Exercise 6. Using the MGF given by Equation (24), deduce the expressions for the mean and variance we found earlier. Exercise 7. Prove the algebraic identity: (x – (+o²t))² , o?4 + ut + xt 25 2g2
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- Properties of scaling. Suppose that you want to examine the relationship between wages and experience measured in months rather than years. a) What is the variance of experience in months? Compare this to 1b). b) What is the covariance of wages and experience in months? Compare this to 1d). c) What is the correlation of experience and wages? Compare this to le). d) Prove mathematically that the Corr(cX,Y) = Corr(X,Y) using the properties of summation from class. Show each step of your proof.For each part below, if a regression has the given coefficient of correlation, find its coefficient of determination. Your answer should be accurate to at least four decimal places. a) Coefficient of correlation is -0.72. Coefficient of determination is 0 b) Coefficient of correlation is 0.84. Coefficient of determination is 0Answer number 4
- Match the coefficient of determination to the scatter diagram. The scales on the x-axis and y-axis are the same for each scatter diagram. (a) R2=0.12, (b) R2=0.90, (a) Scatter diagram . (b) Scatter diagram . (c) Scatter diagramThe data below are the shoot lengths (cm.) of Robusta coffee seedlings as affected by different periods of storage. Find out if there are significant differences in the effects of different periods of storage on the shoot lengths. (Note: CRD experiment) Solve for the; a. F computed b. Coefficient of Variation (CV), C. Standard error of the treatment means (S), d. standard error of difference between treatments (Sd) e. Make a Decision Treatments Replications 11 11 P1 10.1 9.2 9.5 P2 9.5 9.3 8.5 P3 8.7 9.2 7.5 P4 6.7 6.2 5.0A random sample of college students was surveyed about how they spend their time each week. The scatterplot below displays the relationship between the number of hours each student typically works per week at a part- or full-time job and the number of hours of television each student typically watches per week. The correlation between these variables is r = –0.63, and the equation we would use to predict hours spent watching TV based on hours spent working is as follows: Predicted hours spent watching TV = 17.21 – 0.23(hours spent working) Since we are using hours spent working to help us predict hours spent watching TV, we’d call hours spent working a(n) __________________ variable and hours spent watching TV a(n) __________________ variable. The correlation coefficient, along with what we see in the scatterplot, tells us that the relationship between the variables has a direction that is _________________ and a strength that is ______________________. According to the…