The least-square regression line for the given data is \( \hat{y} = 0.449x - 30.27 \). Determine the residual of a data point for which \( x = 98 \) and \( y = 15 \), rounding to three decimal places.| Temperature, \( x \) | 72 | 85 | 91 | 90 | 88 | 98 | 75 | 100 | 80 ||------------------------|----|----|----|----|----|----|----|-----|----|| Number of absences, \( y \) | 3 | 7 | 10 | 10 | 8 | 15 | 4 | 15 | 5 |Options:- A. 28.732- **B. 1.268**- C. 121.535- D. 13.732To find the residual, use the equation to calculate the predicted value of \( y \) when \( x = 98 \), and subtract this from the actual \( y \)-value (15). The residual is the difference between the observed value and the predicted value.

given data regression equation y^ = 0.449x - 30.27for x = 98, y = 15find residual. for x = 98y^ = 0.449(98)-30.27 = 13.732residual = y - y^ = 15-13.732 =1.268answer : (B) 1.268

Answered: The least-square regression line for…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Given are five observations for two variables, x and y. Use the estimated regression equation: y = 73.9561 - 3.1463x (NEED ANSWERS FOR D and E)
A. run a simple regression- dependent variable is Weeks, independent variable is Age. B. run a multiple regression with dependent variable weeks and independent variable-age, married, head, manager and sales. C. Create the regular and standardized residual plots for both. Please show the tables when entering values of the regression for both the outputs and the scatter plots.
Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. X 7 14 10 11 15 12 6. 13 9. у 5.27 6.91 7.95 8.18 1.83 5.83 8.09 3.71 7.67 7.38 6.49 x (Round to two decimal places as needed.) %3D + Create a scatterplot of the data. Choose the correct graph below. A. В. OC. O D. .y 25- Ay 25- y 25- 25- 20- 20- 20- 20- 15- 15 15- 15- 103 105 103 105 5- 5극 53 5극 X X 0- 0- 0- 0 5 10 15 20 25 5 10 15 20 25 05 10 15 20 25 5 10 15 20 25 Identify a characteristic of the data that is ignored by the regression line. A. There is no trend in the data. B. There is an influential point that strongly affects the graph of the regression line. C. The data has a pattern that is not a straight line. D. There is no characteristic of the data that is ignored by the regression line. bo00 0
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 43 inches. Is the result close to the actual weight of 237 pounds? Use a significance level of 0.05. Chest size (inches) 50 54 Weight (pounds) 279 44 54 40 36 D 339 219 292 201 116 × Critical Values of the Pearson Correlation Coefficient r Click the icon to view the critical values of the Pearson correlation coefficient i What is the regression equation? ŷ=+x (Round to one decimal place as needed.) Critical Values of the Pearson Correlation Coefficient r n α = 0.05 α=0.01 NOTE: To test Ho: p=0 4 0.950 0.990 5 0.878 0.959 against H₁: p0, reject Ho if the absolute value of r is 6 0.811 0.917 7 0.754 0.875 greater than the critical value in the table. 8 0.707 0.834 9 0.666 0.798 10 0.632 0.765 11 0.602 0.735 12 0.576 0.708 13 0.553 0.684 14 0.532 0.661 15 0.514 0.641 16 0.497 0.623 17…
Given are five observations for two variables, x and y. Use the estimated regression equation: y = 73.9561 - 3.1463x (NEED ANSWERS FOR A, B, C, D, E)
Suppose that a regression line is found to be ý = 0.5470x +7.7000 What is the predicted value for a = 7? O a. 11.53 O b. 54-45 C. 53-35 O d. -3.87
Listed below is the multiple regression equation for predicting Y by X₁ through Xs. Y is the number of sales per month. X₁ is the number of sales calls made X2 is the number of hours on the showroom floor X3 is the amount spent on radio ads X is the number of text messages sent Xs is the number of email messages sent Regression Statistics R Square 0.634 Standard Error 7.6796 Observations 45 Intercept X₁ X₂ X3 XA Xs Coefficients Standard Error 6.8163 0.1005 -0.3207 0.2084 0.1221 0.0943 77.1211 1.9439 -11.123 0.1144 11.34 1.23 What is the computed value of the F statistic you would use to test the significance of the entire model? Round your answer to two decimal places.
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Run a regression analysis on the following bivariate set of data with y as the response variable. x y 28.8 51.5 11.8 54.7 2.9 45.5 18.5 45.3 18.5 52.4 29 62.9 2.9 56.8 24.9 51.3 Find the correlation coefficient and report it accurate to three decimal places. What proportion of the variation in y can be explained by the variation in the values of x? Report answer as a percentage accurate to one decimal place. (If the answer is 0.84471, then it would be 84.5%...you would enter 84.5 without the percent symbol.)%Based on the data, calculate the regression line (each value to three decimal places)ˆyy^ = x + Predict what value (on average) for the response variable will be obtained from a value of 14.8 as the explanatory variable. Use a significance level of α=0.05α=0.05 to assess the strength of the linear correlation.What is the predicted response value? (Report answer accurate to one decimal place.)ˆyy^ =

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