Given are five observations for two variables, x and y. 15 14 16 19 Yi 56 55 48 17 13 The estimated regression equation for these data is ŷ = 63.98 –- 2.38a. a. Compute SSE, SST, and SSR. SSE (to 2 decimals) SST (to 2 decimals) SSR (to 2 decimals) b. Compute the coefficient of determination p2. Comment on the goodness of fit. (to 3 decimals) The least squares line provided an Select your answer - fit; % of the variability in y has been explained by the estimated regression equation (to 1 decimal). c. Compute the sample correlation coefficient. Enter negative value as negative number. (to 3 decimals)

Use the given data to find the equation of the regression line. Round the final values to three significant digits, if necessary. 6 8 20 28 36 2 4 13 20 30 y OA. y = -2.79+0.897x OB. y = -3.79+0.897x OC. y=-3.79+0.801x OD. y = -2.79+0.950x TIE

Compute the least-squares regression equation for the given data set. Use a TI-84 calculator. Round the slope and y-intercept to at least four decimal places. 43 37 15 19 24 37 18 y 72 67 25 29 42 65 32 Send data to Excel Regression line equation: y = 1.7777x + 1.5838

5. For the following set of data: Y 1 10 5 4 4 13 a. Find the regression equation for predicting Y from X. b. Does the regression equation account for a significant portion of the variance in the Y scores? Use a = .05 to evaluate the F-ratio %3D X27 33

Given are five observations for two variables, z and y. z 3 9 10 18 20 | 53 55 50 14 16 The estimated regression equation for these data is y 70.38 – 2.73z. a. Compute SSE, SST, and SSR. SSE (to 2 decimals) 230 (to 2 decimals) (to 2 decimals) b. Compute the coefficient of determination. Comment on the goodness of fit. SST SSR (to 3 decimals) The least squares line provided an pood explained by the estimated regression equation (to 1 decimal). c. Compute the sample correlation coefficient. Enter negative value as negative number. % of the variability in y has been (to 3 decimals)

26. For the following scores: X 3 5 2 2 4 1 4 Y 8 8 6 3 6 4 7 a. Find the regression equation for predicting Y from X. b. Calculate the predicted Y value for each X.

Below table contains a data sample where X is the independent, and Y the dependent variable. Using the data, please conduct a regression analysis. Determine first the regression equation with the help of below graph and table, then answer all the questions. 1. The value of cell a is 2. The value of cell b is 3: The value of cell c is 4: The value of cell d is 5: The value of cell e is 6: The value of cell f is 7: The value of cell g is 8. The value of cell h is 9: The value of cell i is 10: The value of cell j is 11: The value of cell k is 12: The value of cell l is 13: The value of cell m is 14: The value of cell n is 15: The value of cell o is 16: The value of cell p is 17: The value of cell q is 18: The value of cell r is 19: The value of cell s is 20: The value of cell t is 21: The value of cell u is 22: The value of cell v is 23: The value of cell w is 24: The value of cell x is 25: The value of cell y is 26: The value of cell z is 27: The value of cell aa is 28: The value of cell…