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- Two lines are proposed to describe the relationship between x and y for a particular data set. Shown below are the lines and the sum of squared error for each line. Line1: yˆ = 5+ 4x, Sumofsquarederror= 48.6 Line2: yˆ = 6 + 3.5x, Sumofsquarederror= 40.8 One of these two lines is the regression line. Which line is the regression line?Question 3 Based on the data shown below, calculate the regression line (show each value to two decimal places) valuations 3 12.88 4 9.24 7.8 6. 6.96 6.82 8 7.78 5.84 10 5.3 Submit Question ..jpg pic 16131095275...jpg pic_16131095275..jpg W Zoomday17bsp21.docx pic_1615670389..jpg 84,258 DOO 20 F3 % & * 9. 4 く○Which of the variables is the indepenent variable and dependent variable for the following question. fit a simple linear regression model to predict latitudes using average monthly range lat= latitudes range= the average monthly range between mean montly maximum and minimum temperatures for a selected set of US cities.
- A consumer advocacy group recorded several variables on 140 models of cars. The resulting information was used to produce the following regression output that relates the city gas mileage (in mpg) and the engine displacement (in cubic inches). The regression equation is mpg_city= 35.5 - 0.0696 * displacement We have a car that has an engine with 141 cubic inches. Based on this output, what city gas mileage would you predict for this car?____ (Round answer to the nearest hundredth (2 decimal places.)Use the given dataset*note: Gender takes on a value of 1 if the student is male, and 0 otherwise Estimate a linear regression model relating overall grade weighted average (OGWA) of student to their gender, available internet speed (mbps) and previous term’s grade weighted average (lgwa)a. Interpret the slope coefficients (discuss their values and statistical significance)b. Are the coefficients jointly statistically significant? Explain your answer.c. How much of the variability of the overall grade weighted average is explained by the variability of the model?Use the Manufacturing database from “Excel Databases.xls” on Blackboard. Use Excel to develop a multiple regression model to predict Cost of Materials by Number of Employees, New Capital Expenditures, Value Added by Manufacture, and End-of-Year Inventories. Use Excel to perform a test of the overall model. Write the test statistic. Round your answer to 2 decimal places SIC Code No. Emp. No. Prod. Wkrs. Value Added by Mfg. Cost of Materials Value of Indus. Shipmnts New Cap. Exp. End Yr. Inven. Indus. Grp. 201 433 370 23518 78713 4 1833 3630 1 202 131 83 15724 42774 4 1056 3157 1 203 204 169 24506 27222 4 1405 8732 1 204 100 70 21667 37040 4 1912 3407 1 205 220 137 20712 12030 4 1006 1155 1 206 89 69 12640 13674 3 873 3613 1 207 26 18 4258 19130 3 487 1946 1 208 143 72 35210 33521 4 2011 7199 1 209 171 126 20548 19612 4 1135 3135 1 211 21 15 23442 5557 3 605 5506 2 212 3 2 287 163 1 2 42 2 213 2 2 1508 314 1 15 155 2 214 6 4 624 2622 1 27 554 2 221…
- Construct a scatter plot in Excel with FloorArea as the independent variable and AssessmentValue as the dependent variable. Insert the bivariate linear regression equation and r^2 in your graph. Do you observe a linear relationship between the 2 variables? FloorArea (Sq.Ft.) Offices Entrances Age AssessedValue ($'000) 4790 4 2 8 1796 4720 3 2 12 1544 5940 4 2 2 2094 5720 4 2 34 1968 3660 3 2 38 1567 5000 4 2 31 1878 2990 2 1 19 949 2610 2 1 48 910 5650 4 2 42 1774 3570 2 1 4 1187 2930 3 2 15 1113 1280 2 1 31 671 4880 3 2 42 1678 1620 1 2 35 710 1820 2 1 17 678 4530 2 2 5 1585 2570 2 1 13 842 4690 2 2 45 1539 1280 1 1 45 433 4100 3 1 27 1268 3530 2 2 41 1251 3660 2 2 33 1094 1110 1 2 50 638 2670 2 2 39 999 1100 1 1 20 653 5810 4 3 17 1914 2560 2 2 24 772 2340 3 1 5 890 3690 2 2 15 1282 3580 3 2 27 1264 3610 2 1 8 1162 3960 3 2 17 1447Employee Y X1 X2 1 100 10 7 2 90 3 10 3 80 8 9 70 5 4 5 60 5 8 6 50 7 5 7 40 1 4 8 30 1 1 4.please do all parts! The estimated regression equation for this data set is y=4.4878+1.9549x. Part A: (in image) Part B: is the linear function is the appropriate regression function for this data set? Part C: do the residuals have a constant variance? Part D: are the residuals independent? Part E: are the error terms are normally distributed? y x22 821 818 846 2241 2254 2276 3258 3268 32
- define and state the difference between the three terms association, correlation and causation. find the regression line between the height of the strawberry plant and the water it gets per day and interpret the intercept and slope coefficients. find a 95% confidence interval around the plant estimate of the slope parameter from your model.Listed below are the overhead widths (am) of seals measured from photographs and weights (kg) of the seals. Find the regression equation, letting the overhead width be the predictor 0) vanable Find the best predicted weight of a seal if the overhead width measured from a photograph is 2 am, using the regression equation Can the prediction be correct? it not, what is wrong? Use a significance level of 0 05 Overhead Width (cm) Weight (kg) 7.2 7.3 163 98 261 94 8.7 84 129 218 211 204 The regression equation is y-Ox (Round the y-intercept to the nearest integer as needed. Round the slope to one decimal place as needed) The best predicted weight for an overhead width of 2 cm, based on the regression equation, isNg (Round to one decmal place as needed) Can the prediction be correct? If not, what is wrong? OA The prediction cannot be correct because a negative weight does not make sense. The width in this case is beyond the scope of the avatable sample data OB The prediction cannot be correct…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 50 inches. Is the result close to the actual weight of 427 pounds? Use a significance level of 0.05. Chest_size_(inches) Weight_ (pounds)49 36851 38253 42061 48157 45745 287 What is the regression equation? y=___+___x (Round to one decimal place as needed.) What is the best predicted weight of a bear with a chest size of 50 inches? The best predicted weight for a bear with a chest size of 50 inches is __ pounds. (Round to one decimal place as needed.) Is the result close to the actual weight of 427 pounds?
