Let's assume that there is a manufacturing company which produces a type of machine. Every machineneeds some time to be manufactured. We have the following variables in the dataset,• Y = RunTime, the time in minutes for a production run to be completed• X = RunSize, the number of items being produced in each run. We have 20 randomly selected orders as supervised by one of three managersWe are interested in predicting the run time for an order. The following is an R output after running alinear model:Call: 1m (formula = RunTime ~ RunSize, data = productionResiduals:Min1Q Median3QMax-28.597 -11.079 3.329 8.302 29.627Coefficients: Estimate Std. Error t value Pr(>|t|)(Intercept) 149.74770 8.32815 17.98 6.00e-13 ***RunSize0.259240.037146.98 1.61e-06 ***Residual standard error: 16.25 on 18 degrees of freedomMultiple R-squared: 0.7302, Adjusted R-squared: 0.7152F-statistic: 48.72 on 1 and 18 DF, p-value: 1.615e-06(a)(b)Calculate the 99% confidence interval for the regression coefficient corresponding to theRunSize variable (i.e., B₁) based on the information that you have.Interpret the 99% confidence interval from (a) (c) |Let's assume we have a new order size (i.e., RunSize) of 150. Calculate the predicted valueof the RunTime.(d) L(e) |Calculate the 99% prediction interval for the predicted RunTime from (c)Interpret the prediction interval from (d).

Y Run Time (Dependent variable) the time in minutes for a production run to be completed X Run…

Answered: Let's assume that there is a…

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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I have collected real data on the sale of a microwavable cup of soup across 20 different cities for the same time period (a month). The variables in the dataset are: Quantity sold in the city for that month: Measured in thousands of units Price: measured in dollars Average Income in the city: Measured in thousands of dollars Ads: Average number of ads run in stores for that city during that month. Price of a substitute product: measured in dollars Population of the city: measured in thousands of people The dataset is on Canvas and, using Excel or any other statistical software, please answer the following questions: 1. Describe the patterns in quantity sold and own and rival prices during this time period using basic descriptive statistics. Graphs are welcome as well. 2. Take the logs of the variables, and estimate the demand function. a. Interpret the R-square. b. Interpret the coefficients for logP and logPsub c. Interpret the p-values associated with each independent…
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Fiske Corporation manufactures a popular regional brand of kitchen utensils. The design and variety has been fairly constant over the last three years. The managers at Fiske are planning for some changes in the product line next year, but first they want to understand better the relation between activity and factory costs as experienced with the current products. Discussions with the plant supervisor suggest that overhead seems to vary with labor-hours, machine-hours, or both. The following data were collected from last three year's operations: Quarter Machine-Hours 18,850 4 5 6 7 8 9 10 11 12 18,590 17,480 19,240 21,280 19,630 19,240 18,850 18,460 20,670 17,550 18,460 Labor-Hours 15,605 15,484 16,727 15,990 17,508 17,376 15,297 14,373 16,001 17,002 14,285 17,651 Factory costs $ 3,395,671 3,425,836 3,617,844 3,573,940 3,812,984 3,778,012 3,532,426 3,369,802 3,513, 187 3,731,434 3,325,615 3,724,486 Required: Prepare a scatter graph based on the factory cost and labor-hour data. Note: 1.…
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The table lists the average gestation period (in days) and longevity (in years) for the following mammals, as reported in The World Almanac and Book of Facts 2006. Mammal Gestation, y(days) Longevity, x(years) Mammal Gestation, y(days) Longevity, x(years) Baboon 187 20 Camel 406 12 Bear, black 219 18 Cat 63 12 Bear, grizzly 225 25 Chimpanzee 230 20 Bear, polar 240 20 Chipmunk 31 6 Beaver 105 5 Cow 284 15 Buffalo 285 15 Deer 201 8 Dog 61 12 Monkey 164 15 Donkey 365 12 Moose 240 12 Elephant 645 40 Mouse 21 3 Elk 250 15 Opossum 13 1 Fox 52 7 Pig 112 10 Giraffe 457 10 Puma 90 12 Goat 151 8 Rabbit 31 5 Gorilla 258 20 Rhinoceros 450 15 Guinea pig 48 4 Sea lion 350 12 Hippopotamus 238 41 Sheep 154 12 Horse 330 20 Squirrel 44 10 Kangaroo…

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