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Seeing Through Statistics,9780534357863

Seeing Through Statistics

by
Edition:
2nd
ISBN13:

9780534357863

ISBN10:
0534357865
Format:
Paperback
Pub. Date:
2/19/1999
Publisher(s):
Duxbury Press
List Price: $62.67

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What version or edition is this?
This is the 2nd edition with a publication date of 2/19/1999.
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  • The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any CDs, lab manuals, study guides, etc.

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Summary

This second edition of Jessica Utt's popular book develops statistical literacy and critical thinking through real-world applications, with an emphasis on ideas, not calculations. Utts focuses on two central concepts--uncertainty and data. Ideas are introduced in interesting applied and real contexts, without using an abundance of technicalities and calculations which only serve to confuse students.

Table of Contents

PART 1 FINDING DATA IN LIFE 1(104)
CHAPTER 1 The Benefits and Risks of Using Statistics
2(12)
1.1 Statistics
3(1)
Case Study 1.1 Heart or Hypothalamus?
3(1)
1.2 Detecting Patterns and Relationships
4(3)
Case Study 1.2 Does Aspirin Prevent Heart Attacks?
6(1)
1.3 Don't Be Deceived by Improper Use of Statistics
7(2)
Case Study 1.3 A Mistaken Accusation of Cheating
9(1)
1.4 Summary and Conclusions
9(1)
Exercises
10(2)
Mini-Projects
12(1)
References
13(1)
CHAPTER 2 Reading the News
14(17)
2.1 The Educated Consumer of Data
15(1)
2.2 How to Be a Statistics Sleuth: Seven Critical Components
15(3)
2.3 Four Hypothetical Examples of Bad Reports
18(7)
2.4 Planning Your Own Study: Defining the Components in Advance
25(2)
Case Study 2.1 Brooks Shoes Brings Flawed Study to Court
26(1)
Exercises
27(3)
Mini-Projects
30(1)
References
30(1)
CHAPTER 3 Measurements, Mistakes, and Misunderstandings
31(17)
3.1 Simple Measures Don't Exist
32(1)
3.2 It's All in the Wording
32(3)
Case Study 3.1 No Opinion of Your Own? Let Politics Decide
35(1)
3.3 Open or Closed Questions: Should Choices Be Given?
35(2)
3.4 Defining What Is Being Measured
37(3)
Case Study 3.2 Questions in Advertising
39(1)
3.5 Defining a Common Language
40(4)
Exercises
44(2)
Mini-Projects
46(1)
References
47(1)
CHAPTER 4 How to Get a Good Sample
48(22)
4.1 Common Research Strategies
49(2)
4.2 Defining a Common Language
51(1)
4.3 The Beauty of Sampling
52(2)
4.4 Simple Random Sampling
54(1)
4.5 Other Sampling Methods
55(3)
4.6 Difficulties and Disasters in Sampling
58(5)
Case Study 4.1 The Infamous Literary Digest Poll of 1936
63(1)
Exercises
63(5)
Mini-Projects
68(1)
References
68(2)
CHAPTER 5 Experiments and Observational Studies
70(22)
5.1 Defining a Common Language
71(3)
5.2 Designing a Good Experiment
74(3)
Case Study 5.1 Quitting Smoking with Nicotine Patches
76(1)
5.3 Difficulties and Disasters in Experiments
77(4)
Case Study 5.2 Exercise Yourself to Sleep
81(1)
5.4 Designing a Good Observational Study
81(3)
Case Study 5.3 Baldness and Heart Attacks
81(3)
5.5 Difficulties and Disasters in Observational Studies
84(2)
Exercises
86(4)
Mini-Projects
90(1)
References
90(2)
CHAPTER 6 Getting the Big Picture
92(13)
6.1 Final Questions
92(12)
Case Study 6.1 Mozart, Relaxation, and Performance on Spatial Tasks
93(2)
Case Study 6.2 Meditation and Aging
95(3)
Case Study 6.3 Drinking, Driving, and the Supreme Court
98(3)
Case Study 6.4 Smoking During Pregnancy and Child's IQ
101(2)
Case Study 6.5 For Class Discussion: Guns and Homicides at Home
103(1)
References
104(1)
PART 2 FINDING LIFE IN DATA 105(150)
CHAPTER 7 Summarizing and Displaying Measurement Data
106(21)
7.1 Turning Data into Information
107(1)
7.2 The Total Picture: Stemplots and Histograms
108(7)
7.3 Five Useful Numbers: A Summary
115(1)
7.4 Boxplots
116(3)
7.5 Traditional Measures: Mean, Variance, and Standard Deviation
119(4)
Case Study 7.1 Detecting Exam Cheating with a Histogram
122(1)
For Those Who Like Formulas
123(1)
Exercises
123(3)
Mini-Projects
126(1)
References
126(1)
