Statistics For Dummies

Höfundur: Deborah J. Rumsey (Útgáfa: 2)
Statistics For Dummies

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The fun and easy way to get down to business with statistics Stymied by statistics? No fear? this friendly guide offers clear, practical explanations of statistical ideas, techniques, formulas, and calculations, with lots of examples that show you how these concepts apply to your everyday life. Statistics For Dummies shows you how to interpret and critique graphs and charts, determine the odds with probability, guesstimate with confidence using confidence intervals, set up and carry out a hypothesis test, compute statistical formulas, and more.

Tracks to a typical first semester statistics course Updated examples resonate with today's students Explanations mirror teaching methods and classroom protocol Packed with practical advice and real-world problems, Statistics For Dummies gives you everything you need to analyze and interpret data for improved classroom or on-the-job performance.

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Útgefandi
Wiley Professional Development (P&T)
ISBN
9781119297512
Print ISBN
9781119293521
Format
ePub
Útgáfa
2
Höfundar
Deborah J. Rumsey
Tungumál
English
Útgefið
2016-05-19
Prent takmörkun á líftíma
100
Prent takmörkun
10
Afritunar takmörkun
2

Kaflar

  • Cover
  • Introduction
  • About This Book
  • Conventions Used in This Book
  • What You’re Not to Read
  • Foolish Assumptions
  • How This Book Is Organized
  • Icons Used in This Book
  • Where to Go from Here
  • Part 1: Vital Statistics about Statistics
  • Chapter 1: Statistics in a Nutshell
  • Thriving in a Statistical World
  • Designing Appropriate Studies
  • Collecting Quality Data
  • Creating Effective Summaries
  • Determining Distributions
  • Performing Proper Analyses
  • Drawing Credible Conclusions
  • Becoming a Sleuth, Not a Skeptic
  • Chapter 2: The Statistics of Everyday Life
  • Statistics and the Media: More Questions than Answers?
  • Using Statistics at Work
  • Chapter 3: Taking Control: So Many Numbers, So Little Time
  • Detecting Errors, Exaggerations, and Just Plain Lies
  • Feeling the Impact of Misleading Statistics
  • Chapter 4: Tools of the Trade
  • Statistics: More than Just Numbers
  • Grabbing Some Basic Statistical Jargon
  • Part 2: Number-Crunching Basics
  • Chapter 5: Means, Medians, and More
  • Summing Up Data with Descriptive Statistics
  • Crunching Categorical Data: Tables and Percents
  • Measuring the Center with Mean and Median
  • Accounting for Variation
  • Examining the Empirical Rule (68-95-99.7)
  • Measuring Relative Standing with Percentiles
  • Chapter 6: Getting the Picture: Graphing Categorical Data
  • Take Another Little Piece of My Pie Chart
  • Raising the Bar on Bar Graphs
  • Chapter 7: Going by the Numbers: Graphing Numerical Data
  • Handling Histograms
  • Examining Boxplots
  • Tackling Time Charts
  • Part 3: Distributions and the Central Limit Theorem
  • Chapter 8: Random Variables and the Binomial Distribution
  • Defining a Random Variable
  • Identifying a Binomial
  • Finding Binomial Probabilities Using a Formula
  • Finding Probabilities Using the Binomial Table
  • Checking Out the Mean and Standard Deviation of the Binomial
  • Chapter 9: The Normal Distribution
  • Exploring the Basics of the Normal Distribution
  • Meeting the Standard Normal (Z-) Distribution
  • Finding Probabilities for a Normal Distribution
  • Finding X When You Know the Percent
  • Normal Approximation to the Binomial
  • Chapter 10: The t-Distribution
  • Basics of the t-Distribution
  • Using the t-Table
  • Studying Behavior Using the t-Table
