he following data is given: 1 3 4 6. 9 12 14 y 4 5 6. 7 9. 11 se linear least-squares regression to determine the coefficients m and b in the function y = m:
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- The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.The following estimated regression equation is based on 10 observations yhat = 30.12 + .60x1 + .48x2 SST = 680.3, SSR= 601.4, Sb1 = .0813 and Sb2 = .0567 a. Compute MSR and MSE b. Compute F and perform the appropriate F test. Use alpha = .05. c. Perform a t test for the significance of B1. Use alpha = .05. d. Perform a t test for the significance of B2. Use alpha = .05.The following information pertains to a simple least squares regression for DEF Corporation: Mean value of the dependent variable 30Mean value of the independent variable 8Coefficient of the independent variable 3Number of observations 12 What is the "a" value for the leasts-quares regression model? a. 60b. 30c. 6d. 0
- The following estimated regression equation is based on 10 observations y = 30.12 + .60x1 + .48x2 SST = 680.3, SSR= 601.4, Sb1 = .0813 and Sb2 = .0567 a. Compute MSR and MSE b. Compute F and perform the appropriate F test. Use alpha = .05. c. Perform a t test for the significance of B1. Use alpha = .05. d. Perform a t test for the significance of B2. Use alpha = .05.Consider the following correlations -0.9 , -0.5 , -0.2 , 0 , 0.2 , 0.5 and 0.9. For each give the fraction of the variation in y that is explained by the least-squares regression of y on x.Given are five observations for two variables, x and y. xi 3 8 12 18 20 yi 54 57 50 24 11 -select your answer choices- b. The least squares line provided an (good, bad) fit; __ % of the variability in y has been explained by the estimated regression equation (to 1 decimal)
- Suppose Wesley is a marine biologist who is interested in the relationship between the age and the size of male Dungeness crabs. Wesley collects data on 1,000 crabs and uses the data to develop the following least-squares regression line where ? is the age of the crab in months and ?ˆ is the predicted value of ?, the size of the male crab in cm. ?ˆ=8.1312+0.5226? What is the value of ?ˆ when a male crab is 23.0736 months old? Provide your answer with precision to two decimal places. ?ˆ = Interpret the value of ?. The value of ?ˆis the predicted size of a crab when it is 23.0736 months old. the predicted incremental increase in size for every increase in age by 23.0736 months. the predicted number of crabs out of the 1,000 crabs collected that will be 23.0736 months old. the probability that a crab will be 23.0736 months old.Suppose Wesley is a marine biologist who is interested in the relationship between the age and the size of male Dungeness crabs. Wesley collects data on 1,000 crabs and uses the data to develop the following least-squares regression line where ? is the age of the crab in months and ?̂ is the predicted value of ?, the size of the male crab in cm. ?̂=8.2052+0.5693? What is the value of ?̂ when a male crab is 21.7865 months old? Provide your answer with precision to two decimal place10. For the following data, compute the least squares regression line for predicting gpagiven SAT.SAT: 500 530 590 660 610 700 570 640gpa: 2.3 3.1 2.6 3.0 2.4 3.3 2.6 3.5
- Consider the following five data points: X -1 0 1 2 3 Y -1 1 2 4 5 a. Use regression analysis to calculate by hand the estimated coefficients of the equation Y = B + aX. b. Compute the standard error and the t-statistics for the coefficient of X.For the following data set: x 3.9 6.1 4.6 3.7 1.8 3.3 3.4 y 4.2 4.7 5.7 4.5 9.6 5.2 4.3 Part 1 of 4 (a) Compute the least-squares regression line. Round the answers to at least four decimal places. Regression line equation: =y .In a study measuring the relationship between height in centimeters and annual income in dollars, it has been determined that for Group 1, r2 =0.15 and for Group 2, r2 =0.10 where r denotes the correlation between the two variables. Least-squares regression lines are fitted to the observations from each group. Which of the following statement is true: A. There could be a positive relationship between the two variables for Group 1 and a negative relationship between the two variables for Group 2 B. The sum of the residuals for Group 1 is greater than the sum of the residuals for Group 2. C. Measuring the height in inches would increase the value of r2 for both groups. D. None of the answer options is true Can you also explain the difference between r and r2, and why least square regressions are used?