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The Myth of Statistical Inference

Autor Michael C. Acree
en Limba Engleză Paperback – 6 iul 2022
This book proposes and explores the idea that the forced union of the aleatory and epistemic aspects of probability is a sterile hybrid, inspired and nourished for 300 years by a false hope of formalizing inductive reasoning, making uncertainty the object of precise calculation.  Because this is not really a possible goal, statistical inference is not, cannot be, doing for us today what we imagine it is doing for us.  It is for these reasons that statistical inference can be characterized as a myth.
The book is aimed primarily at social scientists, for whom statistics and statistical inference are a common concern and frustration. Because the historical development given here is not merely anecdotal, but makes clear the guiding ideas and ambitions that motivated the formulation of particular methods, this book offers an understanding of statistical inference which has not hitherto been available. It will also serve as a supplement to the standard statistics texts. Finally, general readers will find here an interesting study with implications far beyond statistics.  The development of statistical inference, to its present position of prominence in the social sciences, epitomizes a number of trends in Western intellectual history of the last three centuries, and the 11th chapter, considering the function of statistical inference in light of our needs for structure, rules, authority, and consensus in general, develops some provocative parallels, especially between epistemology and politics.
 
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Specificații

ISBN-13: 9783030732592
ISBN-10: 3030732592
Pagini: 464
Ilustrații: XV, 448 p. 6 illus.
Dimensiuni: 155 x 235 x 25 mm
Greutate: 0.7 kg
Ediția:1st ed. 2021
Editura: Springer
Locul publicării:Cham, Switzerland

Cuprins

1.       SYNOPSIS, BY WAY OF AUTOBIOGRAPHY . . . . . . . . . . . . . . .  . . . . . . . . . . . . . . .  1      The problem as I originally confronted it . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  . . 3
                    The place of statistics in the social sciences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  3
                    Statistical inference and its misconceptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  5
                    The root of the problem in the dualistic concept of probability . . . . . . . . . . . . . . . .  7
                How this book came about . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  9
                Some qualifications, objections, and implications . . . . . . . . . . . . . . . . . . . . . . . . . . .  12
                    Intervening developments . . . . . . . . . . . . . . . . . . . .  . . . . . . . . . . . . . . . . . . . . . . .  14
                    Some qualifications regarding the historical argument . . . . . . . . . . . . . . . . . . . . .   16
                    An Ad hominem ipsum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .   18
                    References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .    23
 
2.    THE PHILOSOPHICAL AND CULTURAL CONTEXT FOR THE EMERGENCE OF PROBABILITY AND STATISTICAL INFERENCE . . . . . . . . . . . . . . . . . . . . . . . . . .  28
           Brief excursus on historical cognitive change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
               Ancient Greece . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  29
               Medieval Europe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  31
               General observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  32
           The concept of skeuomorphosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
               Early technologies of change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
               The emergence of the market economy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
               Mathematical, mechanistic, and relativistic thinking . . . . . . . . . . . . . . . . . . . . . . .  36
               Scientific objectivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  37
           Some consequences for epistemology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
               The concept of sign . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
               The combinatorics of language and thought . . . . . . . . .  . . . . . . . . . . . . . . . . . . . . .40
               Causality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  42                Representation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
           Some psychological and cultural considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
               The emergence of self-consciousness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  47
               Polarizations, alignments, and projections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  49
                   Rejection of the feminine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  51
                   Mind and body . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  52
                   Public and private . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  54
                   The rejection of roots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  55
           Summary and preview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
           References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . 60
 
 3.   ORIGIN OF THE MODERN CONCEPT OF PROBABILITY . . . . .  . . . . . . . . . . . . .  68
           Why gambling per se didn’t lead to a mathematical theory of probability . . . . . . . . . 68
           The concept of probability before the 17th century . . . . . . . .  . . . . . . . . . . . . . . . . . .  70
           The calculus of expectation . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  74
           Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
           The Art of Conjecturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
               The law of large numbers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  82
               The metaphysical status of probability . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . 85
               One word, two scales . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
                   The scale of measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  86
                   The combination of evidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . .88
           Implications for future developments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  91
           References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  97
 
 4.   THE CLASSICAL THEORY OF STATISTICAL INFERENCE . . . . . . . . . . . . . . . .  102
           Bayes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  103
           Laplace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
           Criticism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
           References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . 113
 
