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Chapter 10

by: Jacqueline Vilca

Chapter 10 PSY 292 Forster- Introduction to Biobehavioral Statistics for Non-Majors

Jacqueline Vilca
GPA 3.9
PSY 292 Forster- Introduction to Biobehavioral Statistics for Non-Majors

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Hello classmates, Here are the notes for chapter 10! Happy studying.
PSY 292 Forster- Introduction to Biobehavioral Statistics for Non-Majors
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This 3 page Class Notes was uploaded by Jacqueline Vilca on Friday March 20, 2015. The Class Notes belongs to PSY 292 Forster- Introduction to Biobehavioral Statistics for Non-Majors at University of Miami taught by Forster in Spring2015. Since its upload, it has received 33 views.

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Date Created: 03/20/15
Study Soup Chapter 10 Hypothesis testing Descriptive Statistics The logic of null hypothesis testing is based on proofby counter example If you nd a case where the hypothesis is false then you can quotreject the hypothesisquot Null hypothesis Testing Formalizing Null Hypothesis testing There is the Null Hypothesis and the Alternative hypothesis In terms of the null hypothesis we can quotrejectquot or quotfail to rejectquot the null hypothesis We can NEVER accept the null hypothesis We can only fail to reject it We can NEVER reject the alternative hypothesis either NULL HYPOTHESIS TESTING DIRECTIONALITY The alternative hypothesis is stated It s the results you obtained that were obtained by chance The null hypothesis is the negation of the alternative hypothesis The alternative hypothesis is a statement of your results not being obtained by chance RULES If the alternative hypothesis is nondirectional the null hypothesis states that the variable has no effect If the alternative is directional then the null hypothesis states that the variable does not have any effect or has an effect in the opposite direction TESTING THE NULL HYPOTHESIS 1 Calculate the probability that we obtain scores from different parts of any sampling distribution 2 Making the assumption that the null hypothesis is true we can calculate the probability of obtaining the set of observed scores in our sample 3 If the probability of obtaining our results is suf ciently small we can reject the null hypothesis 4 If the probability is not suf ciently small then we fail to reject the null hypothesis Remember we cannot prove it only fail to reject it THE CUTOFF The cutoff value of probability that determines whether results are signi cant or not signi cant 005 or 5 DECISION RULES Beta represents the probability of wrongly rejecting the alternative hypothesis Alpha represents the probability of wrongly rejecting the null hypothesis The level of signi cance is considered the probability of wrongly rejecting the null hypothesis Based on the traditional cutoff mentioned above the level of signi cance of alpha is 5 TYPE I ERROR Wrongly rejecting the null hypothesis when the null hypothesis is actually true TYPE ERROR Wrongly rejecting the alternative hypothesis when the alternative hypothesis is true In research we are always searching to disprove our hypothesis We want to minimize our ability to falsely reject something that goes against our hypothesis null hypothesis CLARIFICATION OF ALPHA Alpha is the rate at which we would expect to reject a true null hypothesis It determines our ability to detect the truth DIRECITONAL AND NONDIRECTIONAL Directional is only evaluating only the tail of the distribution that is in the direction speci ed by the alternative hypothesis When the alternative hypothesis is nondirectional then we alpha level must be split between both sides of the distribution


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