DA 410 Project 2 C. C
Project 2
Part 1: Download testscoredata.txt and read it in R or SAS.
Use Hotelling¡¯s T^2 test to test for a difference in the mean score vector of the boys and the mean vector of the girls. Make sure you include clear command lines and relevant output/results with hypotheses, test result(s) and conclusion(s)/interpretation(s).
Part 2: Suppose we have gathered the following data on female athletes in three sports. The measurements we have made are the athletes’ heights and vertical jumps, both in inches. The data are listed as (height, jump) as follows:
Basketball Players: Track Athletes: Softball Players:
(66, 27), (65, 29), (68, 26), (64, 29), (67, 29)
(63, 23), (61, 26), (62, 23), (60, 26)
(62, 23), (65, 21), (63, 21), (62, 23), (63.5, 22), (66, 21.5)
#The following R code should read in the data as 3 vectors:
a) Use R to conduct the MANOVA F-test using Wilks’ Lambda to test for a difference in (height, jump) mean vectors across the three sports. Make sure you include clear command lines and relevant output/results with hypotheses, test result(s) and conclusion(s)/interpretation(s)
b) State the assumptions of your test and check to see whether assumptions are met. Do you believe your inference is valid? Why or why not?
c) Use R to examine the sample mean vectors for each group. Make sure you include clear command lines and relevant output/results. Also comment on the differences among the groups in terms of the specific variables.
Part 3: Save your file as DA410_Project2_XXXXX.docx (or .pdf) where XXXXX is the first five letters of your last name, and submit it online.
sport <- c('B','B','B','B','B','T','T','T','T','S','S','S','S','S','S') height <- c(66,65,68,64,67,63,61,62,60,62,65,63,62,63.5,66) jump<-c(27,29,26,29,29,23,26,23,26,23,21,21,23,22,21.5)