one way analysis of variance and post hoc te - 德克.ppt

Social Work Statistics One-way Analysis of Variance and Post Hoc Tests Key Points about Statistical Test Sample Homework Problem Solving the Problem with SPSS Logic for One-way Analysis of Variance with Post Hoc Tests Power Analysis One-way Analysis of Variance: Purpose Purpose: test whether or not the populations represented by the samples have a different mean Examples: Social work students have higher GPA’s than nursing students and education majors Social work students volunteer for more hours per week than education majors, liberal arts majors, and communications majors UT social work students score higher on licensing exams than graduates of Texas State University, Baylor University, and University of Houston One-way Analysis of Variance: Hypotheses - 1 Hypotheses: Null: mean of population 1 = mean of population 2 = mean of population 3 = mean of population 4 …. Versus Research: at least one population mean is different from the others Decision: Reject null hypothesis if pSPSS ≤ alpha (≠ relationship) One-way Analysis of Variance: Hypotheses - 2 A significant finding tells us that at least one mean is different from the other, but it does not tell us which one or ones differ. To answer that question, we might try to use t-tests to compare each of the pairs of means to identify which are significantly different. However, the multiple tests would increase the probability of making a Type I error increases above the alpha that we set, i.e. greater than the risk of drawing a wrong conclusion. One strategy for controlling the error rate is the Bonferroni inequality by which we divide alpha by the number of tests we need and only report those that meet this reduced level of significance. One-way Analysis of Variance: Hypotheses - 3 As an alternative, statisticians have developed post hoc tests which control the error rate for the number of comparisons that are made. Thus, for a one-way analysis of variance, we only report findings for combinatio