CHAPTER 8 Bell-Shaped Curves and Other Shapes
127(13)
8.1 Populations, Frequency Curves, and Proportions
128(2)
8.2 The Pervasiveness of Normal Curves
130(1)
8.3 Percentiles and Standardized Scores
130(4)
8.4 z-Scores and Familiar Intervals
134(1)
For Those Who Like Formulas
135(1)
Exercises
136(3)
References
139(1)
CHAPTER 9 Plots, Graphs, and Pictures
140(17)
9.1 Well-Designed Statistical Pictures
141(1)
9.2 Pictures of Categorical Data
141(3)
9.3 Pictures of Measurement Variables
144
9.4 Difficulties and Disasters in Plots, Graphs, and Pictures
140
9.5 A Checklist for Statistical Pictures
151(2)
Case Study 9.1 Time to Panic about Illicit Drug Use?
152(1)
Exercises
153(3)
Mini-Projects
156(1)
References
156(1)
CHAPTER 10 Relationships Between Measurement Variables
157(20)
10.1 Statistical Relationships
158(1)
10.2 Strength versus Statistical Significance
159(1)
10.3 Measuring Strength Through Correlation
160(4)
10.4 Specifying Linear Relationships with Regression
164(8)
Case Study 10.1 Are Attitudes about Love and Romance Hereditary?
168(2)
Case Study 10.2 A Weighty Issue: Women Want Less, Men Want More
170(2)
For Those Who Like Formulas
172(1)
Exercises
172(3)
Mini-Projects
175(1)
References
175(2)
CHAPTER 11 Relationships Can Be Deceiving
177(18)
11.1 Illegitimate Correlations
178(5)
11.2 Legitimate Correlation Does Not Imply Causation
183(3)
11.3 Some Reasons for Relationships Between Variables
186(3)
11.4 Confirming Causation
189(1)
Exercises
190(4)
Mini-Projects
194(1)
References
194(1)
CHAPTER 12 Relationships Between Categorical Variables
195(31)
12.1 Displaying Relationships Between Categorical Variables
196(3)
12.2 Assessing the Statistical Significance of a 2 X 2 Table
199(8)
Case Study 12.1 Extrasensory Perception Works Best with Movies
206(1)
12.3 Relative Risk, Increased Risk, and Odds
207(4)
12.4 Misleading Statistics about Risk
211(2)
12.5 Simpson's Paradox: The Missing Third Variable
213(4)
Case Study 12.2 Assessing Discrimination in Hiring and Firing
215(2)
For Those Who Like Formulas
217(1)
Exercises
218(6)
Mini-Projects
224(1)
References
224(2)
CHAPTER 13 Reading the Economic News
226(15)
13.1 Cost of Living: The Consumer Price Index
227(3)
13.2 Uses of the Consumer Price Index
230(2)
13.3 Criticisms of the Consumer Price Index
232(2)
13.4 Economic Indicators
234(3)
Case Study 13.1 Did Wages Really Go Up in the Reagan-Bush Years?
236(1)
Exercises
237(2)
Mini-Projects
239(1)
References
240(1)
CHAPTER 14 Understanding and Reporting Trends over Time
241(14)
14.1 Time Series
242(1)
14.2 Components of Time Series
243(3)
14.3 Seasonal Adjustments: Reporting the Consumer Price Index
246(2)
14.4 Cautions and Checklist
248(3)
Case Study 14.1 If You're Looking for a Job, Try May or October
249(2)
Exercises
251(2)
Mini-Projects
253(1)
References
253(2)
PART 3 UNDERSTANDING UNCERTAINTY IN LIFE 255(60)
CHAPTER 15 Understanding Probability and Long-Term Expectations
256(23)
15.1 Probability
257(1)
15.2 The Relative-Frequency Interpretation
257(3)
15.3 The Personal-Probability Interpretation
260(1)
15.4 Applying Some Simple Probability Rules
261(3)
15.5 When Will It Happen?
264(3)
15.6 Long-Term Gains, Losses, and Expectations
267(4)
Case Study 15.1 Birthdays and Death Days--Is There a Connection?
270(1)
For Those Who Like Formulas
271(1)
Exercises
271(6)
Mini-Projects
277(1)
References
277(2)
CHAPTER 16 Psychological Influences on Personal Probability
279(17)
16.1 Revisiting Personal Probability
280(1)
16.2 Equivalent Probabilities; Different Decisions
280(2)
16.3 How Personal Probabilities Can Be Distorted
282(4)
16.4 Optimism, Reluctance to Change, and Overconfidence
286(2)
16.5 Calibrating Personal Probabilities of Experts
288(2)
Case Study 16.1 Calibrating Weather Forecasters and Physicians
289(1)
16.6 Tips for Improving Your Personal Probabilities and Judgments
290(1)
Exercises
291(3)
Mini-Projects
294(1)
References
294(2)
CHAPTER 17 When Intuition Differs from Relative Frequency
296(19)
17.1 Revisiting Relative Frequency
297(1)
17.2 Coincidences
297(4)
17.3 The Gambler's Fallacy
301(1)
17.4 Confusion of the Inverse
