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Explains how statistics are applied in our everyday lives. This book draws on diverse examples like how pills are manufactured, elections are forecast, and chess tournaments are structured. It familiarizes readers with variables, means, medians, scales of measurement, sampling, estimating, and other stock-in-trade tools of the statistician.

Tabla de contenidos provista por Syndetics

• Introduction(p. xiii)
• Acknowledgments(p. xv)
• Chapter I Why Statistics(p. 1)
• Communication(p. 1)
• Dehydrating the Primordial Soup(p. 3)
• Seeking Truth(p. 6)
• Chapter II What Is Statistics(p. 9)
• A Height of Science(p. 9)
• Changing Times(p. 10)
• Nature's Will to Mediocrity(p. 13)
• Chapter III Names and Numbers(p. 17)
• Telling a Story(p. 17)
• Variables(p. 19)
• On the Unfinished Nature of Statistical Stories(p. 22)
• Chapter IV Scales of Measurement(p. 25)
• Dichotomous Variables(p. 25)
• Categorical Scales(p. 27)
• Ordinal Scales(p. 30)
• Interval Scales(p. 32)
• Ratio Scales(p. 33)
• Summarizing and a Bit More(p. 35)
• Chapter V Error(p. 39)
• What We Seek and What We Get(p. 39)
• Getting Answers to Questions(p. 41)
• Systematic and Random Errors(p. 44)
• Chapter VI Central Tendency(p. 47)
• What We Do(p. 47)
• The Mean(p. 50)
• The Median(p. 52)
• The Mode(p. 57)
• Ordinal Scales and Central Tendency(p. 64)
• Volume Discounts(p. 65)
• A Final Word(p. 66)
• Chapter VII Variation(p. 69)
• From Specifics to Generalities and Back(p. 69)
• Distance(p. 70)
• References(p. 71)
• Measures of Variation(p. 74)
• Chapter VIII Putting Distance in Context(p. 81)
• Relative Distance(p. 81)
• The Standard Score(p. 82)
• A Fly in the Ointment(p. 85)
• Percentiles(p. 88)
• Relative Standing and Relative Distance(p. 92)
• A Peek Ahead(p. 94)
• A Robust Measure of Spread(p. 94)
• Chapter IX Descriptive Statistics: A Review and More(p. 97)
• Why We Do It(p. 97)
• How We Do It: Dealing with Error(p. 98)
• How We Do It: Descriptive Statistics(p. 99)
• The Abstract Nature of Statistical Description(p. 101)
• Chapter X The Significance of Variation(p. 105)
• Variation Exists(p. 105)
• Variation as Uncertainty(p. 106)
• Variation as Information(p. 109)
• The Relationship between Uncertainty and Information(p. 110)
• Chapter XI Uncertainty, Error, and Uniqueness(p. 113)
• Statistical Uncertainty(p. 113)
• Distance, Uncertainty, and Error(p. 114)
• Prediction(p. 115)
• From Prediction Back to Description(p. 118)
• Terminology(p. 119)
• Chapter XII From Description to Inference(p. 121)
• Making Connections(p. 121)
• From Description to Explanation(p. 126)
• The Nature of Statistical Explanation(p. 127)
• Chapter XIII Reliability and Validity(p. 129)
• From the Lab to Life(p. 129)
• Getting It Right(p. 130)
• What Needs Assuming(p. 131)
• Reliability(p. 133)
• Making a Distinction(p. 134)
• Validity(p. 135)
• Another Example(p. 137)
• A Note on Assessing Validity and Reliability(p. 139)
• Chapter XIV Samples and Populations(p. 141)
• Generalization(p. 141)
• Language(p. 142)
• Bounding Generalization(p. 142)
• From Samples to Populations(p. 145)
• Statistical versus Everyday Terminology(p. 146)
• Summarizing(p. 149)
• Chapter XV Estimating Right(p. 151)
• Of Rats and Men(p. 151)
• Bias(p. 153)
• Knowing the Truth(p. 154)
• Back to Ricky(p. 154)
• Some Important Notes(p. 155)
• Sampling Error(p. 156)
• Measurement Error(p. 158)
• Miscellaneous Errors(p. 159)
• Summary(p. 159)
• Chapter XVI Models(p. 161)
• What They Are Not(p. 161)
• Figuring Out Nature(p. 162)
• From Sample to Population(p. 163)
• Infinity: A Beginning(p. 167)
• A Different Way of Looking(p. 167)
• Probability(p. 170)
• Area(p. 172)
• Finally a Model(p. 174)
• Chapter XVII Using Models--A Start(p. 179)
• Gambling(p. 179)
• George Brush(p. 180)
• A Fine Point(p. 186)
• Chapter XVIII Another Model(p. 189)
• Charging the Cavalry(p. 189)
• A Different Way of Looking(p. 190)
• Poisson(p. 192)
• A Note on the Poisson(p. 195)
• Chapter XIX What, Then, Are Models?(p. 197)
• Mathematics(p. 198)
• An Example(p. 200)
• What, Then, Are Models?(p. 202)
• Chapter XX Sampling Distributions(p. 203)
• The Number Six(p. 203)
• What Is Happening Here?(p. 208)
• Tossing a Die(p. 210)
• A Note(p. 213)
• Terminology(p. 213)
• Why Is This Happening?(p. 215)
• Chapter XXI Confidence Intervals(p. 217)
• Sampling Error(p. 217)
• A (Partial) Solution(p. 218)
• Distributions and Distributions(p. 219)
• Back to Confidence Intervals(p. 221)
• Yet Another Difficulty(p. 223)
• A Brief Summary(p. 224)
• An Application(p. 224)
• Some Additional Issues(p. 225)
• Chapter XXII Data and Decisions: An Introduction(p. 227)
• Back Confidence Intervals(p. 230)
• Formalities(p. 232)
• Chapter XXIII Risks and Rewards(p. 235)
• Models Revisited(p. 235)
• On the Difference between Description and Inference(p. 237)
• Risks and Rewards(p. 238)
• Conventional Wisdom(p. 240)
• On Proving the Null(p. 243)
• Where Does the Null Come from?(p. 244)
• A Summary(p. 244)
• Chapter XXIV Distance Revisited(p. 245)
• Questions and Answers(p. 245)
• Another Kind of Sampling Distribution(p. 246)
• Still Another Method(p. 247)
• Factors Affecting Power(p. 250)
• Chapter XXV Understanding(p. 253)
• Turning Weakness into Strength(p. 257)
• Formalizing(p. 258)
• Quantifying Confusion and Understanding(p. 262)
• Statistical Explanation(p. 263)
• Afterword(p. 265)
• References(p. 267)
• Glossary(p. 271)
• Index(p. 281)

Notas de autor provistas por Syndetics

Joseph Tal, Ph.D. is Managing Director of TechnoStat Ltd., a company based in Israel that provides statistical services for clinical trials, marketing research and industrial engineering. He also conducts a popular series of statistics workshops for non-statisticians in Israel and England. Dr. Tal has worked as a statistician and clinical psychologist and has taught both at Northwestern University