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Statistics Exam 2 Study Sheet.pdf

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Multiple choice, T/F, Fill-in topics: Null hypothesis The population mean is the same as that of our sample ○ There are no mean differences between the groups ○ In other words, our sample came ... from this particular population ○ This is the hypothesis we’re actually testing - Null Hypothesis Testing The Null Hypothesis Distribution ○ In the one-sample case, the NHD is the sampling distribution of the mean ○ Think of it as a map of what results are or are not likely by chance You can never prove a null hypothesis or an alternative hypothesis. You can only reject, or fail to reject the null hypothesis. Hypothesis testing: General Region of Rejection (alpha, or α) The area of the distribution in which we reject the null hypothesis (it’s a p-value!) By convention, α = .05 (sometimes .01) General steps: 1.State the null hypotheses 2.Select the statistical test and the significance level 3.Select the sample and collect the data 4.Find the region of rejection 5.Calculate the test statistic (some variable you calculate from samples to determine whether to reject a null hypothesis) 6.Make the statistical decision (and interpretation) Interpretation of results factors for significance p levels confidence intervals Type I and II errors Type I Error Rejecting the null hypothesis when it is in fact true; saying that there is a difference when there is none. Type II Error Failing to reject the null hypothesis when it is in fact false; saying there is no difference when in fact there is one. Pop quiz! A researcher conducts 200 experiments in the last 5 years. She always used an alpha level of .05, and found significant results for 140 of those experiments. How many Type I errors has she made? somewhere between 0 and 140 (Can you explain why?) Depending on what our statistical decision is, we ALWAYS run the risk of making one type of error OR the other! Reject the the null hypothesis - risk Type I Error Fail to reject the null hypothesis - risk Type II Error [Show More]

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