The regression equation is ý = When x is 5 this gives ý =
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The following sample observations were randomly selected. (Round intermediate calculations and final answers to 2 decimal places.)
| x: | 5 | 5 | 3 | 6 | 7 |
| y: | 4 | 6 | 5 | 7 | 2 |
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- The following sample observations were randomly selected. (Round intermediate calculations and final answers to 2 decimal places.) x: 3 5 3 7 6 y: 2 6 5 7 6 a. The regression equation is ŷ = + x b. When x is 4 this gives ŷ =The following sample observations were randomly selected. (Round intermediate calculations and final answers to 2 decimal places.) x: 4 5 3 6 10 y: 4 6 5 7 7 Click here for the Excel Data File a. The regression equation is ŷ = + x b. When x is 7 this gives ŷ =The following sample of observations was randomly selected. x 5 3 6 3 4 4 6 8 y 13 15 7 12 13 11 9 5 a. Determine the regression equation.b. Determine the value of ŷ when x is 7
- 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.For a sample of over 160 college students, the following variables were measured: Y = height X1 = mother’s height X2 = father’s height X3 = 1 if male, 0 if female The goal is to predict student’s height using the mother’s and father’s heights, and sex, where sex is categorized using the variable “male” = 1 if male, 0 if female. Question 1 The regression model is __________________________________________ Regress command results (remember that we now have n = 165 cases; we removed one outlier): Source | SS df MS Number of obs = 165 -------------+------------------------------ F( 3, 161) = 104.38 Model | 1679.17741 3 559.725803 Prob > F = 0.0000 Residual | 863.31653 161 5.36221447 R-squared = 0.6604 -------------+------------------------------ Adj R-squared = 0.6541 Total | 2542.49394 164 15.5030118 Root MSE = 2.3156…