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Statistics for Dummies »

Book cover image of Statistics for Dummies by Deborah Rumsey

Authors: Deborah Rumsey
ISBN-13: 9780764554230, ISBN-10: 0764554239
Format: Paperback
Publisher: Wiley, John & Sons, Incorporated
Date Published: August 2003
Edition: (Non-applicable)

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Author Biography: Deborah Rumsey

Deborah Rumsey earned her Ph.D. in statistics from Ohio State University (OSU) in 1993. Upon graduating, she joined the faculty in the Department of Statistics at Kansas State University, winning the distinguished Presidential Teaching Award and earning tenure and promotion in 1998. In 2000, she returned to OSU as the Director of the Mathematics and Statistics Learning Center, where she is today. Deb is the Editor of the “Teaching Bits” of the Journal of Statistics Education; she has also published papers and given professional presentations on the subject of statistics education, with a particular emphasis on statistical literacy (skills for understanding statistics in everyday life and the workplace) and immersive learning environments (environments that promote students’ discovery of ideas on their own). Her passions include fishing, bird watching, and Ohio State Buckeye football (not necessarily in that order).

Book Synopsis

In the numbers explosion all around us in our modern-day dealings, the buzzword is data, as in, “Do you have any data to support your claim?” “The data supported the original hypothesis that . . .” and “The data bear this out. . . .” But the field of statistics is not just about data. Statistics is the entire process involved in gathering evidence to answer questions about the world, in cases where that evidence happens to be numerical data.

Statistics For Dummies is for everyone who wants to sort through and evaluate the incredible amount of statistical information that comes to them on a daily basis. (You know the stuff: charts, graphs, tables, as well as headlines that talk about the results of the latest poll, survey, experiment, or other scientific study.) This book arms you with the ability to decipher and make important decisions about statistical results, being ever aware of the ways in which people can mislead you with statistics. Get the inside scoop on number-crunching nuances, plus insight into how you can

  • Determine the odds
  • Calculate a standard score
  • Find the margin of error
  • Recognize the impact of polls
  • Establish criteria for a good survey
  • Make informed decisions about experiments

This down-to-earth reference is chock-full of real examples from real sources that are relevant to your everyday life: from the latest medical breakthroughs, crime studies, and population trends to surveys on Internet dating, cell phone use, and the worst cars of the millennium. Statistics For Dummies departs from traditional statistics texts, references, supplement books, andstudy guides in the following ways:

  • Practical and intuitive explanations of statistical concepts, ideas, techniques, formulas, and calculations.
  • Clear and concise step-by-step procedures that intuitively explain how to work through statistics problems.
  • Upfront and honest answers to your questions like, “What does this really mean?” and “When and how I will ever use this?”

Chances are, Statistics For Dummies will be your No. 1 resource for discovering how numerical data figures into your corner of the universe.

