The following estimated regression equation is based on 30 observations.The values of SST (Total Sum of Squares) and SSR (Regression Sum of Squares) are 1,803 and 1,761, respectively.**a. Compute $R^2$ (to 3 decimals).**\[ R^2 = \frac{\text{SSR}}{\text{SST}} \]**b. Compute $R^2_a$ (to 3 decimals).**\[ R^2_a = 1 - \left(\frac{(1 - R^2)(n-1)}{n-k-1}\right) \]Where $ n $ is the number of observations and $ k $ is the number of predictors.**c. Comment on the goodness of fit.**The estimated regression equation:\[\hat{y} = 17.5 + 4x_1 - 2.5x_2 + 7.7x_3 + 2.5x_4\]A dropdown menu is provided for selecting the comment on the goodness of fit with options:- provided an excellent fit- provided a moderately good fit- did not provide a good fit

Answered: The following estimated regression…

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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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 40inches. Is the result close to the actual weight of 352pounds? Use a significance level of 0.05.a. Chest size (inches) 41 54 44 55 39 51 Weight (pounds) 328 528 418 580 296 503 a.What is the regression equation? b. The best predicted weight for a bear with a chest size of 39 inches is _______pounds.
Please assist with question b
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 58 inches. Is the result close to the actual weight of 572 pounds? Use a significance level of 0.05. Chest size (inches) 46 57 53 41 40 40 Weight (pounds) 384 580 542 358 306 320 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=nothing+nothingx (Round to one decimal place as needed.)
The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x = 5 wins Click the icon to view the table of numbers of wins and earned run average. (b) x = 10 wins (c) x = 21 wins (d) x = 15 wins ERA 6- ERA 6- AERA 6- ERA 6- 4- 4- 4- 4- 2- 2- 2- 2- 0+ 6 0- 0- 0- 12 18 24 6. 12 18 24 12 18 24 6 12 18 24 Wins Wins Wins Wins (a) Predict the ERA for 5 wins, if it is meaningful. Select the correct choice below and, if necessary, fill in the answer box within your choice. A. ŷ= (Round to two decimal places as needed.) B. It is not meaningful to predict this value of y because…
Listed below are the overhead widths (cm) of seals measured from photographs and weights (kg) of the seals. Find the regression equation, letting the overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 1.8 cm, using the regression equation. Can the prediction be correct? If not, what is wrong? Use a significance level of 0.05. Overhead Width (cm) 7.3 7.4 9.8 9.5 8.8 8.5 Weight (kg) 152 187 286 247 237 231 The regression equation is y =+ (x. (Round the y-intercept to the nearest integer as needed. Round the slope to one decimal place as needed.)
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 90 mm Hg. Use a significance level of 0.05. Right Arm 103 102 96 76 76 Left Arm 174 167 149 148 148
USA Today reported that about 20% of all people In the United States are Illiterate. Suppose you take eleven people at random off a city street. P USE SALT (a) Make a histogram showing the probability distribution of the number of illiterate people out of the eleven people in the sample. 0.30 0.30 0.25 0.25 0.20 0.20 0.15 0.15 0.10 0.10 0.05 0.05 2 3 4 5 7. 8 9 10 11 0 1 2 3 4 5 6 78 9 10 11 0.30 0.30 0.25 0.25 0.20 0.20 0.15 0.15 0.10 0.10 0.05 0.05 0. 0 1 2 3 4 5 6 7 8 9 10 11 0 1 2 3 45 6 7 8 9 10 11 (b) Find the mean and standard deviation of this probability distribution. (Round your standard deviation to two decimal places.) people people Find the expected number of people in this sample who are illiterate. people
The following multiple regression printout can be used to predict a person's average annual salary given his or her years of employment and number of years of education beyond high school. Regression Analysis: Salary Versus YrsEm, Educ Coefficients Term Constant YrsEm Educ Coef 23,171 678 1,918 SE Coef 1,771 142 376 T-Value 13.08 4.77 5.10 P-Value 0.000 0.000 0.000 (a) Is the regression coefficient of education (Educ) statistically significant? (Use a = 0.05.) Given this output, the regression coefficient for education ---Select--- statistically significant. (b) Does the variable education belong in the model? Given this output, the variable education ---Select--- --Select--- belong in the model. (c) Given this output, which of the following is the correct interpretation for Education in this model? O An individual with 4 years of education beyond high school can expect an annual salary of $7,672. O The estimated change in the average value of annual salary of getting an additional…
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 90 mm Hg. Use a significance level of 0.05. Right Arm 101 100 92 75 75 O Left Arm 174 167 181 149 147 Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is y = + x. (Round to one decimal place as needed.) Given that the systolic blood pressure in the right arm is 90 mm Hg, the best predicted systolic blood pressure in the left arm is mm Hg. (Round to one decimal place as needed.)
Bluereef real estate agent wants to form a relationship between the prices of houses, how many bedrooms, House size in sq ft and Lot Size in sq ft. The data pertaining to 100 houses were processed using MINITAB and the following is an extract of the output obtained: The regression equation is Price = B + ¢Bedroom + yHouse Size + ALot Size Predictor Сoef SE Coef т P Constant 37718 14177 2.66 ** Bedrooms 2306 6994 0.33 0.742 House Size 74.3 52.98 0.164 Lot Size -4.36 17.02 -0.26 0.798 S= 25023 R-Sq=56.0% R-Sq(adj)=54.6% Source DF MS F P Regression 3 76501718347 25500572782 Residual Error 96 60109046053 626135896 Total 99 • Is y significantly different from -0.5? Perform the F test at the 1% level, making sure to state the null and alternative hypotheses. Give an interpretation to the term “R-sq" and comment on its value.
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 80 mm Hg. Use a significance level of 0.05. Right Arm 100 99 93 77 77 Q Left Arm 174 168 148 148 146 Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is ŷ=+x. (Round to one decimal place as needed.) mm Hg. Given that the systolic blood pressure in the right arm is 80 mm Hg, the best predicted systolic blood pressure in the left arm is (Round to one decimal place as needed.) Data table Critical Values of the Pearson Correlation Coefficient r α = 0.05 α = 0.01 0.950 0.990 0.959 0.878 0.811 0.917 0.754 0.875 0.707 0.834 0.666 0.798 0.632 0.765 0.602 0.735 0.576 0.708 0.553 0.684 0.532 0.661 0.514 0.641 0.497 0.623 0.482…

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