book

Statistics For Dummies®, 2nd Edition

by Deborah J. Rumsey

May 2011

Beginner

384 pages

10h 48m

English

For Dummies

Read now

Unlock full access

About This BookConventions Used in This BookWhat You're Not to ReadFoolish AssumptionsHow This Book Is OrganizedIcons Used in This BookWhere to Go from Here

Thriving in a Statistical WorldDesigning Appropriate StudiesCollecting Quality DataCreating Effective SummariesDetermining DistributionsPerforming Proper AnalysesDrawing Credible ConclusionsBecoming a Sleuth, Not a Skeptic
Statistics and the Media: More Questions than Answers?Using Statistics at Work
Detecting Errors, Exaggerations, and Just Plain LiesFeeling the Impact of Misleading Statistics
Statistics: More than Just NumbersGrabbing Some Basic Statistical Jargon
Summing Up Data with Descriptive StatisticsCrunching Categorical Data: Tables and PercentsMeasuring the Center with Mean and MedianAccounting for VariationExamining the Empirical Rule (68-95-99.7)Measuring Relative Standing with Percentiles
Take Another Little Piece of My Pie ChartRaising the Bar on Bar Graphs
Handling HistogramsExamining BoxplotsTackling Time Charts
Defining a Random VariableIdentifying a BinomialFinding Binomial Probabilities Using a FormulaFinding Probabilities Using the Binomial TableChecking Out the Mean and Standard Deviation of the Binomial
Exploring the Basics of the Normal DistributionMeeting the Standard Normal (Z-) DistributionFinding Probabilities for a Normal DistributionFinding X When You Know the PercentNormal Approximation to the Binomial
Basics of the t-DistributionUsing the t-TableStudying Behavior Using the t-Table
Defining a Sampling DistributionThe Mean of a Sampling DistributionMeasuring Standard ErrorLooking at the Shape of a Sampling DistributionFinding Probabilities for the Sample MeanThe Sampling Distribution of the Sample ProportionFinding Probabilities for the Sample Proportion
Seeing the Importance of That Plus or MinusFinding the Margin of Error: A General FormulaCalculating margin of error for a sample meanDetermining the Impact of Sample Size
Not All Estimates Are Created EqualLinking a Statistic to a ParameterGetting with the JargonInterpreting Results with ConfidenceZooming In on WidthChoosing a Confidence LevelFactoring In the Sample SizeCounting On Population VariabilityCalculating a Confidence Interval for a Population MeanFiguring Out What Sample Size You NeedDetermining the Confidence Interval for One Population ProportionCreating a Confidence Interval for the Difference of Two MeansEstimating the Difference of Two ProportionsSpotting Misleading Confidence Intervals
Setting Up the HypothesesGathering Good Evidence (Data)Compiling the Evidence: The Test StatisticWeighing the Evidence and Making Decisions: p-ValuesMaking ConclusionsAssessing the Chance of a Wrong Decision
Testing One Population MeanHandling Small Samples and Unknown Standard Deviations: The t-TestTesting One Population ProportionComparing Two (Independent) Population AveragesTesting for an Average Difference (The Paired t-Test)Comparing Two Population Proportions
Recognizing the Impact of PollsBehind the Scenes: The Ins and Outs of Surveys
Boiling Down the Basics of StudiesDesigning a Good ExperimentMaking Informed Decisions
Picturing a Relationship with a ScatterplotQuantifying Linear Relationships Using the CorrelationWorking with Linear RegressionMaking Proper PredictionsExplaining the Relationship: Correlation versus Cause and Effect
Organizing a two-say TableInterpreting two-say TablesChecking Independence and Describing DependenceCautiously Interpreting Results
Pinpoint Misleading GraphsUncover Biased DataSearch for a Margin of ErrorIdentify Non-Random SamplesSniff Out Missing Sample SizesDetect Misinterpreted CorrelationsReveal Confounding VariablesInspect the NumbersReport Selective ReportingExpose the Anecdote
Know What You Don't Know, and then Do Something about ItAvoid “Yeah-Yeah” TrapsMake Friends with FormulasMake an “If-Then-How” ChartFigure Out What the Question Is AskingLabel What You're GivenDraw a PictureMake the Connection and Solve the ProblemDo the Math — TwiceAnalyze Your Answers
The Z-TableThe t-TableThe Binomial Table

Content preview from Statistics For Dummies®, 2nd Edition

Chapter 3 Taking Control: So Many Numbers, So Little Time

In This Chapter

Examining the extent of statistics abuse
Feeling the impact of statistics gone wrong

The sheer amount of statistics in daily life can leave you feeling overwhelmed and confused. This chapter gives you a tool to help you deal with statistics: skepticism! Not radical skepticism like “I can't believe anything anymore,” but healthy skepticism like “Hmm, I wonder where that number came from?” and “I need to find out more information before I believe these results.” To develop healthy skepticism, you need to understand how the chain of statistical information works.

Statistics end up on your TV and in your newspaper as a result of a process. First, the researchers who study an issue generate results; this group is composed of pollsters, doctors, marketing researchers, government researchers, and other scientists. They are considered the original sources of the statistical information.

After they get their results, these researchers naturally want to tell people about it, so they typically either put out a press release or publish a journal article. Enter the journalists or reporters, who are considered the media sources of the information. Journalists hunt for interesting press releases and sort through journals, basically searching for the next headline. When reporters complete their stories, statistics are immediately sent out to the public through all forms of media. Now the information is ready to be taken ...