The management at a plastics factory has found that the maximum number of units a worker can produce in a day is 45. The learning curve forthe number N of units produced per day after a new employee has worked t days is modeled by N = 45(1 - ekt). After 20 days on the job, a newemployee produces 16 units.(a) Find the learning curve for this employee (first, find the value of k). (Round your value of k to three decimal places.)(b) How many days should pass before this employee is producing 25 units per day? (Round your answer to the nearest whole number.)daysNeed Help?Read ItWatch ItTalk to a Tutor

Answered: The management at a plastics factory…

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter4: Linear Functions

Section4.3: Fitting Linear Models To Data

Problem 35SE: For the following exercises, consider this scenario: The profit of a company decreased steadily over...

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For the following exercises, consider this scenario: The profit of a company decreased steadily over a ten-year spam.The following ordered pairs shows dollars and the number of units sold in hundreds and the profit in thousands ofover the ten-year span, (number of units sold, profit) for specific recorded years: (46,600),(48,550),(50,505),(52,540),(54,495). 35. Find to the nearest tenth and interpret thex-intercept.
For the following exercises, consider this scenario: The profit of a company decreased steadily over a ten-year spam.The following ordered pairs shows dollars and the number of units sold in hundreds and the profit in thousands of over the ten-year span, (number of units sold, profit) for specific recorded years: (46,600),(48,550),(50,505),(52,540),(54,495). Find to the nearest tenth and interpret they-intercept.
The management at a plastics factory has found that the maximum number of units a worker can produce in a day is 30. The learning curve for the number of units produced per day after a new employee has worked t days is modeled by N = 30(1 - e ^ (kt)) After 20 days on the job, a new employee produces 16 units.
The management at a plastics factory has found that the maximum number of units a worker can produce in a day is 30. The learning curve for the number N of units produced per day after a new employee had workers t days is modeled by N=30( 1-e^kt). After 20 days on the job, a new employee produces 19 units. How many days does the model predict will pass before this employee is producing 25 units per day?
The management at a plastics factory has found that the maximum of units a worker can produce in a day is 30. The learning curve for the nuruber N of units produced per day after a new employee has worked t days is modeled by N = 30(1 - e ^ (kt)) . After 20 days on the job, a niew employee produces 19 unites. How many days does the model predict will pass before this employee producing 25 units per day?
The management at a plastics factory has found that the maximum number of units a worker can produce in a day is 50. The learning curve for the number N of units produced per day after a new employee has worked t days is modeled by N = 50(1 − ekt). After 20 days on the job, a new employee produces 16 units.
The management factory has found that the maximum number of units a worker can produce in a day is 40. The learning curve for the number of units N produced per day after a new employee has worked t days is given by N= 40(1-e^kt) After 20 days of the job, a particular worker produced 25 units in 1 day. (a) Find the learning curve for this worker (b) How many days should pass for the worker o produce 35 units per day?
The management at a plastics factory has found that the maximum number of units a worker can produce in a day is 30. The learning curve for the number N of units produced per day after a new employee has worked t days is modeled by ? = 30(1−e^kt). After 20 days on the job, a newemployee produces 19 unites. How many days does the model predict will pass before this employee is producing 25 units per day?
Infants, even newborns, prefer to look at attractive faces compared to less attractive faces (Slater, et al., 1998). In the study, infants from 1 to 6 days old were shown two photographs of women’s faces. Previously, a group of adults had rated one of the faces as significantly more attractive than the other. The babies were positioned in front of a screen on which the photographs were presented. The pair of faces remained on the screen until the baby accumulated a total of 20 seconds of looking at one or the other. The number of seconds looking at the attractive face was recorded for each infant. Suppose that the study used a sample of n = 9 infants and the data produced an average of M = 13 for the attractive face with an estimated standard error sM= 1 (SS = 72). If there were no preference, the 20 seconds should be divided equally between the two photographs. Note that all the available information comes from the sample. Specifically, we do not know the population mean or the…
Infants, even newborns, prefer to look at attractive faces compared to less attractive faces (Slater, et al., 1998). In the study, infants from 1 to 6 days old were shown two photographs of women’s faces. Previously, a group of adults had rated one of the faces as significantly more attractive than the other. The babies were positioned in front of a screen on which the photographs were presented. The pair of faces remained on the screen until the baby accumulated a total of 20 seconds of looking at one or the other. The number of seconds looking at the attractive face was recorded for each infant. Suppose that the study used a sample of n = 9 infants and the data produced an average of M = 13 for the attractive face with an estimated standard error sM= 1 (SS = 72). If there were no preference, the 20 seconds should be divided equally between the two photographs. Note that all the available information comes from the sample. Specifically, we do not know the population mean or the…
A college bookstore must order books two months before each semester starts. They believe that the number of books that will ultimately be sold for any particular course is related to the number of students registered for the course when the books are ordered. They would like to develop a bestfitting line to predict how many books to order. From past records, the bookstore obtains the number of students registered, X, and the number of books actually sold for a course, Y , for 12 different semesters.A scatterplot of the data along with the best fitting line is presented below. a. The correlation between the two variables is r = .89. Calculate and interpret the value of r2.b. The equation for the best fitting line is Y = 9.30 + 0.673X. Explain and interpret the value of 9.30.c. How many books should the store order for a class of 50 students? Would you trust this prediction?
Have you ever been on an airplane and heard the pilot say that the plane would be a little late because it would be flying into a strong headwind or that even though the plane was taking off a bit late, you would be making up time because you would be flying with a tailwind? This problem asks you to analyze such a situation. You have the following data: A plane flying at its maximum speed can go 230 miles per hour with a tailwind or 150 miles per hour into a headwind. What is the wind speed (in miles per hour)? What would be the maximum speed of the plane (in miles per hour) if there were no wind?

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