f    SS MS F Regression     4,853   2,426.5     Residual         485.3                       Coefficients Standard Error

A simple regression model for 10 pair of data resulted in a standard error of 3.95 (i.e., Se = 3.95), and the. The sum of squares of error (SSE) is ______.   a. 187.23   b. 171.63   c. 156.03   d. 140.42   e. 124.82

5 prac

The commercial division of a real estate firm is conducting a regression analysis of the relationship between x, annual gross rents (in thousands of dollars), and y, selling price (in thousands of dollars) for apartment buildings. Data were collected on several properties recently sold and the following computer output was obtained. Analysis of Variance SOURCE DF Adj SS Regression 1 41587.3 Error 7   Total 8 51984.1 Predictor Coef SE Coef T-Value Constant 20.000 3.2213 6.21 X 7.210 1.3626 5.29 Regression Equation Y = 20.0 + 7.21 X (a) How many apartment buildings were in the sample?   (b) Write the estimated regression equation. ŷ =        (c) What is the value of  sb1?   Find the value of the test statistic. (Round your answer to two decimal places.)   Find the p-value. (Round your answer to three decimal places.) p-value =

Suppose a doctor measures the height, x, and head circumference, y, of 8 children and obtains the data below. The correlation coefficient is 0.858 and the least squares regression line is y = 0.228x +11.187. Complete parts (a) and (b) below. Height, x 27.5 25.75 26.5 25.5 27.25 26.25 25.75 27.25 27 27.25 27 Head Circumference, y 17.4 17.2 17.2 16.9 17.6 17.1 17.1 17.4 17.4 17.3 17.3 (a) Compute the coefficient of determination, R². R² =% (Round to one decimal place as needed.) (b) Interpret the coefficient of determination and comment on the adequacy of the linear model. Approximately % of the variation in (Round to one decimal place as needed.) is explained by the least-squares regression model. According to the residual plot, the linear model appears to be

In a regression analysis involving 25 observations, the following estimated regression equation was developed.ŷ = 10 – 18x1 + 3x2 + 14x3Also, the following standard errors and the sum of squares were obtained.Sb1 = 3 Sb1 = 6 Sb1 = 7SST = 4,800 SSE = 1,296The multiple coefficient of determination is _____.   a. .27     b. .73     c. .33     d. .50

Rewrite the regression model to include coefficients from your regression analysis output and then answer the following question   What would be the company's loss if the significant variable(s) change per unit?     SUMMARY OUTPUT                                   Regression Statistics               Multiple R 0.93082               R Square 0.866425               Adjusted R Square 0.85833               Standard Error 4108.993               Observations 36                                 ANOVA                   df SS MS F Significance F       Regression 2 3.61E+09 1.81E+09 107.0261 3.75E-15       Residual 33 5.57E+08 16883824           Total 35 4.17E+09                                 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 3996.678 6603.651 0.605223 0.549171 -9438.55 17431.91 -9438.55 17431.91 X Variable 1 43.5364 3.589484 12.12887 1.05E-13 36.23354 50.83926 36.23354 50.83926 X Variable 2…

The computer-science aptitude score, x, and the achievement score, y (measured by a comprehensive final), were measured for 10 students in a beginning computer-science course. The results were as follows. Calculate the estimated standard error of regression, Sb1. (Give your answer correct to two decimal places.) x 4 16 20 13 22 21 15 20 19 16 y 20 20 25 35 26 27 24 29 16 28