Statistics For Dummies?

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Format: Paperback
Pub. Date: 2003-09-01
Publisher(s): For Dummies
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Summary

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, and study 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.

Author Biography

<b>Deborah Rumsey</b> 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 &#8220;Teaching Bits&#8221; of the <i>Journal of Statistics Education;</i> 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&#8217; discovery of ideas on their own). Her passions include fishing, bird watching, and Ohio State Buckeye football (not necessarily in that order).

Table of Contents

Introductionp. 1
About This Bookp. 1
Conventions Used in This Bookp. 2
Foolish Assumptionsp. 2
How This Book Is Organizedp. 3
Icons Used in This Bookp. 5
Where to Go from Herep. 6
Vital Statistics about Statisticsp. 7
The Statistics of Everyday Lifep. 9
Statistics and the Media Blitz: More Questions than Answers?p. 9
Using Statistics at Workp. 17
Statistics Gone Wrongp. 21
Taking Control: So Many Numbers, So Little Timep. 21
Detecting Errors, Exaggerations, and Just Plain Liesp. 22
Feeling the Impact of Misleading Statisticsp. 36
Tools of the Tradep. 39
Statistics: More than Just Numbersp. 39
Grabbing Some Basic Statistical Jargonp. 41
Number-Crunching Basicsp. 59
Getting the Picture: Charts and Graphsp. 61
Getting Graphic with Statisticsp. 61
Getting a Piece of the Pie Chartp. 62
Raising the Bar on Bar Graphsp. 72
Putting Statistics on the Tablep. 76
Keeping Pace with Time Chartsp. 83
Picturing Data with a Histogramp. 86
Means, Medians, and Morep. 97
Summing Up Data with Statisticsp. 97
Summarizing Categorical Datap. 98
Summarizing Numerical Datap. 101
Determining the Oddsp. 115
What Are the Chances? Understanding Probabilityp. 117
Taking a Chance with Probabilityp. 117
Gaining the Edge: Probability Basicsp. 119
Interpreting Probabilityp. 124
Avoiding Probability Misconceptionsp. 124
Connecting Probability with Statisticsp. 127
Gambling to Winp. 131
Betting on the House: Why Casinos Stay in Businessp. 131
Knowing a Little Probability Helps a Lottop. 133
Wading through the Resultsp. 141
Measures of Relative Standingp. 143
Straightening Out the Bell Curvep. 143
Converting to a Standard Scorep. 151
Sizing Up Results Using Percentilesp. 156
Caution: Sample Results Vary!p. 161
Expecting Sample Results to Varyp. 161
Measuring Variability in Sample Resultsp. 162
Examining Factors That Influence Variability in Sample Resultsp. 174
Leaving Room for a Margin of Errorp. 177
Exploring the Importance of That Plus or Minusp. 177
Finding the Margin of Error: A General Formulap. 179
Determining the Impact of Sample Sizep. 184
Limiting the Margin of Errorp. 186
Guesstimating with Confidencep. 189
The Business of Estimation: Interpreting and Evaluating Confidence Intervalsp. 191
Realizing That Not All Estimates Are Created Equalp. 192
Linking a Statistic to a Parameterp. 193
Making Your Best Guesstimatep. 194
Interpreting Results with Confidencep. 194
Spotting Misleading Confidence Intervalsp. 195
Calculating Accurate Confidence Intervalsp. 197
Calculating a Confidence Intervalp. 197
Choosing a Confidence Levelp. 199
Zooming In on Widthp. 200
Factoring In the Sample Sizep. 201
Counting On Population Variabilityp. 203
Commonly Used Confidence Intervals: Formulas and Examplesp. 205
Calculating the Confidence Interval for the Population Meanp. 205
Determining the Confidence Interval for the Population Proportionp. 207
Developing a Confidence Interval for the Difference of Two Meansp. 208
Coming Up with the Confidence Interval for the Difference of Two Proportionsp. 210
Putting a Claim to the (Hypothesis) Testp. 213
Claims, Tests, and Conclusionsp. 215
Responding to Claims: Some Do's and Don'tsp. 216
Doing a Hypothesis Testp. 219
Weighing the Evidence and Making Decisions: P-Valuesp. 223
Knowing That You Could Be Wrong: Errors in Testingp. 226
Walking through a Hypothesis Test: The Big Picturep. 229
Commonly Used Hypothesis Tests: Formulas and Examplesp. 237
Testing One Population Meanp. 238
Testing One Population Proportionp. 239
Comparing Two (Separate) Population Averagesp. 240
Testing for an Average Difference (Paired Data)p. 242
Comparing Two Population Proportionsp. 245
Statistical Studies: The Inside Scoopp. 249
Polls, Polls, and More Pollsp. 251
Recognizing the Impact of Pollsp. 251
Behind the Scenes: The Ins and Outs of Surveysp. 256
Experiments: Medical Breakthroughs or Misleading Results?p. 267
Determining What Sets Experiments Apartp. 268
Designing a Good Experimentp. 269
Making Informed Decisions about Experimentsp. 279
Looking for Links: Correlations and Associationsp. 281
Picturing the Relationship: Plots and Chartsp. 282
Quantifying the Relationship: Correlations and Other Measuresp. 287
Explaining the Relationship: Association and Correlation versus Causationp. 291
Making Predictions: Regression and Other Methodsp. 291
Statistics and Toothpaste: Quality Controlp. 297
Full-Filling Expectationsp. 297
Squeezing Quality out of a Toothpaste Tubep. 299
The Part of Tensp. 309
Ten Criteria for a Good Surveyp. 311
The Target Population Is Well Definedp. 311
The Sample Matches the Target Populationp. 312
The Sample Is Randomly Selectedp. 313
The Sample Size Is Large Enoughp. 313
Good Follow-Up Minimizes Non-Responsep. 314
The Type of Survey Used Is Appropriatep. 315
The Questions Are Well Wordedp. 316
The Survey Is Properly Timedp. 317
The Survey Personnel Are Well Trainedp. 318
The Survey Answers the Original Questionp. 319
Ten Common Statistical Mistakesp. 321
Misleading Graphsp. 321
Biased Datap. 324
No Margin of Errorp. 325
Non-Random Samplesp. 326
Missing Sample Sizesp. 327
Misinterpreted Correlationsp. 327
Confounding Variablesp. 328
Botched Numbersp. 329
Selectively Reporting Resultsp. 330
The Almighty Anecdotep. 331
Sourcesp. 333
Indexp. 341
Table of Contents provided by Ingram. All Rights Reserved.

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