 5.   NINETEENTH CENTURY DEVELOPMENTS IN STATISTICS . . . . . . . . . . . . . . . 115
           Descriptive statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  115
               The normal curve in astronomy . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . .  115
               Application of the normal curve to populations:  Quetelet . . . . . . . . . . . . . . . . . .  117
               Galton, Pearson, and the biometricians . . . . . . . .  . . . . . . . . . . . . . . . . . . . . . . . . . 121
           Precursors of significance testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  124
               Arbuthnot’s and Gavarret’s use of the binomial . . . . . . . . . . . . . . . . . . . . . . . . . .  124
               Probabilistic criteria for the rejection of discordant observations in astronomy . . 127
               The normal model and data in the social sciences . . . . . . . . . . . . . . . . . . . . . . . . . 130
               The pun on significance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
               Small data sets in agricultural research . . . .  . . . . . . . . . . . . . . . . . . . . . . . . . . . ..  133            References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  136
   6.   THE FREQUENCY THEORY OF PROBABILITY . . . . . . . . . . . . . . . . . .  . . . . . . . . 140
           The principle of indifference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
           The frequency theorists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  144                Venn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
               Peirce . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  146
               Richard von Mises . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
               Reichenbach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  . . . . . . . . . . .  151
               Popper . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  154
           The concept of randomness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156
           Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  160
           References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  161
 
 7.   THE FISHER AND NEYMAN-PEARSON THEORIES OF STATISTICAL
    INFERENCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  164
           Fisher . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  164            The Fisherian theory of statistical inference . . . . . . . . . . . . . . . . . . . . . . . . . . . .  . . . 167
               Maximum likelihood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  168
               Significance testing . . . . . . . . . . . . . .  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
                   Small-sample theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  170
                   The hypothetical infinite population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  171
                   Randomization tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
                   The success of significance testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  175
               Fiducial probability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  177
           Neyman and Pearson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  182
               Hypothesis testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  184
                   The concept of probability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187
                   Implications for statistical inference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  190
               Confidence intervals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  193
           Differences between the Fisher and Neyman-Pearson theories . . . . . . . . . . . . . . . . . 198
           References . . . . . . . . . .  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203  
 8.   BAYESIAN THEORIES OF PROBABILITY AND STATISTICAL INFERENCE .  210
           Logical theories of probability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .   210                Keynes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  210
               Jeffreys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215
               Jaynes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218
           Personalist theories of probability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220
               Ramsey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221
               De Finetti . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222
               Savage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  225
               Wald’s decision theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  227
           General structure of Bayesian inference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  228
           Criticism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  233
               The logical allocation of prior probabilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  233                The subjective allocation of prior probabilities . . . . . . . . . . . . . . . . . . . . . . . . . . . 236
               Subjectivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .238
           Putting theories to work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241
           References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . 243
 
 9.   STATISTICAL INFERENCE IN PSYCHOLOGICAL AND MEDICAL
RESEARCH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247
           Psychological measurement . . . . . . . . .  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  247
           From large-sample to small-sample theory in psychology . . . . . . . . . . . . . . . . . . . .  257
               The concept of probability . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . .  261
               Significance versus confidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  262
               Power . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .   263
               Random sampling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  263
           To the present . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  264
           The context of use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267
               Contexts of discovery versus verification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267
               Statistical significance as an indicator of research quality . . . . . . . . . . . . . . . . . .  268            Problems in application of statistical inference to psychological research . . . . . . . . 270
               Epistemic versus behavioral orientation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  270
               The literalness of acceptance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271
               The individual versus the aggregate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  272
               The paradox of precision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .   274
               Identification with the null . . . . . . . . .  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 276
               Random sampling from hypothetical infinite populations . . . . . . . . . . . . . . . . . .  276
               Assumption violation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .   278
               The impact of the preceding problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  279
           Possible responses by frequentists and Bayesians . . . . . . . . . . . . . . . . . . . . . . . . . .  280
           Toward resolution:  The frequentists versus the Bayesians . . . . . . . . . . . . . . . . . . .  281            The recent integration of Bayesian concepts and methods in psychological and
               medical research: The case of multiple imputation of missing data . . . . . . . . . . . 283
           Postscript on statistics in medicine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  284
           References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 286
 
