The following regression is fitted using variables identified that could be related to studentrequestedloan amount, LOAN-AMT($) for returning students of a certain University.LOAN AMT = a + ß ACCEPT + y PREV + λ OUTSWhere ACCEPT = the percentage of applicants that was accepted by the university, PREV=previous loan amount and OUTS outstanding loan amountThe data was processed using MNITAB and the following is an extract of the output obtained:PredictorConstantACCEPTPREVOUTSS = 2685Coef-26780116.00-4.2170.85R-Sq = 69.6%Analysis of VarianceDF3SourceRegressionResidual Error 49Total52SSEXHIBIT 2St Dev611537.1714.1215.778081393713531930511161332421a) What is dependent and independent variables?b) Fully write out the regression equationT*3.14-0.304.49MS2693797907208021c) What is the sample size used in this investigation?d) Fill in the blanks identified by *** and ****.e) Is ẞ significant, at the 5% level of significance?P0.0000.003**0.000R-Sq (adj)= 67.7%F37.37P0.00

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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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The following table presents the orders of Samson Company for the last 36 months (3 years).MonthOrder Year 1Order Year 2Order Year 3January502614712February408592698March491584686April456532644May481599694June511604702July522624724August500612716September510625732October512627740November520650745December536680756Use the data in the above table and regression analysis to forecast the orders for the next 12 months (4th year). Include your excel work sheet and your work in your write up. Show the regression equation, values of intercept, slope, correlation coefficient and coefficient determination and the forecast of orders for the next 12 months.Explain how you could make your forecast’s results more reliable by incorporating a qualitative research to your quantitative results. Previous
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The table below gives the age and bone density for 5 women. Use the equation of the regression line, y= b0 + b1x, for predicting a women's bone density based on her age. The correlation coefficient may or may not be statically significant for the data given. Remember it wouldn't be appropiate to use regression line to make a prediction if the correlation coefficient isn;t statically significant. (y has a "hat" on the top) age 39 51 54 56 67 bone density 355 349 347 315 313 Find the estimated slope. Rund your answer to three decimal places. Find the estimated y-intercept. Round your answer to three decimal places. Determine the value of the dependent variable y at x+ 0 (y has a "hat" onthe top) Find the estimated value of y when x = 51. Round your answer to three decimal places. Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the valueof the…
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Tire pressure (psi) and mileage (mpg) were recorded for a random sample of seven cars of thesame make and model. The extended data table (left) and fit model report (right) are based on aquadratic model. Calculate R2. Describe what this value means in the context of the problem.
when a regression is used as a method of predicting dependent variables from one or more independent variables. How are the independent variables different from each other yet related to the dependent variable?
The following regression is fitted using variables identified that could be related to student requestedloan amount, LOAN-AMT($) for returning students of a certain University. ????−??? = ? + ? ?????? + ? ???? + ? ????Where ACCEPT = the percentage of applicants that was accepted by the university, PREV = previous loan amount and OUTS =outstanding loan amountThe data was processed using MNITAB and the following is an extract of the output obtained:EXHIBIT 2Predictor Coef StDev T PConstant -26780 6115 * 0.000ACCEPT 116.00 37.17 3.14 0.003PREV -4.21 14.12 -0.30 **OUTS 70.85 15.77 4.49 0.000S = 2685 R-Sq = 69.6% R-Sq(adj) = 67.7%Analysis of VarianceSource DF SS MS F PRegression 3 808139371 269379790 37.37 0.00Residual Error 49 353193051 7208021Total 52 1161332421a)What is dependent and independent variables? b)Fully write out the regression equation c)What is the sample size used in this investigation? d)Fill in the blanks identified by ‘*’ and ‘**’. e)Is β significant, at the 5% level of…
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