X 0.21 0.14 0.11 0.13 0.12 0.13 1.10 1.50 1.90 2.20 2.60 3.20 a. Fit a linear regression equation b. Compute forr
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- Consider the regression equation In Y = 4.37 +0.2X₁ +0.3X2- a. Predict the value of Y when X₁ = 8.5 and X₂ = 4.8. b. Interpret the meaning of the regression coefficients 100 b₁, and 100 b₂. a. The predicted value of Y is. (Type an integer or decimal rounded to two decimal places as needed.) b. Choose the correct answer below. OA. Holding constant the other variables, for every one percent increase in X, or X₂, the value of Y increases by b₁ or b2 units, respectively. OB. Holding constant the other variables, for every one unit increase in X, or X₂, the value of Y increases by b, or b2 percent, respectively. OC. For every decrease of one unit of In Y, holding bo constant, the estimated change in X, or X₂ is 100.b, or 100 b₂ units, respectively. OD. Holding constant the other variables, for every one unit increase in X, or X₂, the value of Y increases by 100 b₁ or 100 b2 percent, respectively. O E. Holding constant the other variables, for every one percent increase in X, or X₂, the…Annual high temperatures in a certain location have been tracked for several years. Let X represent the number of years after 2000 and Y the high temperature. Based on the data shown below, calculate the linear regression equation using technology (each constant to three decimal places). y 34.38 2. 35.56 3 37.64 4 36.22 38.8 6. 39.68 7. 40.66 8 38.84 9 39.32 10 40.3 11 43.78 12 43.16 13 43.24 14 43.62 Question Help: D Video Submit QuestionConsider the regression equation In Y₁ = 3.89 +0.5X₁ +0.3X₂i a. Predict the value of Y when X₁ = 7.1 and X₂ = 4.9. b. Interpret the meaning of the regression coefficients 100.b₁, and 100.b₂.
- 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. -3.87A regression model relating a, number of salespersons at a branch office, to y, annual sales at the office (in thousands of dollars) provided the following regression output. Where ntotal = 32, ANOVA df MS F Significance F Regression 6,665.7 Residual Total 8,845.1 Coefficients Standard Error t Stat P-value Intercept 83.0 10.915 Number of 42.0 5.864 Salespersons a. Write the estimated regression equation (to whole number). b. Compute the F statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals) F-value p-value is c. Compute the t statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals) Select your answer , we Select your answer - v Họ t Stat p-value is Select your answer - , we Select your answer - v Ho: B, = d. Predict the annual sales at the Memphis branch office. This branch employs 11 salespersons. $ thousand (to whole number)A set of n = 25 pairs of scores (X and Y values) produces a regression equation Y = 3X – 2. Findthe predicted Y value for each of the following X scores: 0, 1, 3, -2.
- Let x be the size of a house (in square feet) and y be the amount of natural gas used (therms) during a specified period. Suppose that for a particular community, x and y are related according to the simple linear regression model with the following values. ? = slope of population regression line = 0.016 ? = y intercept of population regression line = −7 Question: Graph the population regression line by first finding the point on the line corresponding to x = 1,000 and then the point corresponding to x = 2,000, and drawing a line through these points.Graph the scatterplot and find the equation of the regression line GDP. CO2 emissions (in millions metric tons) 1.7. 552.6 1.2. 462.3 2.5. 475.4 2.8. 374.3 3.6. 748.5 2.2. 400.9 0.8. 253.0 1.5. 318.6 2.4. 496.8 5.9. 1180.6Annual high temperatures in a certain location have been tracked for several years. Let X represent the number of years after 2000 and Y the high temperature. Based on the data shown below, calculate the linear regression equation using technology (each constant to 2 decimal places). x y 4 36.68 5 35.85 6 35.52 7 35.99 8 38.46 9 38.93 10 38 11 38.07 12 39.54 13 40.11 14 41.58 The equation is y^ = x + Interpret the slope For each additional 33.38 years, the annual high temperature will increase by 1 degree on average. For each additional 0.52 years, the annual high temperature will increase by 1 degree on average. For each additional year, the annual high temperature will increase by 0.52 degrees on average. For each additional year, the annual high temperature will increase by 33.38 degrees on average. Interpret the y-intercept In 2000, the temperature was about 33.38. It does not make sense to interpret the intercept in this scenario. In 2004, the…
- Jensen Tire & Auto is in the process of deciding whether to purchase a maintenance contract for its new computer wheel alignment and balancing machine. Managers feel that maintenance expense should be related to usage, and they collected the following information on weekly usage (hours) and annual maintenance expense (in hundreds of dollars). Weekly Usage Annual (hours) Maintenance Expense 15 22 12 27 22 35 30 42 34 52 19 36 26 38 33 44 42 57 40 45 a. Develop the estimated regression equation that relates annual maintenance expense (in hundreds of dollars) to weekly usage hours (to 3 decimals). Expense = Weekly Usage b. Test the significance of the relationship in part (a) at a 0.05 level of significance. Compute the value of the F test statistic (to 2 decimals). The p value is - Select your answer - What is your conclusion? - Select your answer c. Jensen expects the new machine to be used 30 hours per week. What is the expected annual maintenance expense in hundreds of dollars (to 2…5. 50 29 47 33 1 46 28 42 20 3 58 21 1 42 22 The multiple linear regression equation of the table is shown below: ý = - 6.99 + 0.17x1 + 0.03r2 Use the equation to predict the value of y at ¤1 = 44.5 and x2 = 24.3 (Round to 2 decimal places)A regression analysis was conducted to investigate the relationship between the total charge and travel time for a certain car service. Computer output from a linear regression analysis is shown below. The analysis was performed on a sample of 24 observations. Term CoefCoef SE CoefSE Coef Constant −1.55−1.55 0.945 Travel time 0.22 0.023 Assume that the conditions for inference for the slope of the regression equation have been met. Which of the following defines the margin of error of a 90 percent confidence interval for the slope of the least-squares regression line? 1.321(0.945)1.321(0.945) A 1.717(0.945)1.717(0.945) B 1.717(0.22)1.717(0.22) C 1.321(0.023)1.321(0.023) D 1.717(0.023) E