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- 4. For a sample of 12 observations, a businessman wants to regress the price (in dollar) of the laptop (Y) on the processor's speed (X). The summary results of the observations are given below. Σx = 19.8 , Σy = 24798, Σxy = 431882 Σx^2 = 3388, Σγ^2 = 57365692 a) compute correlation coefficient (b) Find the fitted regression line of the price of laptop on processor speed.Given are five observations for two variables, x and y.x 3 12 6 20 14y 65 50 65 15 18a. Develop a scatter diagram for these data.b. Compute correlation between x and y variable.c. Develop the estimated regression equation by computing b0 and bGiven are five observations for two variables, x and y.x 3 12 6 20 14y 65 50 65 15 18a. Develop a scatter diagram for these data.b. Compute correlation between x and y variable.c. Develop the estimated regression equation by computing b0 and b1
- The following sample contains the scores of 6 students selected at random in Mathematics and English. Use the scores in English as the dependent variable Y. Mathematics score (X) 70 92 80 74 65 83 English score (Y) 74 84 63 87 78 90 ∑x=464, ∑y=476,∑x^2=36354,∑y^2=38254, ∑xy=36926. Estimate the regression parameters and also write the prediction equation.Interpret the estimated regression coefficient corresponding to the Z variable. Data Salary Education Experience Sex 29.7985 15 3 1 21.8219 4 0 0 22.8978 4 0 0 22.0917 1 1 0 21.8993 5 0 0 22.4829 3 1 1 28.0772 15 0 0 y=salary 23.6292 6 1 1 x1=education level in schooling years 32.3595 0 15 1 x2=experience level in employment level 21.794 1 0 0 d=sex (1 for male,0 for female) 19.8762 3 0 0 Ln(Y) = alpha +beta1X1 +Beta2X2+ Beta3D +Beta4Z +e 21.0253 3 0 0 where z =X2D 24.6323 0 5 1 19.0247 0 0 0 18.8857 0 0 0 21.8552 1 0 0 24.2675 6 1 0 18.7931 0 0 0 18.9276 0 0 0 23.4441 5 1 1 20.8047 2 0 0 18.26 0 0 0 20.6726 0 2 1 21.7815 3 0 0…4.For a sample of 12 observations, a businessman wants to regress the price (in dollar) of the laptop (Y) on the processor's speed (X). The summary results of the observations are given below. Σx = 19.8 , Σy = 24798, Σxy = 431882 Σx^2 = 33.88, Σγ^2 = 57365692 (b)Find the fitted regression line of the price of laptop on processor speed. (c) Find the predicted price of the laptop (y) for the processor speed x-1.9. (d) Compute the coefficient of determination and comment.
- Use the following results obtained from a simple linear regression analysis with 12 observations. Y = 37.2895- (1.2024)X Sb = 0.2934 Test to determine if there is a significant negative relationship between the independent and dependent variables at alpha= .05. Give the resulting conclusion. a. is rejected. B.cannot be tested with the given information. c. is not rejected. D. is not an appropriate null hypothesis for this situation.In exercise 1, the following estimated regression equation based on 10 observations waspresented. y^= 29.1270 + .5906x1 + .4980x2Here SST =6724.125, SSR =6216.375, Sb1 = .0813, and Sb2 = .0567.a. Compute MSR and MSE.b. Compute F and perform the appropriate F test. Use α .05.c. Perform a t test for the significance of B1. Use α .05.d. Perform a t test for the significance of B2. Use α .05.A researcher intends to conduct a multiple regression on the following data set where YY is the dependent variable. X1X1 X2X2 YY 41.1 46.8 40.8 43.5 37 46.3 42.9 71.2 69.3 25.3 75 47.8 38.6 59.7 41.3 46.5 53.2 52.7 49.3 42.6 50.3 47.6 29 34.1 37.1 43.1 39.7 50.1 43.5 56.1 Calculate the following correlations and semipartial correlations with the dependent variable. Report all answers accurate to at least 3 decimal places.The correlation between x1 and y = The correlation between x2 and y =