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Lecture 7

PSYC209 Lecture 7: Chapter 7 Notes

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University of Delaware
Ly Agnes

Madison Newman PSYC 209080 31717 Chapter 7.17.6: Hypothesis Testing o Hypothesisstatement of proposed explanation for an observation or problem tested using a research method o Hypothesis testing significance testing o Null hypothesisnull is a statement about a population parameter such as the population mean, that is assumed to be true o Alternative hypothesis (H)statement that directly contradicts a null hypothesis by stating that the actual value of a population parameter is less than null hypothesis o Level of significancesignificance levelcriterion of judgment upon which a decision is made regarding value states is a null hypothesis o Test statisticmathematical formula that identifies how far or how many standard deviations a sample outcome is from value states is a null hypothesis o P valueprobability of obtaining a sample outcome, given that the null hypothesis is true o Statistical significancedecision made concerning null hypothesis o Type II errorprobability of retaining a null hypothesis that is actually false o Type I errorprobability of rejecting a null hypothesis that is actually true o Alpha levellevel of significance or criterion for a hypothesis test o Powerprobability of rejecting a false null hypothesis o Nondirectional testshypothesis tests in which the alternative hypothesis is stated as not equal to a value o Critical valuecutoff value that defines the boundaries beyond which less than 5 of sample means can be obtained if the null hypothesis is true o Rejection region o Z statistic o Obtained value o Directional tests o Type III errorrejection region located in wrong tail o Effect sizestatistical measure of the size of an effect in a population o Cohens dmeasure of effect size in terms of the number of standard deviations that mean score shifted above or below the population mean stated by the null hypothesis o Cohens effect size conventionsstandard rules identifying small, medium, and large effects based on typical behavioral research o As the size of an effect increases, the power to detect the effect also increases o Increasing sample size increases power by reducing standard error, thereby increasing the value of the test statistic in hypothesis testing o Increasing power will decrease standard deviation o Power in decisionmaking processlikelihood of of rejecting a false null hypothesis
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