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This volume focuses on the abuse of statistical inference in scientific and statistical literature, as well as in a variety of other sources, presenting examples of misused statistics to show that many scientists and statisticians are unaware of, or unwilling to challenge the chaotic state of statistical practices.;The book: provides examples of ub
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This volume focuses on the abuse of statistical inference in scientific and statistical literature, as well as in a variety of other sources, presenting examples of misused statistics to show that many scientists and statisticians are unaware of, or unwilling to challenge the chaotic state of statistical practices.;The book: provides examples of ub
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd (Sales)
- Seitenzahl: 256
- Erscheinungstermin: 19. September 2019
- Englisch
- Abmessung: 231mm x 155mm x 18mm
- Gewicht: 227g
- ISBN-13: 9780367402563
- ISBN-10: 0367402564
- Artikelnr.: 57814788
- Verlag: Taylor & Francis Ltd (Sales)
- Seitenzahl: 256
- Erscheinungstermin: 19. September 2019
- Englisch
- Abmessung: 231mm x 155mm x 18mm
- Gewicht: 227g
- ISBN-13: 9780367402563
- ISBN-10: 0367402564
- Artikelnr.: 57814788
Wang\, Charmont
Part 1 Fads and fallacies in hypothesis testing: examples
the t
test; a two
stage test
of
significance; more examples
a Kolmogorov
Smirnov test; mechanical application of statistical tests; data snooping; an appreciation of non
significant results; type I and type II errors
for decision making; type I and type II errors
for general scientists. Part 2 Quasi
inferential statistics: randomness or chaos? Hume's problem; unobservables, semi
unobservables and grab sets; is statistics a science?; grab sets and quasi
inferential statistics; concluding remarks
quasi
and pseudo
inferential statistics. Part 3 Statistical causality and law
like relationships: sense and nonsense in causal inference
examples; Rubin's model and controlled experiments; Rubin's model and observational studies; causal inference in sample survey and other observational studies; causes, indicators and latent variables. Part 4 Amoeba regression and time
series models: discovering causal structure
science now can be easily cloned; regression and time
series analysis
science or lunacy? (part I); regression and time
series analysis
science or lunacy? (part II); regression and time
series analysis
science or lunacy? (part III); statistical correlation versus physical causation. Part 5 A critical eye and an appreciative mind toward subjective knowledge: the sorry state of statistical evaluation
a case study in educational research; modeling interaction effects
a case study from the social
behavioural sciences. Part 6 On objectivity, subjectivity and probability: statistical justification of scientific knowledge and scientific philosophy; classical probability, common sense and a strange view of nature; intuition and subjective knowledge in action
the Bayes theorem (and its misuse); Bayesian time
series analysis and E. T. (extra time
series) judgment; a pursuit of information beyond the data in randomized and nonrandomized studies; women and love
a case study in qualitative/quantitative analysis. Part 7 A delicate balance between order and chaos: reliability; order within chaos
heartbeats, brainwaves, simulated annealing and the fiddling of a system. Part 8 The riddle of the ubiquitous statistics: information and misinformation; statistical quality control and the conflicting teachings of Q.C. Gurus. Epilogue
toward a new perspective on statistical inference.
the t
test; a two
stage test
of
significance; more examples
a Kolmogorov
Smirnov test; mechanical application of statistical tests; data snooping; an appreciation of non
significant results; type I and type II errors
for decision making; type I and type II errors
for general scientists. Part 2 Quasi
inferential statistics: randomness or chaos? Hume's problem; unobservables, semi
unobservables and grab sets; is statistics a science?; grab sets and quasi
inferential statistics; concluding remarks
quasi
and pseudo
inferential statistics. Part 3 Statistical causality and law
like relationships: sense and nonsense in causal inference
examples; Rubin's model and controlled experiments; Rubin's model and observational studies; causal inference in sample survey and other observational studies; causes, indicators and latent variables. Part 4 Amoeba regression and time
series models: discovering causal structure
science now can be easily cloned; regression and time
series analysis
science or lunacy? (part I); regression and time
series analysis
science or lunacy? (part II); regression and time
series analysis
science or lunacy? (part III); statistical correlation versus physical causation. Part 5 A critical eye and an appreciative mind toward subjective knowledge: the sorry state of statistical evaluation
a case study in educational research; modeling interaction effects
a case study from the social
behavioural sciences. Part 6 On objectivity, subjectivity and probability: statistical justification of scientific knowledge and scientific philosophy; classical probability, common sense and a strange view of nature; intuition and subjective knowledge in action
the Bayes theorem (and its misuse); Bayesian time
series analysis and E. T. (extra time
series) judgment; a pursuit of information beyond the data in randomized and nonrandomized studies; women and love
a case study in qualitative/quantitative analysis. Part 7 A delicate balance between order and chaos: reliability; order within chaos
heartbeats, brainwaves, simulated annealing and the fiddling of a system. Part 8 The riddle of the ubiquitous statistics: information and misinformation; statistical quality control and the conflicting teachings of Q.C. Gurus. Epilogue
toward a new perspective on statistical inference.
