An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regressionequation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes and total cost data fora manufacturing operation.Production Volume (units)Total Cost ($)450400050048006005200700610075065008007300The data on the production volume x and total cost y for particular manufacturing operation were used to develop the estimated regression equation ý = 272.03 + 8.49x.a. The company's production schedule shows that 550 units must be produced next month. Predict the total cost for next month.(to 2 decimals)ý* =b. Develop a 98% prediction interval for the total cost for next month.(to 2 decimals)t-value(to 3 decimals)Spred(to 2 decimals)Prediction Interval for an individual Value next month) (to whole number)c. If an accounting cost report at the end of next month shows that the actual production cost during the month was $6,000, should managers be concerned about incurring such a high total cost forthe month? Discuss.Based on one month, $6,000 - Select your answer - v outside the upper limit of the prediction interval. A sequence of five to seven months with consistently high costs should cause concern.

Answered: Image /qna-images/answer/7ccd0b1c-7307-4715-a9cd-acdd976a1c31.jpg

Answered: he data on the production volume x and…

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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Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed lemon/crash data, where lemon imports are in metric tons and the fatality rates are per 100,000 people, find the best predicted crash fatality rate for a year in which there are 425 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports Crash Fatality Rate 226 270 16 15.8 364 481 521 15.5 15.4 14.9
The equation used to predict annual cauliflower yield (in pounds per acre) is y =24,231 + 4.417x, - 4.677x,, where x, is the number of acres planted and x, is the number of acres harvested. Use the multiple regression equation to predict the y-values for the values of the independent variables. (a) x, = 36,100, X2 = 36,500 (b) x, = 37,800, X2 = 38,100 (c) X4 = 38,800, X2 = 39,000 (d) x, = 42,100, X2 = 42,200 %3D %3D (a) The predicted yield is pounds per acre. (Round to one decimal place as needed.)
Given r2=0.9316, SSE=60.55 and the slope of the regression equation is positive.Compute: SST= Round to 4 decimal places. SSR= Round to 4 decimal places. r= Round to 4 decimal places.
A chemical process was studied using a 2k design. Using ANOVA, the results have been modeled to produce the following linear equation in coded units: Vield =28.360+0.615 Temperature +0.485 Time Along the direction of steepest ascent. how many coded units must be moved in the Time direction for each step of one coded unit in the Temperature direction? Express your answer to 3 decimal places (XXXXX) Your Answer:
a snow plower recorded inches of snow fall and the yield by measure of square acreage over the previous 5 seasons. The regression equation is determined to be y=38.4+6.3x where x represents the inches of snowfall and y the measure of yield. 1. use the best fitting line to predict yield for 6 inches of snow 2. one of the records is (6,75) what is teh residual if x is 6
A regression analysis was performed to determine if there is a relationship between hours ofTV watched per day r) and number of sit ups a person can do (y). The results of the regression were: у-ах+b a=-0.827 b=35.329 r2=0.540225 r=-0.735 Use this to predict the number of sit ups a person who watches 13.5 hours of TV can do, and please round your answer to a whole number.
The line of best fit through a set of data is y = 13.661 – 3.451x According to this equation, what is the predicted value of the dependent variable when the independent variable has value 80? y = Round to 1 decimal place.
The volume (in cubic feet) of a black cherry tree can be modeled by the equation y = - 50.8 + 0.3x, +4.5x,, where x, is the tree's height (in feet) and x, is the tree's diameter (in inches). Use the multiple regression equation to predict the y-values for the values of the independent variables. x, = 70, x, = 8.6 The predicted volume is cubic feet. (Round to one decimal place as needed.)
A regression was run to determine if there is a relationship between hours of TV watched per day (xx) and number of situps a person can do (yy). The results of the regression were: y=ax+ba=-1.392b=32.952r2=0.527076r=-0.726Use this to predict the number of situps a person who watches 2 hour(s) of TV can do, and please round your answer to a whole number.
In calculating a simple regression for average number of drinks consumed (x) and grade point average (y), you get a slope coefficient (b) of -.15 and a y intercept of 2.50. Using the formula Y = a + bX, what would the predicted grade point average be for a student who averaged 1.0 drinks per week?
its not 35,500.

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