7. The equation of the regression line is given by A. y = −116.01 + 0.12x B. y = 1321.32 − 7.64x C. y = 116.01 + 0.12x D. y = 7.64x + 1321.32
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7. The equation of the regression line is given by
A. y = −116.01 + 0.12x
B. y = 1321.32 − 7.64x
C. y = 116.01 + 0.12x
D. y = 7.64x + 1321.32
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- What is regression analysis? Describe the process of performing regression analysis on a graphing utility.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 regression equation 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 for a manufacturing operation.An important application of regression analysis is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, one can estimate the cost associated with a particular manufacturing volume. Consider the following sample of monthly production volumes and total costs data for a manufacturing operation for the year 2018. Month (2018) Volume of Production (Units) Total Costs ($) Jan 500 6000 Feb 350 4000 Mar 450 5000 Apr 550 5400 May 600 5900 Jun 400 4000 Jul 400 4200 Aug 350 3900 Sept 400 4300 Oct 600 6000 Nov 700 6400 Dec 750 7000 1) Calculate the (Pearson) correlation coefficient between production volume and total costs in this problem. 2) What is the most suitable interpretation of the (Pearson) correlation coefficient between production volume and total costs in this problem? 3) The equation of the regression line is given by...? 4) How…
- An important application of regression analysis is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, one can estimate the cost associated with a particular manufacturing volume. Consider the following sample of monthly production volumes and total costs data for a manufacturing operation for the year 2018. Month (2018) Volume of Production (Units) Total Costs ($) Jan 500 6000 Feb 350 4000 Mar 450 5000 Apr 550 5400 May 600 5900 Jun 400 4000 Jul 400 4200 Aug 350 3900 Sept 400 4300 Oct 600 6000 Nov 700 6400 Dec 750 7000 1) Which of the following is NOT necessarily true about the interpretation of the value of b in the simple linear regression equation y = a + bx for this problem? 2) Which of the following statements are true about the dependent (or response) and independent (or predictor) variables for the simple linear model in…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 regression equation 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 for a manufacturing operation. KINDLY ANSWER LETTER DCost Estimation. 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 regression equation 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 for a manufacturing operation. Production Volume (units) Total Cost ($) 400 4000 450 5000 550 5400 600 5900 700 6400 750 7000 Regression equation y=1246.667 + 7.6x Variable cost per unit produced = 7.6 Compute the coefficient of determination. = 0.9587 Question 1 - What percentage of the variation in total cost can be explained by production volume?Question 2 - The company’s production schedule shows 500 units must be produced next month. Predict the total cost for this operation. Please do not…
- An important application of regression analysis is in the estimation of cost. By collecting data on volume and cost and using the least-squares method to develop an estimated regression equation relating volume and cost, one can estimate the cost associated with a particular manufacturing volume. Consider the following sample of monthly production volumes and total costs data for a manufacturing operation for the year 2018 (Please help me.. this problem is the only chance my teacher gave me to pass our math subject... thank you very much in advance) 1. Which of the following is NOT necessarily true about the interpretation of the value of b in the simple linear regression equation y = a + bx for this problem? I.The monthly total costs will increase by Rs 7.637 for every one-unit increase in the production volume. II.Since b>0, there is a direct relationship between production volume and total costs. III. Because b>1, there is a very strong positive linear relationship between…In a study of housing demand, the county assessor develops the following regression model to estimate the market value (i.e., selling price) of residential property within his jurisdiction. The assessor suspects that important variables affecting selling price (YY, measured in thousands of dollars) are the size of a house (X1X1, measured in hundreds of square feet), the total number of rooms (X2X2), age (X3X3), and whether or not the house has an attached garage (X4X4, No=0, Yes=1No=0, Yes=1). Y=α+β1X1+β2X2+β3X3+β4X4+εY=α+β1X1+β2X2+β3X3+β4X4+ε Now suppose that the estimate of the model produces following results: a=166.048a=166.048, b1=3.459b1=3.459, b2=8.015b2=8.015, b3=−0.319b3=−0.319, b4=1.186b4=1.186, sb1=1.079sb1=1.079, sb2=5.288sb2=5.288, sb3=0.789sb3=0.789, sb4=12.252sb4=12.252, R2=0.838R2=0.838, F-statistic=12.919F-statistic=12.919, and se=13.702se=13.702. Note that the sample consists of 15 randomly selected observations. According to the estimated model, holding all…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 regression equation 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 for a manufacturing operation. Production Volume (Units) Total Cost ($) 400 4000 450 5000 550 5400 600 5900 700 6400 750 7000 Use these data to develop an estimated regression Equation that could be used to predict the total cost for a given production volume. What is the variable Cost per unit produced? Compute the coefficient of determination. What percentage of the variation in total cost can be explained by production volume? The company's production schedule shows 500 untis must be produced next month. Predict the total cost for this operation. Where data on production…
- 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 regression equation 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 for a manufacturing operation. Production Volume (Units) Total Cost ($) 400 4000 450 5000 550 5400 600 5900 700 6400 750 7000 Use these data to develop an estimated regression Equation that could be used to predict the total cost for a given production volume. What…An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes and total cost data for a manufacturing operation. Production Volume (units) Total Cost ($) 400 4,300 450 5,300 550 5,700 600 6,200 700 6,700 750 7,300 a. Compute b1 and b0 (to 1 decimal). b. The company's production schedule shows 500 units must be produced next month. What is the estimated total cost for this operation (to the nearest whole number)?The Pilot Pen Company has decided to use 15 test markets to examine the sensitivity of demand for its new product to various prices, as shown in the following table. Advertising effort was identical in each market. Each market had approximately the same level of business activity and population.a. Using a linear regression model, estimate the demand function for Pilot’s new pen.b. Evaluate this model by computing the coefficient of determination and by performing a t-test of the significance of the price variable.c. What is the price elasticity of demand at a price of 50 cents? TEST MARKET PRICE CHARGED (¢) QUANTITY SOLD(THOUSANDS OF PENS) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 50 50 55 55 60 60 65 65 70 70¢ 80 80 90¢ 90 40 20.0 21.0 19.0 19.5 20.5 19.0 16.0 15.0 14.5 15.5 13.0 14.0 11.5 11.0 17.0
