A particular professor has noticed that the number of people, P, who complain about his attitude isdependent on the number of cups of coffee, n, he drinks. From eight days of tracking he compiled thefollowing data:Реople (P)13131077734Cups of coffee (n)1123345Unless otherwise stated, you can round values to two decimal places.a) Using regression to find a linear equation for P(n)P(n) =%3Db) Interpret the meaning of the slope of your formula in the context of the problemc) Interpret the meaning of the P intercept in the context of the problemd) Use your model to predict the number of people that will complain about his attitude if he drinks 8cups of coffee.(Round to 2 decimals)e) Is the answer to part d reasonable? Why or why not?

A particular professor has noticed that the number of people, P, who complain about his attitude is dependent on the number of cups of coffee, n, he drinks. From eight days of tracking he compiled the following data: Реople (P) 13 13 10 7 7 7 4 Cups of coffee (n) 1 4 5 Unless otherwise stated, you can round values to two decimal places. a) Using regression to find a linear equation for P(n) P(n) = b) Interpret the meaning of the slope of your formula in the context of the problem c) Interpret the meaning of the P intercept in the context of the problem

A particular professor has noticed that the number of people, P, who complain about his attitude is dependent on the number of cups of coffee, n, he drinks. From eight days of tracking he compiled the following data: Реople (P) 13 13 10 7 7 7 4 Cups of coffee (n) 1 4 5 Unless otherwise stated, you can round values to two decimal places. a) Using regression to find a linear equation for P(n) P(n) = b) Interpret the meaning of the slope of your formula in the context of the problem c) Interpret the meaning of the P intercept in the context of the problem

College Algebra

7th Edition

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section: Chapter Questions

Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...

See similar textbooks

Similar questions

Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.
The table presents data on the taste test of 38 brands of pinot noir wine [data were first reported in an article by Kwan, Kowalski, and Skogenboe in the Journal Agricultural and Food Chemistry (1979, Vol. 27), the response variable is y = quality, and we want to find the "best" regression equation that relates quality to the other five parameters
Suppose that researchers are interested in determining the bi-annual salary of statisticians of different levels using their years of experience and their education level (M = bachelors, P = doctorate). They fit the following model to a dataset that includes these variables and, after performing the proper steps of multiple linear regression, the following multiple linear regression model is obtained: yˆ = 42308 + 323x1 + 213x2 + 301(x1*x2) where the variables are as follows: yˆ = predicted bi−annual salary in dollars, x1 = number of years of experiencex2= {1 if the education level is a doctorate 0 if the education level is a bachelors What is the predicted bi-annual salary in dollars of an employee with 5 years of experience and a bachelor’s degree?
Suppose that researchers are interested in determining the bi-annual salary of statisticians of different levels using their years of experience and their education level (M = bachelors, P = doctorate). They fit the following model to a dataset that includes these variables and, after performing the proper steps of multiple linear regression, the following multiple linear regression model is obtained: yˆ = 42308 + 323x1 + 213x2 + 301(x1*x2) where the variables are as follows: yˆ = predicted bi−annual salary in dollars, x1 = number of years of experiencex2= {1 if the education level is a doctorate 0 if the education level is a bachelors What is the predicted bi-annual starting salary of an employee with a doctorate degree? (Someone with no work experience). $ What is the predicted bi-annual starting salary of an employee with a bachelor’s degree? (Someone with no work experience). $
Compute the least-squares regression equation for the given data set. Use a TI-84 calculator. Round the slope and y-Intercept to at least four decimal places.
The following table shows the length, in centimeters, of the humerus and the total wingspan, in centimeters, of several pterosaurs, which are extinct flying reptiles. (A graphing calculator is recommended.) (a) Find the equation of the least-squares regression line for the data. (Where × is the independent variable.) Round constants to the nearest hundredth. y= ? (b) Use the equation from part (a) to determine, to the nearest centimeter, the projected wingspan of a pterosaur if its humerus is 52 centimeters. ? cm
The following table indicates the ages of a sample of female employees of People Plus Pty, and the corresponding monthly income of each employee (in thousands of Rands). Age In Years (x) 404932273846 Monthly Income (R000s) (y) 434936314142 By completing the table given below, and then applying the relevant formulae, determine the linear regression function for this bivariate data set. X Y X^2 XY TOTAL If a female employee is 39 years of age, estimate her monthly income.
The following table represents the survey result from the seven online stores. Use linear regression to find the linear equation that is best fit for the data, width x equal to the online advertising. Round your coefficient to three decimal places. Online Store Online Advertising (in thousand dollars) Monthly e-commerce Sales (in thousand dollars) 1 1.5 368 2 1.7 340 3 2.8 665 4 5 954 5 1.3 331 6 2.2 556 7 1.3 376
The data regarding the production of wheat in tons (X) and the price of the kilo of flour in Ghana cedis (Y) Takoradi some years ago were: a. Fit the regression line for the day using the method of least squares
The following table shows the marks in statistics and economics for ten students. Fit a least square line to the data using a) ‘X’ as the independent variable b) What will be the regression equation if X= 20