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- can you help me explain the diagramFill in the blanksBreakfast cereals We saw in Chapter 7 that the calorie con-tent of a breakfast cereal is linearly associated with its sugar content. Is that the whole story? Here’s the output of aregression model that regresses Calories for each serving onits Protein(g), Fat(g), Fiber(g), Carbohydrate(g), andSugars(g) content.Dependent variable is CaloriesR-squared = 84.5, R-squared (adjusted) = 83.4,s = 7.947 with 77 - 6 = 71 degrees of freedomSource Sum ofSquares dfMeanSquare F-RatioRegression 24367.5 5 4873.50 77.2Residual 4484.45 71 63.1613Variable Coefficient SE(Coeff) t-Ratio P-ValueIntercept 20.2454 5.984 3.38 0.0012Protein 5.69540 1.072 5.32 60.0001Fat 8.35958 1.033 8.09 60.0001Fiber -1.02018 0.4835 -2.11 0.0384Carbo 2.93570 0.2601 11.3 60.0001Sugars 3.31849 0.2501 13.3 60.0001Assuming that the conditions for multiple regressionare met,a) What is the regression equation?b) Do you think this model would do a reasonably goodjob at predicting calories? Explain.c) To check the conditions, what…
- Annual Revenue million of dollars Franchise value of dollars 244 486 154 237 206 439 171 165 202 330 248 636 241 478 257 656 189 330 247 589 235 428 259 635 164 174 178 190 243 630 Dialog content ends PrintDone The value of a sports franchise is directly related to the amount of revenue that a franchise can generate. The accompanying data table gives the value and the annual revenue for 15 major sport teams. Suppose you want to develop a simple linear regression model to predict franchise value based on annual revenue generated. b. Use the least-squares method to determine the regression coefficients b0 and b1. b0 = enter your response here b1 = enter your response here (Round to two decimal places as needed.)The final grade in a particular course is determined by grades on the midterm and final. The grades for five students and the two grading systems are modeled by the following matrices. Call the first matrix A and the second B. Complete parts (a) and (b). Click to view the matrices. a. Describe the grading system that is represented by matrix B. Grading system 1 assigns 50% of the final grade to the midterm and 50% of the final grade to the final. Grading system 2 assigns 20% of the final grade to the midterm and 80% of the final grade to the final. b. Compute the matrix AB and assign each of the five students a final course grade first using system 1 and then using system 2. (89.5-100=A, 79.5-89.4 = B, 69.5-79.4 = C, 59.5-69.4D, below 59.5 = F) Grade System 1 System 2 ... Student 1 Student 2 Student 3 Student 4 Student 5 (Type A, B, C, D, or F.)Regression establishes functional relationship between and variable. a. Cross and Managerial O b. Mutual and Managerial O C. Average and Mutual O d. Independent and dependent
- In agricultural economics, a “supply response function” describes how supply of a commodity responds to changes in the price of that commodity. (production is the dependent variable,Independent variable: Price) Dataset: Year Seeded Area (hectares) Harvested Area (hectares) Average Yield (kg per ha) Production (tonnes) Price per Tonne ($/tonne) 1966 1,317,000 1,317,000 1,630 2,150,000 65 1967 1,424,000 1,424,000 1,720 2,449,000 60 1968 1,376,000 1,376,000 1,800 2,477,000 48 1969 1,012,000 1,012,000 1,720 1,742,000 46 1970 567,000 567,000 1,465 830,000 52 1971 1,019,000 1,019,000 1,975 2,014,000 50 1972 1,052,000 1,052,000 1,785 1,878,000 68 1973 1,214,000 1,214,000 1,725 2,095,000 158 1974 1,133,000 1,133,000 1,415 1,605,000 147 1975 1,255,000 1,255,000 1,690 2,123,000 130 1976 1,538,000 1,538,000 1,820 2,803,000 103…answer quicklyObjective [2.6] Situation: The Ipod Touch has been out for two years now and a lot of data has been collected. Relevant Relationship: There is a functional relationship between Price of an IPod Touch,p and Weekly Demand,s. Below is a table of data that have been collected Price,p,($) Weekly Demand, s,(1,000s) 150 170 190 210 230 250 215 202 198 188 178 171 A.. Find the linear model that best fits this data using regression and enter the model below (for entry round the linear parameter value to nearest 0.01 and constant parameter to nearest 1) S = T(p) = B. The squared correlation coefficient was Select an answer 0.95 (note: values less than 0.95 MAY mean the model is not appropriate for making predictions) Now answer these two questions using the UNROUNDED model parameters C. What does the model predict will be the weekly demand if the price of an ipod touch is $235 ? (nearest 100) D. According to the model at what should the price be set in order to have a weekly demand of 202,800…