A Test of Probability Model in Hypothesis Testing
碩士 === 國立交通大學 === 工業工程與管理系 === 90 === While testing a hypothesis, people have difficulty in using falsifying evidence. Kirby’s signal detection theory(1994)assumes that people can falsify, but the probability of P and Q in a rule “if P then Q” would affect hypothesis-testing. He predicts...
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ndltd-TW-090NCTU00310622016-06-27T16:08:59Z http://ndltd.ncl.edu.tw/handle/12787553108399687989 A Test of Probability Model in Hypothesis Testing 假設檢定歷程中機率模式探討 Yi-Chi Lin 林奕祺 碩士 國立交通大學 工業工程與管理系 90 While testing a hypothesis, people have difficulty in using falsifying evidence. Kirby’s signal detection theory(1994)assumes that people can falsify, but the probability of P and Q in a rule “if P then Q” would affect hypothesis-testing. He predicts that tending to falsify would increase if the probability of P is low. In contrast, Oaksford and Chater’s optimal data selection theory(1996)doesn’t assume that people can falsify, they predict that people would use whatever information that more expected information gain. In this study, the probability of P or Q in Wason’s selection task was manipulated and the Subject’s selection of P or ~Q card in 20 selection tasks were compared with-or-without rule violation hint. The results show that subjects select more P cards when probability of P is low, and more ~Q card when probability of Q is high. This pattern of result lend the optimal data selection theory, namely, the hypothesis-testing process involves a inductive reasoning process:P and ~Q are regarded as samples of a population and are evaluated according to expected information gain of testing the sample. Besides, the rule violation hint also increased ~Q selection significantly. It indicates that people can falsify, but do not use it automatically. The lack of interaction between rule violation hint and probability of P or Q suggests that the heuristic regarding information gain and the falsification logic may affect hypothesis-testing independently. Ruey-Yun Horng 洪瑞雲 2002 學位論文 ; thesis 107 zh-TW |
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碩士 === 國立交通大學 === 工業工程與管理系 === 90 === While testing a hypothesis, people have difficulty in using falsifying evidence. Kirby’s signal detection theory(1994)assumes that people can falsify, but the probability of P and Q in a rule “if P then Q” would affect hypothesis-testing. He predicts that tending to falsify would increase if the probability of P is low. In contrast, Oaksford and Chater’s optimal data selection theory(1996)doesn’t assume that people can falsify, they predict that people would use whatever information that more expected information gain. In this study, the probability of P or Q in Wason’s selection task was manipulated and the Subject’s selection of P or ~Q card in 20 selection tasks were compared with-or-without rule violation hint. The results show that subjects select more P cards when probability of P is low, and more ~Q card when probability of Q is high. This pattern of result lend the optimal data selection theory, namely, the hypothesis-testing process involves a inductive reasoning process:P and ~Q are regarded as samples of a population and are evaluated according to expected information gain of testing the sample. Besides, the rule violation hint also increased ~Q selection significantly. It indicates that people can falsify, but do not use it automatically. The lack of interaction between rule violation hint and probability of P or Q suggests that the heuristic regarding information gain and the falsification logic may affect hypothesis-testing independently.
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author2 |
Ruey-Yun Horng |
author_facet |
Ruey-Yun Horng Yi-Chi Lin 林奕祺 |
author |
Yi-Chi Lin 林奕祺 |
spellingShingle |
Yi-Chi Lin 林奕祺 A Test of Probability Model in Hypothesis Testing |
author_sort |
Yi-Chi Lin |
title |
A Test of Probability Model in Hypothesis Testing |
title_short |
A Test of Probability Model in Hypothesis Testing |
title_full |
A Test of Probability Model in Hypothesis Testing |
title_fullStr |
A Test of Probability Model in Hypothesis Testing |
title_full_unstemmed |
A Test of Probability Model in Hypothesis Testing |
title_sort |
test of probability model in hypothesis testing |
publishDate |
2002 |
url |
http://ndltd.ncl.edu.tw/handle/12787553108399687989 |
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