a. Using Excel, develop the multiple regression equation for these data.b. What is the coefficient of determination for this regression equation? Do you think the superintendentis correct in his beliefs?c. If the certain school has an average SOL score of 74, with an average teacher salary of P27,500 and anaverage teacher tenure of 7.8 years. The superintendent has proposed to the school board a salaryincrease that would raise the average salary to P30,000 as well as a benefits program, with the goal ofincreasing the average tenure to 9 years. He has suggested that if the board passes his proposals, thenthe average SOL score will increase to 80. Is he correct, according to the forecasting model? Average Tenure ofAverage SOLAverage TeacherSchoolthe Teachers inScoreSalaryYears8134,3009.327828,70010.137626,5007.67736,2008.28435,9008.868632,50012.777931,8008.48.9138,20011.56.6827,1008.3107331,5007.3119037,60012.3128540,40014.2stLO

SOL Score Salary Tenure 1 81 34300 9.3 2 78 28700 10.1 3 76 26500 7.6 4 77 36200 8.2 5…

Answered: a. Using Excel, develop the multiple…

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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please use chart attatched. a. Explain the meaning of the slope of the regression line in this context. b. What is the predicted cost of maintenance for someone who racks up about 2,000 miles per month on a sedan? c. Suppose one of the observations used to get the data table above was a sedan owner who reported he drove 980 miles this month and spent about $450 on maintenance costs in the same month. What is the residual of this observation?
Suppose a new location opens in an area with a population of 144,000, an average income of$36,000, an average age of 27, and $2,000 spent on advertising in the previous month.a. Use your chosen regression to predict Gross Sales for the month at the new location. (I picked population)b. Suppose actual Gross Sales for the month were $420,624. Does this make sense,given your model and predicted value?12. Using your chosen regression model,a. Identify the slope and explain what it means, in the context of the model.b. Identify the initial value or y-intercept and explain what it means, in the context ofthe model.
Accountants at the GIll Co and Charted Brothers Accounting believed that several traveling executives were submitting unusually high travel vouchers upon returning from business trips. First, they took a sample of 200 vouchers submitted from the past year. Then they developed the following multiple-regression equation relating expected travel cost (Y) to a number of days on the road (X1) and distance traveled (X2) in miles: Y = 90.00 + 48.50X1 + 0.40X2 Here is additional information concerning the regression model: Sb1 = 0.038 Sb2 =0.019 R2 = 0.68 Se = 1.63 F-Statistic = 32.123 Durbin-Watson (d) statistic = 0.5436 a. Which of the independent variables appear to be statistically significant (at the 0.05 significant level) in explaining the expected travel cost for accountants
Which of the following is true of a linear regression line? a. Located as close as possible to all the points of a scatter chart. B. Is defined by an equation having 2 parameters: the slope and the intercept c. Provides an approximate relationship between the values of two parameters d. All of the above
In the section we introduced a descriptive measure of the utility of the multiple linear regression for making predictions. a. Define and interpret this descriptive measure. b. Identify the symbol used for this descriptive measure.
1. School administrators believe their freshman applications are influenced by two variables: tuition and the size of the applicant pool of eligible high school seniors in the state. The following data for an 8-year period show the tuition rates (per semester) and the sizes of the applicant pool for each year: Tuition in pesos Applicants Pool Applicants 27000 76,200 11,060 37500 78,050 10,900 41250 67,420 8,670 42000 70,390 9.050 46500 62,550 7,400 48750 59,230 7,100 52500 57,900 6,300 57900 60,080 6,100
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 The equation of the regression line is y = x+ | (Round to two decimal places as needed.) !!
Use the p-value criterion to find the best model for predicting the number of points scored per game by football teams using the accompanying National Football League Data. Does the model make logical sense? E Click the icon to view the National Football League Data. Determine the best multiple regression model. Let X, represent Rushing Yards, let X, represent Passing Yards, let X3 represent Penalties, let X4 represent Interceptions, and let Xg represent Fumbles. Enter the terms of the equation so that the Xy-values are in ascending numeral order by base. Select the correct choice below and fill in the answer boxes within your choice. (Type an integer or decimal rounded to three decimal places as needed.) Points/Game =+ OX 01+Og+O1 A. OB Points/Game = O C. Points/Game = OD. Points/Game = + Dx O E. Points/Game = Data table for the national football league Points/ Game Rushing Yards/ Game Passing Yards/ Penalties Interceptions Fumbles O Game 25.2 90.1 259.2 140 18 4 16.2 95.2 208.5 108…
Below table contains a data sample where X is the independent, and Y the dependent variable. Using the data, please conduct a regression analysis. Determine first the regression equation with the help of below graph and table, then answer all the questions. 1. The value of cell a is 2. The value of cell b is 3: The value of cell c is 4: The value of cell d is 5: The value of cell e is 6: The value of cell f is 7: The value of cell g is 8. The value of cell h is 9: The value of cell i is 10: The value of cell j is 11: The value of cell k is 12: The value of cell l is 13: The value of cell m is 14: The value of cell n is 15: The value of cell o is 16: The value of cell p is 17: The value of cell q is 18: The value of cell r is 19: The value of cell s is 20: The value of cell t is 21: The value of cell u is 22: The value of cell v is 23: The value of cell w is 24: The value of cell x is 25: The value of cell y is 26: The value of cell z is 27: The value of cell aa is 28: The value of cell…
In the graph shown below consider the horizontal line to represent the average y value for the data set and the slant line to represent the linear regression equation. use only the graph of the data to do the following:

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