The below data on the production volume x and total cost y (in dollars) for a particular manufacturing operation were used to develop the estimated regression equation ý = 1,062.67 + 7.92x.Production VolumeTotal Cost(units)($)4003,9004505,0005505,5006005,8007006,4007507,100(a) The company's production schedule shows that 650 units must be produced next month. What is the point estimate of the total cost (in dollars) for next month? (Round your answer to the nearest cent.)$(b) Develop a 99% prediction interval for the total cost (in dollars) for next month. (Round your answers to the nearest cent.)to $(c) If an accounting cost report at the end of next month shows that the actual production cost during the month was $7,400, should managers be concerned about incurring such a high total cost for the month? Discuss.Since $7,400 is --Select--- v the prediction interval, managers should ---Select--- v concerned about incurring such a high total cost for one month.

(a) The estimated cost for the next month can simply be calculated by substituting x=650 in the…

Answered: The below data on the production volume…

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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A 1 ROAA (%) Efficiency Ratio (%) 2 1.04 39.93 3 57.75 4 81.4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 0.68 7.27 1.08 0.72 0.92 0.79 1.04 1.76 1.07 1.37 0.93 0.66 1.72 1.5 0.59 2.12 1.11 1.45 1.06 B A 53.49 71.08 65.41 68.07 68.14 68.1 64.82 48.58 63.1 59.16 49.93 54.7 81.6 75.21 69.82 49.47 57.09 с Total Risk-Based Capital (%) 17.04 13.88 27.77 18.31 14.66 14.04 13.38 16.8 16.69 13.86 12 18.65 19.76 17.69 26.6 15.08 14.55 17.5 16.03 14.62 D E F G H |
The following table shows the approximate amount of trash produced in an industrialized country from 1980 to 2000. Let x represent the year after 1980 (1980 is year 0) and y represent the amount of trash (millions of tons). Year Million Tons 1980 149 1990 205 2000 224 (a) Draw the graph for this data. (b) Find the equation of the regression line for the data. (Round your answers to one decimal place.)y = x + (c) Use the equation to predict the amount of trash y that will be produced in 2010 and 2015. (Round your answers to one decimal place.) in 2010 million tons in 2015 million tons
The Toyota Camry is one of the best-selling cars in North America. The cost of a previously owned Camry depends upon many factors, including the model year, mileage, and condition. To investigate the relationship between the car's mileage and the sales price for a 2007 model year Camry, the following data show the mileage and sale price for 19 sales (PriceHub website). Click on the datafile logo to reference the data. DATA file 1. 18 Price ($1000s) 16 14 12 10 18 6 If your answer is zero, enter "0". a. Select a scatter diagram with the car mileage on the horizontal axis and the price on the vertical axis. 20 40 6,0 8,0 100 Miles (1000s) 120 223 +♡ ♡ Miles(1000s) 29 36 47 63 77 73 87 92 101 110 28 59 68 68 91 42 65 110 Price ($1000s) 16.2 16.0 13.8 11.5 12.5 12.9 11.2 13.0 11.8 10.8 8.3 12.5 11.1 15.0 12.2 13.0 15.6 12.7 8.3
The flow rate in a device used for air quality measurement depends on the pressure drop x (inches of water) across the device's filter. Suppose that for x values between 5 and 20, these two variables are related according to the simple linear regression model with true regression line y = -0.11 + 0.097x. (a.1) What is the true average flow rate for a pressure drop of 10 in.?(a.2) A drop of 15 in.?(b) What is the true average change in flow rate associated with a 1 inch increase in pressure drop?(c) What is the average change in flow rate when pressure drop decreases by 5 in.?
A statistical program is recommended. The owner of Showtime Movie Theaters, Inc., would like to predict weekly gross revenue as a function of advertising expenditures. Historical data for a sample of eight weeks follow. Weekly Television Gross Newspaper Advertising Advertising ($1,000s) ($1,000s) Revenue ($1,000s) 96 5.0 1.5 90 2.0 2.0 95 4.0 1.5 92 2.5 2.5 95 3.0 3.3 94 3.5 2.3 94 2.5 4.2 94 3.0 2.5 1 (a) Develop an estimated regression equation with the amount of television advertising as the independent variable. (Round your numerical values to two decimal places. Let x₁ represent the amount of television advertising in $1,000s and y represent the weekly gross revenue in $1,000s.) y = 88.64 + 1.60x1 X (b) Develop an estimated regression equation with both television advertising and newspaper advertising as the independent variables. (Round your numerical values to two decimal places. Let x₁ represent the amount of television advertising in $1,000s, x₂ represent the amount of…
