The materials handling manager of a manufacturing company is trying to forecast the cost of maintenance for the company's fleet of over-the-road tractors. The manager believes that the cost of maintaining thetractors increases with their age. The following data was collected:Age(years)5.5where Y = Yearly maintenance cost in dollars and X = Age in years.5.55.55.05.05.06.06.06.5YearlyMaintenanceCost (S)1,3191,7491,7331,1951,4231,3811,5902,2221,687Age(years)5.01.51.5Y =7.07.02.02.02.0YearlyMaintenanceCost ($)1,894863882a. Use POM for Windows' least squares-linear regression module to develop a relationship to forecast the yearly maintenance cost based on the age of a tractor. (Enter your responses rounded to three decimalplaces and include a minus sign if necessary.)1,4642,0731,6781,1661,249

Given data is Age Yearly Maintenance 5.5 1319 5.5 1749 5.5 1733 5.0 1195 5.0 1423…

Answered: The materials handling manager of a…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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A researcher studied the relationship between the number of times a certain species of cricket will chirp in one minute and the temperature outside. Her data is expressed in the scatter plot and line of best fit below. What is the meaning of the y-value on the line when a = 90? 95 90 85 80 75 60 55 50 80 100 160 120 130 140 150 Chirps Per Minute The predicted temperature in degrees Fahrenheit if the cricket has chirped 56.3 times. The actual temperature in degrees Fahrenheit when the cricket has chirped 56.3 times. The predicted temperature in degrees Fahrenheit if the cricket has chirped 90 times. The actual temperature in degrees Fahrenheit when the cricket has chirped 90 times. Temperature (Degrees Fahrenheit)
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. x11.88.26.93.62.82.72.10.3y14.310.79.86.96.26.264.2x= thousands of automatic weapons y= murders per 100,000 residents This data can be modeled by the equation y=0.86x+3.9.Use this equation to answer the following; A) How many murders per 100,000 residents can be expected in a state with 5 thousand automatic weapons? Answer = Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 6.4 thousand automatic weapons? Answer = Round to 3 decimal places.
Suppose a researcher collects data on the gas mileage, measured in miles per gallon, for both city and highway driving in 35 cars. The data is plotted with city gas mileage on the horizontal axis and highway gas mileage on the vertical axis. The 1965 Triumph Herald is an outlier in the ?‑direction. What must be true about this car? A. This car is an influential observation. B. The highway gas mileage for this car is much higher or lower than other cars in the data set that have similar city gas mileage. C. The absolute value of the residual of this car is large. D. The city gas mileage for this car is much higher or lower than the rest of the cars in the data set. E. The highway gas mileage for this car is much higher or much lower than the rest of the cars in the data set.
Judge and Cable (2010) reported the results of a study demonstrating a negative relationship between weight and income for a group of women professionals. To simply the weight variable, the women are classified into five categories that measure actual weight relative to height, from 1 = thinnest to 5 = heaviest. Income figures are annual income (in thousands), rounded to the nearest $1,000. Weight (X) Income (Y) 1 125 2 78 4 49 3 63 5 35 2 84 5 38 3 51 1 93 4 44 b. Compute the Pearson correlation for these data. c. What percentage of variance for the income is predicted from the weight for the women group?
Assuming the lowest decile of men receive an average of $800/month in Social Security, while the highest decile receive $2200/month in Social Security how much does each receive (on average) during their years in retirement. Use the chart called: Predictive Years of Receiving Social Security Benefits. Also use the born in 1940 data.
Below, we see a snippet of a dataset that consists of 128 observations and 15 variables. We present two models describing the linear relationship between the BodyFat and other variables. Density BodyFat Age Weight Height Neck Chest Abdomen Hip Thigh Knee Ankle 1 1.0708 12.3 23 154.25 85.2 94.5 59.0 37.3 21.9 2 1.0853 6.1 22 173.25 83.0 98.7 58.7 37.3 3 1.0414 87.9 99.2 59.6 38.9 4 1.0751 86.4 101.2 5 1.0340 100.0 101.9 63.2 42.2 6 1.0502 94.4 107.8 66.0 42.0 23.4 24.0 67.75 36.2 93.1 72.25 38.5 93.6 25.3 22 154.00 66.25 34.0 95.8 10.4 26 184.75 72.25 37.4 101.8 28.7 24 184.25 71.25 34.4 97.3 20.9 24 210.25 74.75 39.0 104.5 60.1 37.3 22.8 24.0 25.6 Biceps Forearm Wrist 1 32.0 27.4 17.1 2 30.5 28.9 18.2 3 28.8 25.2 16.6 32.4 29.4 18.2 5 32.2 27.7 17.7 6 35.7 30.6 18.8 Analysis of Variance Table Model 1: x$BodyFat ~ x$Neck Model 2: x$BodyFat x$Neck + xSWeight + x$Height F Pr (>F) Res. Df RSS Df Sum of Sq 1 250 13348.1 2 248 9461.4 2 3886.7 50.939 < 2.2e-16 *** --- Signif. codes: 0***…
