Consider the following output in R for the heptathlon data we have discussed. (a) Then give an interprotation, in terms of the data, for each of the components YO 11se >data("heptathlon", package - > heptathlonShurdlesmax (heptathlonShurdles)heptath >hoptathlnn200mmax (hoptathlonSrun200m)htathlonSrun200m >heptathlonSrun800m- max (heptathlonSrun800m) - heptathlonSrun800m(c) Repeat the factor analysis with rotation- promar(and 2 factons). Compare > factanal (heptathlon[,-8],2,rotationvarimax" "HSAUR) hlonShurdles( b) Interpret the Uniqueness values for this analysis. your results with the rotation "varimax results Call (d) Repest the analysis (with rotation-"varinax) without adjusting tbe ranning and hurdks variables so that bigger is better That is, without: factanal (x heptathlon[, -8], factors =2, rotation= "varimax ") Uniquenesses hurdlos highjup run200m ngjump Javelin run800m 0.052 0.224 0.484 0.005 0.094 0.743 0.406 Briefly explain why the rosults do, or do not, surprise you Loadinga Factori Factor2 hurdles 0.968 0.104 highjump 0.859 -0.196 shot run200m 0.725 0.685 longjump 0.928 0.210 javelin run800m 0.765 0.644 0.318 0.507 Factori Factor2 SS loadings 4.064 0.928 Proportion Var 0.581 0.133 Cumulative Var 0.581 0.713 Test of the hypothesis that 2 factors are sufficient The chi square statistic is 13.07 on 8 dogrees of freedom. The p-value is 0.11 Consider the following output in R for the heptathlon data we have discussed. (a) Then give an interprotation, in terms of the data, for each of the components YO 11se >data("heptathlon", package - > heptathlonShurdlesmax (heptathlonShurdles)heptath >hoptathlnn200mmax (hoptathlonSrun200m)htathlonSrun200m >heptathlonSrun800m- max (heptathlonSrun800m) - heptathlonSrun800m(c) Repeat the factor analysis with rotation- promar(and 2 factons). Compare > factanal (heptathlon[,-8],2,rotationvarimax" "HSAUR) hlonShurdles( b) Interpret the Uniqueness values for this analysis. your results with the rotation "varimax results Call (d) Repest the analysis (with rotation-"varinax) without adjusting tbe ranning and hurdks variables so that bigger is better That is, without: factanal (x heptathlon[, -8], factors =2, rotation= "varimax ") Uniquenesses hurdlos highjup run200m ngjump Javelin run800m 0.052 0.224 0.484 0.005 0.094 0.743 0.406 Briefly explain why the rosults do, or do not, surprise you Loadinga Factori Factor2 hurdles 0.968 0.104 highjump 0.859 -0.196 shot run200m 0.725 0.685 longjump 0.928 0.210 javelin run800m 0.765 0.644 0.318 0.507 Factori Factor2 SS loadings 4.064 0.928 Proportion Var 0.581 0.133 Cumulative Var 0.581 0.713 Test of the hypothesis that 2 factors are sufficient The chi square statistic is 13.07 on 8 dogrees of freedom. The p-value is 0.11
