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Unformatted text preview: STA 6166 Practice Problems Exam 3 A study is conducted to compare whether incidence of muscle aches differs among athletes exposed to 5 types of pain medication. A total of 500 people who are members of a large fitness center are randomly assigned to one of the medications. After a lengthy workout, each is given a survey to determine presence/absence of muscle pain. For the 5 groups: 25, 38, 32, 40, and 35 are classified as having muscle pain, respectively. The following output gives the results for the Pearson chisquare statistic for testing ( =0.05): H : True incidence rate of muscle pain doesnt differ among medications H A : Incidence rates are not all equal Test Statistic _________________________ Reject H if the test statistic falls in the range(s) ________________________ Pvalue _____________________________ Conclude (Circle One): Medication effects not all equal No differences in effects Give the expected number of incidences of muscle pain for each medication under H : In a 2Factor ANOVA, measuring the effects of 2 factors (A and B) on a response (y), there are 3 levels each for factors A and B, and 4 replications per treatment combination. Give the values of of the Fstatistic for the AB interaction for which we will conclude the effects of Factor A levels depend on Factor B levels and vice versa ( =0.05): ChiSquare Tests 6.150 a 4 .188 Pearson ChiSquare Value df Asymp. Sig. (2sided) A simple linear regression model is fit, relating plant growth over 1 year (y) to amount of fertilizer provided (x). Twenty five plants are selected, 5 each assigned to each of the fertilizer levels (12, 15, 18, 21, 24). The results of the model fit are given below: Can we conclude that there is an association between fertilizer and plant growth at the 0.05 significance level? Why (be very specific). Give the estimated mean growth among plants receiving 20 units of fertilizer. The estimated standard error of the estimated mean at 20 units is 46 . 450 ) 18 20 ( 25 1 1 . 2 2 = + Give a 95% CI for the mean at 20 units of fertilizer. Coefficients a 8.624 1.810 4.764 .000 .527 .098 5.386 .000 (Constant) x Model 1 B Std. Error Unstandardized Coefficients t Sig. Dependent Variable: y a. A multiple regression model is fit, relating salary (Y) to the following predictor variables: experience (X 1 , in years), accounts in charge of (X 2 ) and gender (X 3 =1 if female, 0 if male). The following ANOVA table and output gives the results for fitting the model....
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 Fall '08
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