Table of Contents

Introduction1
About This Book1
Conventions Used in This Book2
Foolish Assumptions2
How This Book Is Organized3
Icons Used in This Book5
Where to Go from Here6
Part IVital Statistics about Statistics7
Chapter 1The Statistics of Everyday Life9
Statistics and the Media Blitz: More Questions than Answers?9
Using Statistics at Work17
Chapter 2Statistics Gone Wrong21
Taking Control: So Many Numbers, So Little Time21
Detecting Errors, Exaggerations, and Just Plain Lies22
Feeling the Impact of Misleading Statistics36
Chapter 3Tools of the Trade39
Statistics: More than Just Numbers39
Grabbing Some Basic Statistical Jargon41
Part IINumber-Crunching Basics59
Chapter 4Getting the Picture: Charts and Graphs61
Getting Graphic with Statistics61
Getting a Piece of the Pie Chart62
Raising the Bar on Bar Graphs72
Putting Statistics on the Table76
Keeping Pace with Time Charts83
Picturing Data with a Histogram86
Chapter 5Means, Medians, and More97
Summing Up Data with Statistics97
Summarizing Categorical Data98
Summarizing Numerical Data101
Part IIIDetermining the Odds115
Chapter 6What Are the Chances? Understanding Probability117
Taking a Chance with Probability117
Gaining the Edge: Probability Basics119
Interpreting Probability124
Avoiding Probability Misconceptions124
Connecting Probability with Statistics127
Chapter 7Gambling to Win131
Betting on the House: Why Casinos Stay in Business131
Knowing a Little Probability Helps a Lotto133
Part IVWading through the Results141
Chapter 8Measures of Relative Standing143
Straightening Out the Bell Curve143
Converting to a Standard Score151
Sizing Up Results Using Percentiles156
Chapter 9Caution: Sample Results Vary!161
Expecting Sample Results to Vary161
Measuring Variability in Sample Results162
Examining Factors That Influence Variability in Sample Results174
Chapter 10Leaving Room for a Margin of Error177
Exploring the Importance of That Plus or Minus177
Finding the Margin of Error: A General Formula179
Determining the Impact of Sample Size184
Limiting the Margin of Error186
Part VGuesstimating with Confidence189
Chapter 11The Business of Estimation: Interpreting and Evaluating Confidence Intervals191
Realizing That Not All Estimates Are Created Equal192
Linking a Statistic to a Parameter193
Making Your Best Guesstimate194
Interpreting Results with Confidence194
Spotting Misleading Confidence Intervals195
Chapter 12Calculating Accurate Confidence Intervals197
Calculating a Confidence Interval197
Choosing a Confidence Level199
Zooming In on Width200
Factoring In the Sample Size201
Counting On Population Variability203
Chapter 13Commonly Used Confidence Intervals: Formulas and Examples205
Calculating the Confidence Interval for the Population Mean205
Determining the Confidence Interval for the Population Proportion207
Developing a Confidence Interval for the Difference of Two Means208
Coming Up with the Confidence Interval for the Difference of Two Proportions210
Part VIPutting a Claim to the (Hypothesis) Test213
Chapter 14Claims, Tests, and Conclusions215
Responding to Claims: Some Do's and Don'ts216
Doing a Hypothesis Test219
Weighing the Evidence and Making Decisions: P-Values223
Knowing That You Could Be Wrong: Errors in Testing226
Walking through a Hypothesis Test: The Big Picture229
Chapter 15Commonly Used Hypothesis Tests: Formulas and Examples237
Testing One Population Mean238
Testing One Population Proportion239
Comparing Two (Separate) Population Averages240
Testing for an Average Difference (Paired Data)242
Comparing Two Population Proportions245
Part VIIStatistical Studies: The Inside Scoop249
Chapter 16Polls, Polls, and More Polls251
Recognizing the Impact of Polls251
Behind the Scenes: The Ins and Outs of Surveys256
Chapter 17Experiments: Medical Breakthroughs or Misleading Results?267
Determining What Sets Experiments Apart268
Designing a Good Experiment269
Making Informed Decisions about Experiments279
Chapter 18Looking for Links: Correlations and Associations281
Picturing the Relationship: Plots and Charts282
Quantifying the Relationship: Correlations and Other Measures287
Explaining the Relationship: Association and Correlation versus Causation291
Making Predictions: Regression and Other Methods291
Chapter 19Statistics and Toothpaste: Quality Control297
Full-Filling Expectations297
Squeezing Quality out of a Toothpaste Tube299
Part VIIIThe Part of Tens309
Chapter 20Ten Criteria for a Good Survey311
The Target Population Is Well Defined311
The Sample Matches the Target Population312
The Sample Is Randomly Selected313
The Sample Size Is Large Enough313
Good Follow-Up Minimizes Non-Response314
The Type of Survey Used Is Appropriate315
The Questions Are Well Worded316
The Survey Is Properly Timed317
The Survey Personnel Are Well Trained318
The Survey Answers the Original Question319
Chapter 21Ten Common Statistical Mistakes321
Misleading Graphs321
Biased Data324
No Margin of Error325
Non-Random Samples326
Missing Sample Sizes327
Misinterpreted Correlations327
Confounding Variables328
Botched Numbers329
Selectively Reporting Results330
The Almighty Anecdote331
AppendixSources333
Index341

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