book

Statistics For Dummies®, 2nd Edition

by Deborah J. Rumsey

May 2011

Beginner

384 pages

10h 48m

English

For Dummies

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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

Part IV

Guesstimating and Hypothesizing with Confidence

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In this part …

Anytime you're given a statistic by itself, you haven't really gotten the full story. The statistic alone is missing the most important part: by how much that statistic is expected to vary. All good estimates of population parameters contain not just a statistic but also a margin of error. This combination of a statistic plus or minus a margin of error is called a confidence interval.

Now suppose you're already given a claim, assumption, or target value for the population parameter, and you want to test that claim. You do it with a hypothesis test based on sample statistics. Because sample statistics will vary, you need techniques that take this into account.

This part gives you a general, intuitive look at margin of error, confidence intervals, and hypothesis tests: their function, formulas, calculations, influential factors, and interpretation. You also get quick references and examples for the most commonly used confidence intervals and hypothesis tests.