10.  RECENT WORK IN PROBABILITY AND INFERENCE . . . . . . . . . . . . . . . . . . . . . 294
           Statistical and nonstatistical inference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 294
               The putative philosophical distinction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 294
               Psychological research on reasoning in statistical contexts . . . . . . . . . . . . . . . . . . 297
                   Models of inference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 297
                       Bayes’ Theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 298
                       Clinical inference and multiple regression . . . . . . . . . . . . . . . . . . . . . . . . . .  302
                       Causal inference and analysis of variance . . . . . . . . . . . . . . . . . . . . . . . . . . . 303
                   General issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  .   304
                       Atmosphere effects and the difficulty of abstract problems . . . . . . . . . . . . .  304
                       Judgments of randomness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  306
                   Randomness, representativeness, and replication in psychological research . .  307
           The ontogenesis of probability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 309
           The propensity theory of probability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 312
           The likelihood theory of statistical inference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 316
           Shafer’s theory of belief functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..318
           Recent work on reasoning in philosophy and artificial intelligence . . . . . . . . . . . . .  323
               Some recent concepts from artificial intelligence . . . . . . . . . . . . . . . . . . . . . . . . .  323
               Bayesian versus Dempster-Shafer formalisms . . . . . . . . . . . . . . . . . . . . . . . . . . .  326
           On formalization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  329
               Limits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329
               The relation between philosophy and psychology:  Bayesian theory . . . . . . . . . .  331
               Purposes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 332            Summary of challenges to Bayesian theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 334
           Postscript on Bayesian neuropsychology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335
           References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  336
 
11.  CONCLUSIONS AND THE FUTURE OF PSYCHOLOGICAL RESEARCH . . . . .. 339
           Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  . . . . . . . . . . . . . . . . . . 339
               The concept of probability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339
               The concept of statistical inference . . .  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341            The future of psychological research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 344
                    Surface obstacles to change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..344
                    Possible paths for quantitative research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347
                    The ambivalent promise of qualitative methods . . . . . . . . . . . . . . . . . . . . . . . . . .  350
                    Toward deeper obstacles to change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352
                The philosophical, social, and psychological context for the emergence of
                    a new epistemology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353
                    Empty self . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  355
                    Empty world . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . .  359
                    Objectivity, skeuomorphosis, and the problem of scale . . . . . . . . . . . . . . . . . . . .  363
                    The scarecrows of relativism and anarchy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366
                Biomedical research without a biomedical model . . . . . . . . . . . . . . . . . . . . . . . . . . . 367
                Postscript on Perceptual Control Theory . . . . . . . . . . . . . . . . . . . . . .  . . . . . . . . . . . .370
                References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  374

Notă biografică

Michael C. Acree received his Ph.D. in psychology from Clark University in 1978, where he completed the clinical training program and also worked as Data Analysis Consultant for the Department of Psychology.  At the University of Nebraska—Lincoln he was the first member of the psychology faculty to be elected to all three programs—Experimental, Social, and Clinical.  During his 3 years there, he taught undergraduate courses in clinical and abnormal psychology and graduate statistics and supervised clinical practicum students.  After leaving Nebraska voluntarily in 1979, he was for 5 years Assistant Research Psychologist at the Center on Deafness at the University of California, San Francisco.  There he conducted long-term longitudinal research on prelingually deaf children, and was Principal Investigator on a $75,000 grant from the National Institute of Handicapped Research, entitled “Dialogue with Deaf Children: Its Relation to Intellectual and Personal Growth.”  From 1985 to 1990 he was Assistant Professor at the Pacific Graduate School of Psychology in Palo Alto, where he was awarded a $28,000 grant by the Chapman Research Fund on “Roots of Social Science Methodology: Ontogenesis and History.”  After 5 years as Associate Professor at the California Institute for Integral Studies in San Francisco, he joined the UCSF Center for AIDS Prevention Studies as Senior Statistician, and in 2001 he moved in the same capacity to the Osher Center for Integrative Medicine, until his retirement in 2017.

Textul de pe ultima copertă

This book proposes and explores the idea that the forced union of the aleatory and epistemic aspects of probability is a sterile hybrid, inspired and nourished for 300 years by a false hope of formalizing inductive reasoning, making uncertainty the object of precise calculation.  Because this is not really a possible goal, statistical inference is not, cannot be, doing for us today what we imagine it is doing for us.  It is for these reasons that statistical inference can be characterized as a myth.
The book is aimed primarily at social scientists, for whom statistics and statistical inference are a common concern and frustration. Because the historical development given here is not merely anecdotal, but makes clear the guiding ideas and ambitions that motivated the formulation of particular methods, this book offers an understanding of statistical inference which has not hitherto been available. It will also serve as a supplement to the standard statistics texts. Finally, general readers will find here an interesting study with implications far beyond statistics.  The development of statistical inference, to its present position of prominence in the social sciences, epitomizes a number of trends in Western intellectual history of the last three centuries, and the 11th chapter, considering the function of statistical inference in light of our needs for structure, rules, authority, and consensus in general, develops some provocative parallels, especially between epistemology and politics.


Caracteristici

Highlights 12th to 17th century changes to conceptual basis of knowledge
Critiques modern concepts of probability and statistical inference
Proposes a view of psychology and medicine grounded in biological principles rather than in statistics.