Answer this question in R. Show as much of your work as possible.
Example 5 The highlights of the Railway budget for 1983-84 are as follows. The actual gross traffic receipts for 1981-82 was Rs. 3,538.24 crores. The Budget Estimates for 1982-83 in regard to Gross traffic receipts was Rs. 4,171.8 crores and the revised Budget Estimate for 1982-83 for the above item is Rs. 4,375.79 crores respectively. Whereas the budget estimates for 1983-84 for Gross traffic receipts is Rs. 5,343.63 crores, the actual total working expenses and the net railway revenue for 1981-82 were Rs. 3,182.05 crores and Rs. 403.1 crores respectively. The Budget Estimates and Revised Budget Estimates for 1982-83 in respect of total working expenses are Rs. 3,700.90 crores and Rs. 3,892.28 crores respectively. Whereas the corresponding estimates for 1982-83 in respect of net-railway revenue are Rs. 510.91 crores and Rs. 533.4 crores respectively, the estimated budget on total working expenses and net railway revenue for 1983-84 exceed the actuals for 1981-82 by Rs. 1,338.72 crores…
In a certain country, total alcoholic beverage sales are reported throughout the year. Sales were reported as $118.5 billion at the beginning of 2004 and $136.2 billion at the beginning of 2006. (a) Let the x-axis denote time and the y-axis denote the amount of alcohol sales (in billions), Let x = 0 correspond to 2004. Fill in the blanks: The given data is represented by the points ( 118.5) and (2, ). (b) Find the linear equation determined by the two points in part (a). (c) Use the equation in part (b) to estimate the alcohol sales produced in 2005. (d) If the model remains accurate, in what year will reported alcohol sales reach $150 billion? (a) The given data is represented by the points (,118.5) and (2,). (Type integers decimals rounded to one decimal place.) (b) The linear equation determined by the two points in part (a) is y =x+. (Type integers or decimals rounded to one decimal place.) (c) The alcohol sales produced in 2005 are approximately $ billion. (Type an integer or…
Two different forecasting techniques (F1 and F2) were used to forecast demand for cases of bottled water. Actual demand and the two sets of forecasts are as follows. The question asks whether the F1 or F2 forecast is more accurate, and what is the Mean Absolute Percentage Error. Show your work and answer the question. Be as succinct as possible please, you do not need to show me calculations for the wrong answers. Period Demand F1 F2 1 2 3 4 5 6 8 68 75 70 74 69 72 80 78 66 66 68 68 72 70 71 72 72 74 70 76 71 78 74 80 e1 3.0 2.0 7.0 7.0 -2.0 -3.0 2.0 Forecast F1 9.0 4.0 MAD MAPE MSE 2.0 2.9 4.0 9.3 49.0 2.0 2.9 4.0 3.0 4.1 9.0 3.0 4.3 9.0 2.0 2.8 4.0 9.0 11.3 81.0 4.0 5.1 16.0 e2 2.0 Forecast F2 MAD MAPE 2.0 2.9 9.3 7.0 7.0 0.0 0.0 2.0 2.0 0.0 2.7 5.0 7.2 -5.0 -4.0 4.0 5.6 2.0 2.0 2.5 -2.0 2.0 2.6 MSE 4.0 49.0 0.0 4.0 25.0 16.0 4.0 4.0
Suppose an oceanographer monitors the daily salinity of a particular ocean in relation to the temperature of the water. The oceanographer plots the data with temperature, in degrees Celsius (°C), along the horizontal axis and salinity, in parts per thousand (ppt), along the vertical axis. Select the true statement about the data point identified by the arrow. An ocean temperature of 21 °C causes the salinity to be 29 ppt. The predicted salinity is 29 ppt when the ocean temperature for the day is 21 °C. An ocean temperature of 29 °C corresponds to a salinity level of 21 ppt. The observed salinity is 29 ppt when the ocean temperature for the day is 21 °C. There is no relationship between the temperature of the ocean on a given day and salinity.
The amount of time adults spend watching television is closely monitored by firms because this helps to determine advertising pricing for commercials. Complete parts (a) through (d). (a) Do you think the variable "weekly time spent watching television" would be normally distributed? If not, what shape would you expect the variable to have? A. The variable "weekly time spent watching television" is likely skewed left, not normally distributed. B. The variable "weekly time spent watching television" is likely normally distributed. C. The variable "weekly time spent watching television" is likely uniform, not normally distributed. D. The variable "weekly time spent watching television" is likely symmetric, but not normally distributed. E. The variable "weekly time spent watching television" is likely skewed right, not normally distributed.

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