An important application of regression in manufacturing is the estimation of cost of production. Based on DATA from Ajax Widgets relating cost (Y) to volume (X), what is the cost of producing 600 widgets? Production Volume (units) Total Cost ($) 400 3430 450 4080 550 4878 600 4884 700 5913 750 6402 425 4273 475 4362 575 5089 625 5446 725 6017 775 6591
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An important application of regression in manufacturing is the estimation of cost of production. Based on DATA from Ajax Widgets relating cost (Y) to volume (X), what is the cost of producing 600 widgets?
| Production Volume (units) | Total Cost ($) |
| 400 | 3430 |
| 450 | 4080 |
| 550 | 4878 |
| 600 | 4884 |
| 700 | 5913 |
| 750 | 6402 |
| 425 | 4273 |
| 475 | 4362 |
| 575 | 5089 |
| 625 | 5446 |
| 725 | 6017 |
| 775 | 6591 |
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- What is regression analysis? Describe the process of performing regression analysis on a graphing utility.A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a linear function of batch size (the number of boards produced in one lot or batch), production plant (Kingsland, and Yorktown), and production shift (day, and evening). In this model, "shift" is O a dependent variable an independent variable a quantitative variable a constant a response variableFind the required linear model using least-squares regression. The table below gives the total sales (in billions of dollars) for the aerospace industry. Year 2006 2007 2008 2009 2010 2011 Total Sales 179.7 182.0 183.6 184.8 185.8 186.6 (a) Find a linear model for the data with x = 6 corresponding to the year 2006. (b) Assuming the trend continues, estimate the total sales for the year 2016. (a) The linear model for the data is y =x+ (Round to two decimal places as needed.) Print Help me solve this O Type here to search
- 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. In the Microsoft Excel Online file below you will find a sample of production volumes and total cost data for a manufacturing operation. Conduct a regression analysis to explore the relationship between total cost and production volume and then answer the questions that follow. Compute b1 and b0 (to 1 decimal). b1 b0 Complete the estimated regression equation (to 1 decimal). = + x According to this model, what is the change in cost (in dollars) for every unit produced (to 1 decimal)? Compute the coefficient of determination (to 3 decimals). Note: report r2 between 0 and 1. r2 = What percentage of the variation in total cost can be explained by the…In linear regression analysis, the coefficient for the x-variable when the y-variable is regressed on the x-variable can be thought of as: Note: more than one answer may be correct Group of answer choices How much the value of the predicted y-variable will change when the x-variable changes by one unit. In the simple (two variable) linear regression model, the coefficient can be thought as the slope coefficient that measures the responsiveness of y to changes in x. The estimated coefficient will change if the sample containing x and y changes. The sample coefficient is an estimate of the population coefficient Before interpreting the coefficient for the x-variable, we should test whether the coefficient is statistically significant.The owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue (1) as a function of television advertising (Z1) and newspaper advertising (). Weekly Gross Television Newspaper Revenue Advertising Advertising ($1000s) ($1000s) ($1000s) 97 6.0 1.5 90 2.0 3.0 96 5.0 1.5 92 2.5 2.5 95 4.0 4.3 94 3.5 3.3 94 2.5 5.2 95 4.0 3.5 The estimated regression equation was y = 86.0 + 1.87z1 +0.71r2 The computer solution provided SST- 34.9 and SSR 32.700 a. Compute and interpret R and R: (to 3 decimals). R R b. When television advertising was the only independent variable, R = 0.653 and Ra = 0.595, Do you prefer the multiple regression results? Explain. Select your answer-
- The owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x1) and newspaper advertising (*2). Weekly Gross Television Newspaper Revenue Advertising Advertising ($1000s) ($1000s) ($1000s) 96 6.0 2.5 90 2.0 3.0 96 5.0 2.5 92 3.5 2.5 96 4.0 3.3 95 3.5 3.3 94 2.5 4.2 95 4.0 3.5 The estimated regression equation was ŷ = 79.4 + 1.94x1 + 2.40x2. The computer solution provided SST = 33.5 and SSR = 29.283. a. Compute and interpret R2 and R. (to 3 decimals). R2 = R = b. When television advertising was the only independent variable, R = 0.653 and R = 0.595. Do you prefer the multiple regression results? Explain. No, because less variability is explained when both independent variables are usedOpening weekend box office revenue is an important source of income to the movie industry and a crucial preliminary indicator of long-run profitability of a motion picture. Here are a scatter plot and the residual plot for predicting the World Gross Revenue from the Opening-Weekend Revenues for 136 Hollywood movies in 2011 using simple linear regression. 50 100 150 50 100 150 Opening Weekend Revenue (millions of dollars) Opening Weekend Revenue (millions of dollars) From the two plots above, which assumption of a simple linear model is most clearly violated? (i) linearity (ii) constant variability (iii) normal residuals (iv) independence оо 007 0008 00-- Residual (millions of dollars) 1200 00 008 (millions of dollars) World Gross RevenueA 10-year study conducted by the American Heart Association provided data on how age, blood pressure, and smoking related to the risk of strokes. The data file “Stroke.xslx” includes a portion of the data from the study. The variable “Risk of Stroke” is measured as the percentage of risk (proportion times 100) that a person will have a stroke over the next 10-year period. Regression Analysis As Image: 1) Based on the simple regression analysis output, write the estimated regression equation. 2) What is the correlation coefficient between Risk of Stroke and Age? How do you find i
- A microcomputer manufacturer has developed a regression model relating his sales (y=$10,000s) with three independent variables. The three independent variables are price per unit(Price in $100s), advertising( ADV in $1000s) and the number of product lines (Lines). Part of the regression results is shown below. Coefficient Standard Error Intercept 1.0211 22.8752 Price(X1) -0.1524 0.1411 ADV (X2) 0.8849 0.2886 Lines(X3) -0.1463 1.5340 Source d.f. S.S. Regression 3 2708.61 Error 14 2840.51 Total 17 5549.12 What has been the sample size (n) for this analysis? Use the above results to find the estimated multiple…To predict the market share of one of their products, a manufacturer of consumer electronics products hired a market research company to conduct a study that relates market share in a particular geographic region (in %) to the average annual household income and the number of retail outlets per 100,000 residents. The results of a multiple regression model to predict market share from Household income (in thousands of dollars) and number of outlets per 100,000 residents are given below. a) How much of the variation in market share can this model predict? Is this statistically significant? b) Someone claims that each additional outlet will increase the market share by more than 1.5%, regardless of what the household income is. Perform the appropriate hypothesis test to check this claim with a 5% significance level. c) What increase in market share would your model predict for every two additional retail outlets in a region where the annual household income is $75,000? Find a 95%…Illustrate the importance of using regression models.
