formulas 473 Make an “If‐Then‐How” Chart 474 Figure Out What the Question Is Asking 475 Label What You’re Given 476 Draw a Picture 478 Make the Connection and Solve the Problem 479 Do the Math — Twice 479 Analyze Your Answers 480 Appendix 481 The Z‐Table 481 The t‐Table 484 The Binomial Table 486 Index 491