10:32An engineer wants to determine how the weight of a gas-powered car, x, affects gas mileage, y. The accompanyingdata represent the weights of various domestic cars and their miles per gallon in the city for the most recent modelyear. Complete parts (a) through (d) below.Click here to view the weight and gas mileage data.(a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as theresponse variable.1ŷ=x+(Round the x coefficient to five decimal places as needed. Round the constant to two decimal places as needed.)2.4G 15%(b) Interpret the slope and y-intercept, if appropriate. Choose the correct answer below and fill in any answer boxes inyour choice.(Use the answer from part a to find this answer.)OA. A weightless car will get miles per gallon, on average. It is not appropriate to interpret the slope.mile(s) per gallon,OB. For every pound added to the weight of the car, gas mileage in the city will decrease bymiles per gallon, on average.on average. A weightless car will getOC. For every pound added to the weight of the car, gas mileage in the city will decrease byon average. It is not appropriate to interpret the y-intercept.OD. It is not appropriate to interpret the slope or the y-intercept.BelowAbove(c) A certain gas-powered car weighs 3500 pounds and gets 18 miles per gallon. Is the miles per gallon of this carabove average or below average for cars of this weight?(d) Would it be reasonable to use the least-squares regression line to predict the miles per gallon of a hybrid gas andelectric car? Why or why not?|||mile(s) per gallon,OA. Yes, because the hybrid is partially powered by gas.B. No, because the absolute value of the correlation coefficient is less than the critical value for a sample sizeof n = 11.=O C. No, because the hybrid is a different type of car.O D. Yes, because the absolute value of the correlation coefficient is greater than the critical value for a samplesize of n = 11.O Weight(pounds), x37643787280135823369304337782572350138313402Miles perGallon, y1617241820231824201718

Answered: An engineer wants to determine how the…

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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At the stadium, there are three lines for arriving customers, each staffed by a single worker. The arrival rate for customers is 140 per minute and each customer takes (on average) 1.1 seconds for a worker to process. The coefficient of variation for arrival time is 1.4 and the coefficient of variation for service time is 1. (Round your answerto three decimal places.) How much time (in seconds will an average customer spend in queue? seconds
Is this considered a weak, negative relationship between Carbon Monoxide and Temperature?
(SUB-PART C ONLY PLEASE) Each row represents an experimental “run” (in this case, averaged sample of mango wine). Column A shows the run number; Column B shows the percentage of ethanol; Column C shows the amount of glycerol (in g/L); Column D shows the amount of acid (in g/L); Column E shows the temperature of the run (in °C); and Column F shows the pH of the run. Y represents Ethanol of mango wine. 1. Create a scatterplot of the ethanol data for all 20 runs (CREATED) a. Draw a graphical representation of the model that you chose to use. (CREATED WITHIN SCATTERPLOT) b. Comparing the model to your data, evaluate its fit in one or two sentences. (LINEAR MODEL; The conditions to say that the model is a good fit are as given below: To say that the model is the good fit, the coefficient of determination should be high. Atleast one the predictor variables should be statistically significant in predicting the response variable. ) c. Replace the generic Yi = β0 + ε with the information you…
Each row represents an experimental “run” (in this case, averaged sample of mango wine). Column A shows the run number; Column B shows the percentage of ethanol; Column C shows the amount of glycerol (in g/L); Column D shows the amount of acid (in g/L); Column E shows the temperature of the run (in °C); and Column F shows the pH of the run. Y represents Ethanol of mango wine. 1. Create a scatterplot of the ethanol data for all 20 runs a. Draw a graphical representation of the model that you chose to use. b. Comparing the model to your data, evaluate its fit in one or two sentences. (Not sure what this question is getting at. I've provided all the information given) c. Replace the generic Yi = β0 + ε with the information you have here. Please help. I have no idea what this even means or where to start. HERE is the attached dataset to start with; a b c d e f Run Ethanol Glycerol Acidity Temp pH 1 4.8 3.5 0.84 24 3.8 2 9.6…
The cost of fuel is the largest component of cost of ownership for most vehicles. Fuel cost is (almost) inversely proportional to gas mileage; higher gas mileage means lower fuel cost and vice-versa. If you keep track of the number of miles driven on each tank of gas as well as how much gas is purchased, it is easy to calculate gas mileage; many cell phone apps exist to track this. The data in the following table is the gas mileage for Mr. Hebert's 2015 Jeep Wrangler Unlimited. 12.85 14.98 15.36 17.09 18.86 13.28 15.11 15.62 17.50 19.07 13.48 15.12 15.65 17.66 20.91 14.65 15.13 16.41 18.17 21.17 14.71 15.14 16.80 18.27 22.11 a. Find the average fuel economy. x =enter your response here (Round your answer to 3 decimal places.)
The cost of fuel is the largest component of cost of ownership for most vehicles. Fuel cost is (almost) inversely proportional to gas mileage; higher gas mileage means lower fuel cost and vice-versa. If you keep track of the number of miles driven on each tank of gas as well as how much gas is purchased, it is easy to calculate gas mileage; many cell phone apps exist to track this. The data in the following table is the gas mileage for Mr. Hebert's 2015 Jeep Wrangler Unlimited. 12.85 14.98 15.36 17.09 18.86 13.28 15.11 15.62 17.50 19.07 13.48 15.12 15.65 17.66 20.91 14.65 15.13 16.41 18.17 21.17 14.71 15.14 16.80 18.27 22.11 c. Find the five number summary. enter your response here, enter your response here, enter your response here, enter your response here, enter your response here
Complete the table.
A researcher is interested in understanding the relationship between ife stress (Variable X) and quality of life (Varlable Y). Using the whiteboard, plot the data below Into a scatterplot and comment on the type of relationship you see between life stress and quality of life. BE SURE AND SAVE YOUR PICTURE. 3. 3. Aa stroke
K Disk drives have been getting larger. Their capacity is now often given in terabytes (TB) where 1 TB = 1000 gigabytes, or about a trillion bytes. A survey of prices for external disk drives found the data shown to the right. For this data, we want to predict Price from Capacity. Complete parts a through i below. Click the icon to view the disk drive data and summary statistics. Disk Drive Data and Summary Statistics Capacity (in TB) 0.5 1.0 2.0 3.0 4.0 6.0 8.0 12.0 32.0 x = 7.611 SD(x) = 9.85 r = 0.987 --- Print Price (in $) 58.79 75.79 114.00 105.95 146.45 425.49 594.00 1074.00 4464.49 y = 784.329 SD(y) = 1420.27 Done X A. It indicates the price for a hard drive with no capacity. It is meaningless and should not be interpreted. B. It indicates the additional capacity in TB for each additional dollar of price. It is meaningful in that it could be interpreted as the cost of the parts common to all drives.

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