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 estimatedregression 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 totalcost data for a manufacturing operation.Production Volume (units)400450550600700750a. Use these data to develop an estimated regression equation that could be used to predict the total cost for a given production volume. Do not round intermediate calculations.Compute by and be (to 1 decimal).boComplete the estimated regression equation (to 1 decimal). Do not round intermediate calculationsTotal Cost (5)4,0005,0005,4005,9006,4007,000b. What is the variable cost per unit produced (to 2 decimal)? Do not round intermediate calculationsc. Compute the coefficient of determination (to 3 decimals). Do not round intermediate calculations. Note: report between 0 and 1.PWhat percentage of the variation in total cost can be explained by the production volume (to 1 decimal)? Do not round intermediate calculationsd. The company's production schedule shows 500 units must be produced next month. Predict the total cost for this operation (to the nearest whole number). Do not round intermediate calculations

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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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Income (in 1960 dollars/person) for European countries and the percent of the labor force (in %) that works in agriculture in 1960 are in the table below ('OECD economic development,' 2013). X, percent of labor in agriculture (in %) Y, income (in 1960 dollars/person) 15 1242 56 324 20 977 42 290 11 1361 27 504 6 1005 79 177 23 681 11 810 18 1049 14 1644 20 1013 15 1035 25 839
The table below show data that has been collected from different fields from various farms in a certain valley. The table contains the grams of Raspberries tested and the amount of their Vitamin C content in mg. Find a linear model that express Vitamin C content as a function of the weight of the Raspberries. grams Vitamin Ccontent in mg 75 20.3 90 28.1 105 34.6 120 40.6 135 48.2 150 55.6 165 60 A) Find the regression equation: y=y= x+x+ Round your answers to 3 decimal places B) Answer the following questions using your un-rounded regression equation. If we test 195 grams of raspberries what is the expected Vitamin C content? mgmg (round to the nearest tenth)
Situation: The Ipod Touch has been out for two years now and a lot of data has been collected.Relevant Relationship:There is a functional relationship between Price of an IPod Touch,p and Weekly Demand,s.Below is a table of data that have been collected Price,p ,($) Weekly Demand,s ,(1,000s) 150 209 170 205 190 200 210 192 230 177 250 175 A.. Find the linear model that best fits this data using regression and enter the model below(for entry round the linear parameter value to nearest 0.01 and constant parameter to nearest 1)s=T(p)= C. What does the model predict will be the weekly demand if the price of an ipod touch is $172 ? (nearest 100) can you answer these two questions
An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes O and total cost data for a manufacturing operation. O Production Volume (units) Total Cost ($) 400 4100 450 4600 500 5600 600 6400 700 7400 750 8400 N The data on the production volume and total cost y for particular manufacturing operation were used to develop the estimated regression equation ŷ = -524.58+11.66z. a. The company's production schedule shows that 550 units must be produced next month. Predict the total cost for next month. ŷ* = (to 2 decimals) b. Develop a 98% prediction interval for the total cost for next month. X (to 2 decimals) 8 t-value (to 3 decimals) 8pred (to 2 decimals) Prediction Interval for…
In agricultural economics, a “supply response function” describes how supply of a commodity responds to changes in the price of that commodity. (production is the dependent variable,Independent variable: Price) Dataset: Year Seeded Area (hectares) Harvested Area (hectares) Average Yield (kg per ha) Production (tonnes) Price per Tonne ($/tonne) 1966 1,317,000 1,317,000 1,630 2,150,000 65 1967 1,424,000 1,424,000 1,720 2,449,000 60 1968 1,376,000 1,376,000 1,800 2,477,000 48 1969 1,012,000 1,012,000 1,720 1,742,000 46 1970 567,000 567,000 1,465 830,000 52 1971 1,019,000 1,019,000 1,975 2,014,000 50 1972 1,052,000 1,052,000 1,785 1,878,000 68 1973 1,214,000 1,214,000 1,725 2,095,000 158 1974 1,133,000 1,133,000 1,415 1,605,000 147 1975 1,255,000 1,255,000 1,690 2,123,000 130 1976 1,538,000 1,538,000 1,820 2,803,000 103…
An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes and total cost data for a manufacturing operation. Production Volume (Units) Total Cost ($) 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. Total Cost ($) 3900 4700 5300 5700 6400 7100 The data on the production volume and total cost y for particular manufacturing operation were used to develop the estimated regression equation =-490.00 + 10.60x, a. The company's production schedule shows that 450 units must be produced next month. Predict the total cost for next month. ŷ* = * (to 2 decimals) b. Develop a 99% prediction interval for the total cost for next month. (to 2 decimals) 8 t- value decimals) (to 3 * (to 2 Spred decimals) Prediction Interval for an individual Value next month Ⓡ Production Volume…
The table contains price-supply data and price-demand data for corn. Find a linear regression model for the price-supply data where x is supply (in billions of bushels) and y is price (in dollars). Do the same for the price-demand data Find the equilibrium price for corn. Price Supply ($/bu) (billion bu) 2.14 2.24 2.38 2.43 2.45 2.54 6.29 7.33 7.69 7.83 8.12 8.23 Price ($/bu) 2.02 2.14 2.24 2.35 2.35 2.42 Demand (billion bu) 9.76 9.47 8.48 8.18 7.72 6.93 XX Find a linear regression model for the price-supply data where x is supply (in billions of bushels) and y is price (in dollars). y=0 (Type an equation using x as the variable. Round to two decimal places as needed.)
97000 96000 95000 94000 93000 92000 91000 90000 89000 1000 Revenue vs TV Advertise 2000 3000 4000 5000 6000 97000 96000 95000 94000 93000 92000 91000 90000 89000 Revenue vs Print Advertise 1000 1500 2000 2500 3000 3500 4000 4500 Given above are the plots between weekly gross revenues and TV advertising and between weekly gross revenues and TV advertising for Showtime Movie Theaters. Which advertising (TV or Print) has a stronger relationship with the weekly gross revenues? O A. Print Advertising has stronger relationship with the weekly gross revenue. B. We cannot tell without calculating the related correlation coefficients. O C. TV Advertising has stronger relationship with the weekly gross revenue. O D. The strength of the relationships is the same for both advertising.

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