Statistics for Dummies�

ISBN-10: 0764554239

ISBN-13: 9780764554230

Edition: 2003

Authors: Deborah Rumsey

List price: $19.99
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This is a simple, clear, direct guide that enables any reader to feel confident interpreting data and applying the concepts of statistics.
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Book details

List price: $19.99
Copyright year: 2003
Publisher: John Wiley & Sons, Incorporated
Publication date: 9/19/2003
Binding: Paperback
Pages: 384
Size: 7.50" wide x 9.00" long x 1.00" tall
Weight: 1.540
Language: English

About This Book
Conventions Used in This Book
Foolish Assumptions
How This Book Is Organized
Icons Used in This Book
Where to Go from Here
Vital Statistics about Statistics
The Statistics of Everyday Life
Statistics and the Media Blitz: More Questions than Answers?
Using Statistics at Work
Statistics Gone Wrong
Taking Control: So Many Numbers, So Little Time
Detecting Errors, Exaggerations, and Just Plain Lies
Feeling the Impact of Misleading Statistics
Tools of the Trade
Statistics: More than Just Numbers
Grabbing Some Basic Statistical Jargon
Number-Crunching Basics
Getting the Picture: Charts and Graphs
Getting Graphic with Statistics
Getting a Piece of the Pie Chart
Raising the Bar on Bar Graphs
Putting Statistics on the Table
Keeping Pace with Time Charts
Picturing Data with a Histogram
Means, Medians, and More
Summing Up Data with Statistics
Summarizing Categorical Data
Summarizing Numerical Data
Determining the Odds
What Are the Chances? Understanding Probability
Taking a Chance with Probability
Gaining the Edge: Probability Basics
Interpreting Probability
Avoiding Probability Misconceptions
Connecting Probability with Statistics
Gambling to Win
Betting on the House: Why Casinos Stay in Business
Knowing a Little Probability Helps a Lotto
Wading through the Results
Measures of Relative Standing
Straightening Out the Bell Curve
Converting to a Standard Score
Sizing Up Results Using Percentiles
Caution: Sample Results Vary!
Expecting Sample Results to Vary
Measuring Variability in Sample Results
Examining Factors That Influence Variability in Sample Results
Leaving Room for a Margin of Error
Exploring the Importance of That Plus or Minus
Finding the Margin of Error: A General Formula
Determining the Impact of Sample Size
Limiting the Margin of Error
Guesstimating with Confidence
The Business of Estimation: Interpreting and Evaluating Confidence Intervals
Realizing That Not All Estimates Are Created Equal
Linking a Statistic to a Parameter
Making Your Best Guesstimate
Interpreting Results with Confidence
Spotting Misleading Confidence Intervals
Calculating Accurate Confidence Intervals
Calculating a Confidence Interval
Choosing a Confidence Level
Zooming In on Width
Factoring In the Sample Size
Counting On Population Variability
Commonly Used Confidence Intervals: Formulas and Examples
Calculating the Confidence Interval for the Population Mean
Determining the Confidence Interval for the Population Proportion
Developing a Confidence Interval for the Difference of Two Means
Coming Up with the Confidence Interval for the Difference of Two Proportions
Putting a Claim to the (Hypothesis) Test
Claims, Tests, and Conclusions
Responding to Claims: Some Do's and Don'ts
Doing a Hypothesis Test
Weighing the Evidence and Making Decisions: P-Values
Knowing That You Could Be Wrong: Errors in Testing
Walking through a Hypothesis Test: The Big Picture
Commonly Used Hypothesis Tests: Formulas and Examples
Testing One Population Mean
Testing One Population Proportion
Comparing Two (Separate) Population Averages
Testing for an Average Difference (Paired Data)
Comparing Two Population Proportions
Statistical Studies: The Inside Scoop
Polls, Polls, and More Polls
Recognizing the Impact of Polls
Behind the Scenes: The Ins and Outs of Surveys
Experiments: Medical Breakthroughs or Misleading Results?
Determining What Sets Experiments Apart
Designing a Good Experiment
Making Informed Decisions about Experiments
Looking for Links: Correlations and Associations
Picturing the Relationship: Plots and Charts
Quantifying the Relationship: Correlations and Other Measures
Explaining the Relationship: Association and Correlation versus Causation
Making Predictions: Regression and Other Methods
Statistics and Toothpaste: Quality Control
Full-Filling Expectations
Squeezing Quality out of a Toothpaste Tube
The Part of Tens
Ten Criteria for a Good Survey
The Target Population Is Well Defined
The Sample Matches the Target Population
The Sample Is Randomly Selected
The Sample Size Is Large Enough
Good Follow-Up Minimizes Non-Response
The Type of Survey Used Is Appropriate
The Questions Are Well Worded
The Survey Is Properly Timed
The Survey Personnel Are Well Trained
The Survey Answers the Original Question
Ten Common Statistical Mistakes
Misleading Graphs
Biased Data
No Margin of Error
Non-Random Samples
Missing Sample Sizes
Misinterpreted Correlations
Confounding Variables
Botched Numbers
Selectively Reporting Results
The Almighty Anecdote
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