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The managing director of a consulting group has the accompanying monthly data on total overhead costs and professional labor hours to bill to clients. Complete parts a through c Click the icon to view the monthly data. a. Develop a simple linear regression model between billable hours and overhead costs. Overhead Costs = 247733.3 +(43.2000) x Billable Hours (Round the constant to one decimal place as needed. Round the coefficient to four decimal places as needed. Do not include the $ symbol in your answers.) b. Interpret the coefficients of your regression model. Specifically, what does the fixed component of the model mean to the consulting firm? Interpret the fixed term, bo. if appropriate. Choose the correct answer below. OA. The value of by is the predicted overhead costs for 0 billable hours. OB. For each increase of 1 unit in overhead costs, the predicted billable hours are estimated to increase by bo OC. It is not appropriate to interpret by. because its value is the predicted…
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Q1: [Regression and Correlation] The index of biotic integrity (IBI) is a measure of water quality in streams. As a data analyst you must monitor, track, and predict changes in water quality. You want to create a simple linear regression model that will allow you to predict changes in IBI in forested area. The following table conveys sample data from a coastal forest region and gives the data for IBI and forested area in square kilometers. Let forest area be the predictor variable (x) and IBI be the response variable (y). IBI X 47 72 21 72234 19 58 49 Forest Area Y 38 59 27 24 63 49 45 Required a. Q2: [Naïve Bayes] a. Write the pseudo-code of the following Naïve Bayes algorithm b. Consider the given dataset that classifies animals into two distinct classes. The classes are labeled as 'cat' and 'dog'. Use Naive Bayes classifier to figure out the class (cat/dog) of an instance if it has the following values of attributed Plot Scatter graph b. Determine the regression equation c. Compute…
You may need to use the appropriate appendix table or technology to answer this question. The below data on the production volume x and total cost y (in dollars) for a particular manufacturing operation were used to develop the estimated regression equation ŷ = 1,213.33 + 7.6x. Production Volume Total Cost (units) ($) 400 450 550 600 700 750 4,000 X 4,900 5,300 6,000 6,400 6,900 (a) The company's production schedule shows that 650 units must be produced next month. What is the point estimate of the total cost (in dollars) for next month? (Round your answer to the nearest cent.) $1 (b) Develop a 99% prediction interval for the total cost (in dollars) for next month. (Round your answers to the nearest cent.) $1 X to $1 X (c) If an accounting cost report at the end of next month shows that the actual production cost during the month was $7,000, should managers be concerned about incurring such a high total cost for the month? Discuss. Since $7,000 is outside of ⒸX the prediction interval,…
The police chief believes that maintenance costs on high-mileage police vehicles are much higher than those costs for low-mileage vehicles. If high-mileage vehicles are costing too much, it may be more economical to purchase more vehicles. An analyst in the department regresses yearly maintenance costs (Y) for a sample of 200 police vehicles on each vehicle’s total mileage for the year (X). The regression equation finds: Y = $50 + .030X with a r2 of .90 If a vehicle’s mileage for the year is 50,000, what is its predicted maintenance costs? What does an r2 of .90 tell us? Is this a strong or weak correlation? How can you tell?
B b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables? The scatter diagram indicates a positive linear relationship between a = average number of passing yar and y = the percentage of games won by the team. c. Develop the estimated regression equation that could be used to predict the percentage of games won given the avera passing yards per attempt. Enter negative value as negative number. WinPct =| |)(Yds/Att) (to 4 decimals) d. Provide an interpretation for the slope of the estimated regression equation (to 1 decimal). The slope of the estimated regression line is approximately So, for every increase : of one yar number of passes per attempt, the percentage of games won by the team increases by %. e. For the 2011 season, the average number of passing yards per attempt for the Kansas City Chiefs was was 5.5. Use th regression equation developed in part (c) to predict the percentage of games won by the Kansas City Chiefs.…

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