Part 1 Fads and fallacies in hypothesis testing: examples
the t
test; a two
stage test
of
significance; more examples
a Kolmogorov
Smirnov test; mechanical application of statistical tests; data snooping; an appreciation of non
significant results; type I and type II errors
for decision making; type I and type II errors
for general scientists. Part 2 Quasi
inferential statistics: randomness or chaos? Hume's problem; unobservables, semi
unobservables and grab sets; is statistics a science?; grab sets and quasi
inferential statistics; concluding remarks
quasi
and pseudo
inferential statistics. Part 3 Statistical causality and law
like relationships: sense and nonsense in causal inference
examples; Rubin's model and controlled experiments; Rubin's model and observational studies; causal inference in sample survey and other observational studies; causes, indicators and latent variables. Part 4 Amoeba regression and time
series models: discovering causal structure
science now can be easily cloned; regression and time
series analysis
science or lunacy? (part I); regression and time
series analysis
science or lunacy? (part II); regression and time
series analysis
science or lunacy? (part III); statistical correlation versus physical causation. Part 5 A critical eye and an appreciative mind toward subjective knowledge: the sorry state of statistical evaluation
a case study in educational research; modeling interaction effects
a case study from the social
behavioural sciences. Part 6 On objectivity, subjectivity and probability: statistical justification of scientific knowledge and scientific philosophy; classical probability, common sense and a strange view of nature; intuition and subjective knowledge in action
the Bayes theorem (and its misuse); Bayesian time
series analysis and E. T. (extra time
series) judgment; a pursuit of information beyond the data in randomized and nonrandomized studies; women and love
a case study in qualitative/quantitative analysis. Part 7 A delicate balance between order and chaos: reliability; order within chaos
heartbeats, brainwaves, simulated annealing and the fiddling of a system. Part 8 The riddle of the ubiquitous statistics: information and misinformation; statistical quality control and the conflicting teachings of Q.C. Gurus. Epilogue
toward a new perspective on statistical inference.
the t
test; a two
stage test
of
significance; more examples
a Kolmogorov
Smirnov test; mechanical application of statistical tests; data snooping; an appreciation of non
significant results; type I and type II errors
for decision making; type I and type II errors
for general scientists. Part 2 Quasi
inferential statistics: randomness or chaos? Hume's problem; unobservables, semi
unobservables and grab sets; is statistics a science?; grab sets and quasi
inferential statistics; concluding remarks
quasi
and pseudo
inferential statistics. Part 3 Statistical causality and law
like relationships: sense and nonsense in causal inference
examples; Rubin's model and controlled experiments; Rubin's model and observational studies; causal inference in sample survey and other observational studies; causes, indicators and latent variables. Part 4 Amoeba regression and time
series models: discovering causal structure
science now can be easily cloned; regression and time
series analysis
science or lunacy? (part I); regression and time
series analysis
science or lunacy? (part II); regression and time
series analysis
science or lunacy? (part III); statistical correlation versus physical causation. Part 5 A critical eye and an appreciative mind toward subjective knowledge: the sorry state of statistical evaluation
a case study in educational research; modeling interaction effects
a case study from the social
behavioural sciences. Part 6 On objectivity, subjectivity and probability: statistical justification of scientific knowledge and scientific philosophy; classical probability, common sense and a strange view of nature; intuition and subjective knowledge in action
the Bayes theorem (and its misuse); Bayesian time
series analysis and E. T. (extra time
series) judgment; a pursuit of information beyond the data in randomized and nonrandomized studies; women and love
a case study in qualitative/quantitative analysis. Part 7 A delicate balance between order and chaos: reliability; order within chaos
heartbeats, brainwaves, simulated annealing and the fiddling of a system. Part 8 The riddle of the ubiquitous statistics: information and misinformation; statistical quality control and the conflicting teachings of Q.C. Gurus. Epilogue
toward a new perspective on statistical inference.