  • Chapter 11: Sampling Distributions and the Central Limit Theorem
  • Defining a Sampling Distribution
  • The Mean of a Sampling Distribution
  • Measuring Standard Error
  • Looking at the Shape of a Sampling Distribution
  • Finding Probabilities for the Sample Mean
  • The Sampling Distribution of the Sample Proportion
  • Finding Probabilities for the Sample Proportion
  • Part 4: Guesstimating and Hypothesizing with Confidence
  • Chapter 12: Leaving Room for a Margin of Error
  • Seeing the Importance of That Plus or Minus
  • Finding the Margin of Error: A General Formula
  • Determining the Impact of Sample Size
  • Chapter 13: Confidence Intervals: Making Your Best Guesstimate
  • Not All Estimates Are Created Equal
  • Linking a Statistic to a Parameter
  • Getting with the Jargon
  • Interpreting Results with Confidence
  • Zooming In on Width
  • Choosing a Confidence Level
  • Factoring In the Sample Size
  • Counting On Population Variability
  • Calculating a Confidence Interval for a Population Mean
  • Figuring Out What Sample Size You Need
  • Determining the Confidence Interval for One Population Proportion
  • Creating a Confidence Interval for the Difference of Two Means
  • Estimating the Difference of Two Proportions
  • Spotting Misleading Confidence Intervals
  • Chapter 14: Claims, Tests, and Conclusions
  • Setting Up the Hypotheses
  • Gathering Good Evidence (Data)
  • Compiling the Evidence: The Test Statistic
  • Weighing the Evidence and Making Decisions: p-Values
  • Making Conclusions
  • Assessing the Chance of a Wrong Decision
  • Chapter 15: Commonly Used Hypothesis Tests: Formulas and Examples
  • Testing One Population Mean
  • Handling Small Samples and Unknown Standard Deviations: The t-Test
  • Testing One Population Proportion
  • Comparing Two (Independent) Population Averages
  • Testing for an Average Difference (The Paired t-Test)
  • Comparing Two Population Proportions
  • Part 5: Statistical Studies and the Hunt for a Meaningful Relationship
  • Chapter 16: Polls, Polls, and More Polls
  • Recognizing the Impact of Polls
  • Behind the Scenes: The Ins and Outs of Surveys
  • Chapter 17: Experiments: Medical Breakthroughs or Misleading Results?
  • Boiling Down the Basics of Studies
  • Designing a Good Experiment
  • Making Informed Decisions
  • Chapter 18: Looking for Links: Correlation and Regression
  • Picturing a Relationship with a Scatterplot
  • Quantifying Linear Relationships Using the Correlation
  • Working with Linear Regression
  • Making Proper Predictions
  • Explaining the Relationship: Correlation versus Cause and Effect
  • Chapter 19: Two-Way Tables and Independence
  • Organizing a Two-Way Table
  • Interpreting Two-Way Tables
  • Checking Independence and Describing Dependence
  • Cautiously Interpreting Results
  • Part 6: The Part of Tens
  • Chapter 20: Ten Tips for the Statistically Savvy Sleuth
  • Pinpoint Misleading Graphs
  • Uncover Biased Data
  • Search for a Margin of Error
  • Identify Non-Random Samples
  • Sniff Out Missing Sample Sizes
  • Detect Misinterpreted Correlations
  • Reveal Confounding Variables
  • Inspect the Numbers
  • Report Selective Reporting
  • Expose the Anecdote
  • Chapter 21: Ten Surefire Exam Score Boosters
  • Know What You Don’t Know, and then Do Something about It
  • Avoid “Yeah-Yeah” Traps
  • Make Friends with Formulas
  • Make an “If-Then-How” Chart
  • Figure Out What the Question Is Asking
  • Label What You’re Given
  • Draw a Picture
  • Make the Connection and Solve the Problem
  • Do the Math — Twice
  • Analyze Your Answers
  • Appendix: Tables for Reference
  • About the Author
  • Advertisement Page
  • Connect with Dummies
  • End User License Agreement