302(3)
Case Study 17.1 Streak Shooting in Basketball: Reality or Illusion?
304(1)
17.5 Using Expected Values to Make Wise Decisions
305(4)
Case Study 17.2 How Bad Is a Bet on the British Open?
307(2)
For Those Who Like Formulas
309(1)
Exercises
309(3)
Mini-Projects
312(1)
References
313(2)
PART 4 MAKING JUDGMENTS FROM SURVEYS AND EXPERIMENTS 315(138)
CHAPTER 18 The Diversity of Samples from the Same Population
316(19)
18.1 Setting the Stage
317(1)
18.2 What to Expect of Sample Proportions
317(5)
18.3 What to Expect of Sample Means
322(4)
18.4 What to Expect in Other Situations
326(2)
Case Study 18.1 Do Americans Really Vote When They Say They Do?
327(1)
For Those Who Like Formulas
328(1)
Exercises
329(3)
Mini-Projects
332(2)
References
334(1)
CHAPTER 19 Estimating Proportions with Confidence
335(16)
19.1 Confidence Intervals
336(1)
19.2 Three Examples of Confidence Intervals from the Media
336(3)
19.3 Constructing a Confidence Interval for a Proportion
339(6)
Case Study 19.1 A Winning Confidence Interval Loses in Court
344(1)
For Those Who Like Formulas
345(1)
Exercises
345(4)
Mini-Projects
349(1)
References
350(1)
CHAPTER 20 The Role of Confidence Intervals in Research
351(20)
20.1 Confidence Intervals for Population Means
352(3)
20.2 Confidence Intervals for the Difference Between Two Means
355(2)
20.3 Revisiting Case Studies: How Journals Present Confidence Intervals
357(5)
20.4 Understanding Any Confidence Interval
362(2)
Case Study 20.1 Premenstrual Syndrome? Try Calcium
363(1)
For Those Who Like Formulas
364(1)
Exercises
365(3)
Mini-Projects
368(1)
References
369(2)
CHAPTER 21 Rejecting Chance--Testing Hypotheses in Research
371(17)
21.1 Using Data to Make Decisions
372(2)
21.2 The Basic Steps for Testing Hypotheses
374(3)
21.3 What Can Go Wrong: The Two Types of Errors
377(6)
Case Study 21.1 Testing for the Existence of Extrasensory Perception
380(3)
Exercises
383(3)
Mini-Projects
386(1)
References
387(1)
CHAPTER 22 Hypothesis Testing--Examples and Case Studies
388(19)
22.1 How Hypothesis Tests Are Reported in the News
389(1)
22.2 Testing Hypotheses about Proportions and Means
390(3)
22.3 Revisiting Chi-Squared Tests for Categorical Variables
393(2)
22.4 Revisiting Case Studies: How Journals Present Hypothesis Tests
395(5)
Case Study 22.1 An Interpretation of a p-Value Not Fit to Print
398(2)
For Those Who Like Formulas
400(1)
Exercises
401(4)
Mini-Projects
405(1)
References
406(1)
CHAPTER 23 Significance, Importance, and Undetected Differences
407(14)
23.1 Real Importance versus Statistical Significance
408(2)
23.2 The Role of Sample Size in Statistical Significance
410(1)
23.3 No Difference versus No Statistically Significant Difference
411(3)
Case Study 23.1 Seen a UFO? You May Be Healthier Than Your Friends
413(1)
23.4 A Summary of Warnings
414(2)
Case Study 23.2 Finding Loneliness on the Internet
415(1)
Exercises
416(3)
Mini-Projects
419(1)
References
420(1)
CHAPTER 24 Meta-Analysis: Resolving Inconsistencies across Studies
421(17)
24.1 The Need for Meta-Analysis
422(1)
24.2 Two Important Decisions for the Analyst
423(4)
Case Study 24.1 Smoking and Reduced Fertility
426(1)
24.3 Some Benefits of Meta-Analysis
427(2)
24.4 Criticisms of Meta-Analysis
429(5)
Case Study 24.2 Controversy over Mammograms
432(2)
Exercises
434(2)
Mini-Projects
436(1)
References
437(1)
CHAPTER 25 Putting What You Have Learned to the Test
438(15)
Case Study 25.1 Cranberry Juice and Bladder Infections
439(1)
Case Study 25.2 Children on the Go
440(1)
Case Study 25.3 It Really Is True about Aspirin
441(2)
Case Study 25.4 You Can Work and Get Your Exercise at the Same Time
443(1)
Case Study 25.5 Sex, Alcohol, and the First Date
443(1)
Case Study 25.6 Unpalatable Pate
444(1)
Case Study 25.7 Nursing Moms Can Exercise, Too
445(1)
Case Study 25.8 So You Thought Spinach Was Good for You?
446(2)
Case Study 25.9 Chill Out--Time to Move to Honolulu
448(2)
Case Study 25.10 So You Thought Hot Dogs Were Bad for You?
450(3)
References
451(2)
Solutions to Selected Exercises 453(4)
Index 457


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