Given: Student Pre-test Scores Post-test Scores 1 84 85 2 78 86 ITT 3 88 89 4 79 83 5 84 87 Find: degree of relationship of the two variables Least-Square Regression Line Equation (LSRL) and predict the post-test score if the pre- test score is 75.
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- Which of the multivariate regression parameters listed below would be best interpreted as: the predicted value on the dependent variable when all of the independent variables in the model are equal to zero. a b1 X1 R2For a multiple regression model, SSR = 600 and SSE = 200. The multiple coefficient of determination isA ski resort asked a random sample of guests to rate their satisfaction on various attributes of their visit on a scale of 1–5 with 1 = very unsatisfied and 5 = very satisfied. The estimated regression model was Y = overall satisfaction score, X1 = lift line wait, X2 = amount of ski trail grooming, X3 = safety patrol visibility, and X4 = friendliness of guest services. Predictor Coefficient Intercept 2.7115 LiftWait 0.1474 AmountGroomed 0.2517 SkiPatrolVisibility 0.0656 FriendlinessHosts −0.1172 (a) Write the fitted regression equation. (Round your answers to 4 decimal places. Negative values should be indicated by a minus sign.) yˆy^ = ?? + ?? * LiftWait + ?? * AmountGroomed + ?? * SkiPatrolVisibility + ?? * FriendlinessHosts (b) Interpret each coefficient. Overall satisfaction increases Correctwith an increase in satisfaction for each individual predictor except for friendliness of hosts.(c) Would the intercept seem to have meaning in this…
- A ski resort asked a random sample of guests to rate their satisfaction on various attributes of their visit on a scale of 1–5 with 1 = very unsatisfied and 5 = very satisfied. The estimated regression model was Y = overall satisfaction score, X1 = lift line wait, X2 = amount of ski trail grooming, X3 = safety patrol visibility, and X4 = friendliness of guest services. Predictor Coefficient Intercept 2.9833 LiftWait 0.1458 AmountGroomed 0.2562 SkiPatrolVisibility 0.0428 FriendlinessHosts −0.1298 (a) Write the fitted regression equation. (Round your answers to 4 decimal places. Negative values should be indicated by a minus sign.) yˆy^ = + * LiftWait + * AmountGroomed + * SkiPatrolVisibility + * FriendlinessHosts (b) Interpret each coefficient. Overall satisfaction increases with an increase in satisfaction for each individual predictor except for friendliness of hosts. (d) Make a prediction for Overall Satisfaction when a guest’s satisfaction in…A ski resort asked a random sample of guests to rate their satisfaction on various attributes of their visit on a scale of 1–5 with 1 = very unsatisfied and 5 = very satisfied. The estimated regression model was Y = overall satisfaction score, X1 = lift line wait, X2 = amount of ski trail grooming, X3 = safety patrol visibility, and X4 = friendliness of guest services. Predictor Coefficient Intercept 2.9018 LiftWait 0.1642 AmountGroomed 0.2343 SkiPatrolVisibility 0.0602 FriendlinessHosts −0.1193 (a) Write the fitted regression equation. (Round your answers to 4 decimal places. Negative values should be indicated by a minus sign.) yˆy^ = + * LiftWait + * AmountGroomed + * SkiPatrolVisibility + * FriendlinessHosts (b) Interpret each coefficient. Overall satisfaction (Click to select) increases decreases remains same with an increase in satisfaction for each individual predictor except for friendliness of hosts.(c) Would the intercept seem to…A random sample of twelve students were chosen, and their midterm test score (y), as- signment score (x1), and missed classes (x2) were recorded as follows: Midterm Score, y Assignment Score, x1 Classes Missed, x2 85 74 76 90 85 87 94 98 81 91 76 74 65 50 55 65 55 70 65 70 55 70 50 55 5 7 5 2 6 3 2 5 4 3 1 4 (i) What is the fitted multiple linear regression equation of the form yˆ = b0 + b1x1 + b2x2? (ii) From part (i) above, estimate the midterm test score grade for a student who has an assignment score of 60 and missed 4 classes.
- The grades of a sample of 9 students on a prelim exam (x) and on the midterm exam (y) are shown in the excel worksheet. Find the regression equationA seafood-sales manager collected data on the maximum daily temperature, T, and the daily revenue from salmon sales, R, using sales receipts for 30 days selected at random. Using the data, the manager conducted a regression analysis and found the least-squares regression line to be Rˆ=126+2.37T. A hypothesis test was conducted to investigate whether there is a linear relationship between maximum daily temperature and the daily revenue from salmon sales. The standard error for the slope of the regression line is SEb1=0.65. Assuming the conditions for inference have been met, which of the following is closest to the value of the test statistic for the hypothesis test? t=0.274 A t=0.65 B t=1.54 C t=3.65 D t=193.85 EIn a laboratory experiment, data were gathered on the life span (y in months) of 33 rats, units of daily protein intake (x1), and whether or not agent x2 (a proposed life-extending agent) was added to the rats' diet (x2 = 0 if agent x2 was not added, and x2 = 1 if agent was added). From the results of the experiment, the following regression model was developed:ŷ = 36 + .8x1 − 1.7x2Also provided are SSR = 60 and SST = 180.The test statistic for testing the significance of the model is _____. a. 5.00 b. .50 c. .25 d. .33
- A sociologist was hired by a large city hospital to investigate the relationship between the number of unauthorized days that employees are absent per year and the distance (miles) between home and work for the employee. A sample of 10 employees was chosen, and the following data were collected. A. Is the estimated regression equation appropriate and adequateSuppose that a multiple linear regression model was fit to data and that the following output resulted: Coefficients: (Intercept)exam1exam2attendance Estimate20.001.3002.5000.685 Std. Error4.2910.2610.2745.608 t value-4.6604.9819.124 0.122 Pr(>|t|)<0.0001<0.0001<0.00010.9032 Perform a backwards selection process. Select the variable that would be removed first from the model. The significance level is 0.05 for testing purposes. attendance exam2 exam1Use the table of x and y values below to determine the slope of the least-squares regression line.