Step 1 of 3 : Write the estimated regression equation using the least squares estimates for b0and b1. Round to four decimal places, if necessary. Regression StatisticsMultiple R0.935409572R Square0.874991067Adjusted R Square0.865374995Standard Error57.78795393Observations15ANOVAdfSSMSFRegression1303,864.914286303,864.91428690.99256792Residual1343,412.8190483339.447619Total14347,277.733333CoefficientsStandard Errort StatP-valueIntercept443.9238095231.3995565914.137900592.85887E-09Month32.942857143.453490799.5390024593.10231E-07 Consider the following monthly revenue data for an up-and-coming technology company.Sales DataMonthRevenue (Thousands of Dollars)MonthRevenue (Thousands of Dollars)13259.7972547108193539118314580128485640138606.699148637697158598708

The regression equation is y = b0 + b1x, where b0 is the y intercept, b1 is the slope coefficient, x…

Answered: Write the estimated regression equation…

Write the estimated regression equation using the least squares estimates for b0 and b1. Round to four decimal places, if necessary.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

While collecting data on shoe sizes (y) compared to heights in inches (x) of male students in the class a student found that the shoe sizes ranged from size 7 to size 11 and the heights of the students ranged from 60 to 72 inches. The student ran a linear regression to get the function = 1 -x- 3 13 where y is the shoe size and is the height of the person in inches. What would be the shoe size for a student who was 73 inches tall? Shoe sizes only show up in incriments of 0.5 (ie. 7, 7.5, 8, 8.5, 9, 9.5, ....) so round to the nearest 1/2 shoe size. Show all your work.
Report the equation of the regression line and interpret it in the context of the problem
A marketing consultant created a linear regression model to predict the number of units sold by a client based on the amount of money spent on marketing by the client. Which of the following is the best graphic to use to evaluate the appropriateness of the model?
The managing director of a consulting group has the accompanying monthly data on total overhead costs and professional labor hours to bill to clients. Complete parts a through c Click the icon to view the monthly data. a. Develop a simple linear regression model between billable hours and overhead costs. Overhead Costs = 247733.3 +(43.2000) x Billable Hours (Round the constant to one decimal place as needed. Round the coefficient to four decimal places as needed. Do not include the $ symbol in your answers.) b. Interpret the coefficients of your regression model. Specifically, what does the fixed component of the model mean to the consulting firm? Interpret the fixed term, bo. if appropriate. Choose the correct answer below. OA. The value of by is the predicted overhead costs for 0 billable hours. OB. For each increase of 1 unit in overhead costs, the predicted billable hours are estimated to increase by bo OC. It is not appropriate to interpret by. because its value is the predicted…
The table shows the average weekly wages (in dollars) for state government employees and federal government employees for 8 years. The equation of the regression line is y = 1.493x - 83.403. Complete parts (a) and (b) below. A Average Weekly Wages (state), x Average Weekly Wages (federal), y 764 1003 766 1048 791 1119 (a) Find the coefficient of determination and interpret the result. r² = 0 (Round to three decimal places as needed.) 800 1152 843 1201 887 1250 924 1277 939 1306
Find the linear model that best fits this data using regression and enter the model below
The table lists the average tuition and fees at private colleges and universities for selected years. Year 1985 1990 1995 2000 2008 5311 25,115 Tuition and Fees (in dollars) 9375 SO 12,418 (a) Find the equation of the least-squares regression line that models the data. y 840.450 (Type the slope as a decimal rounded to three decimal places. Round the y-intercept to the nearest integer.) (b) Graph the data and the regression line in the same viewing window using the parameters given below the graph choices. Choose the correct graph below. OA. O B. o HE RO OC. 16,230 A o ƠN
A biologist collected data on a sample of 20 porcupines. She wants to be able to predict the body mass of a porcupine (M, in grams) based on the length of the porcupine (L, in cm). Her least squares regression equation is M = – 3089 + 175.6L. Predict the body mass of a porcupine that is 51 cm long. Report your answer using one decimal place. O 5661.0 g O 5732.5 g O 5866.6 g O 6139.2 g eTextbook and Media Save for Later Last saved 3 minutes ago. Attempts: 2 of 3 used Submit Answer Saved work will be auto-submitted on the due date. Auto- submission can take up to 10 minutes.
Use the time/tip data from the table below, which includes data from New York City taxi rides. (The distances are in miles, the times are in minutes, the fares are in dollars, and the tips are in dollars.) Find the regression equation, letting time be the predictor (x) variable. Find the best predicted tip for a ride that takes 20minutes. How does the result compare to the actual tip amount of $4.55? Distance 1.40 1.65 0.68 1.32 8.51 1.80 1.02 12.71 Time 18.00 11.00 6.00 8.00 31.00 25.00 8.00 27.00 Fare 12.30 9.80 6.30 7.80 31.75 16.30 7.80 36.80 Tip 2.46 1.96 1.89 0.00 2.98 1.50 2.34 0.00 The regression equation is y=enter your response here+enter your response herex. (Round the y-intercept to two decimal places as needed. Round the slope to four decimal places as needed.) The best predicted tip for a ride that takes 20 minutes is $enter your response here. (Round to the…
Compute the least-squares regression equation for the given data set. Round the slope and yFintercept to at least four decimal places. 4 y 7. 3. Send data to Excel Regression line equation: y =|
An automotive sales manager wishes to examine the relationship between age (years) and sales price ($) for used automobiles of a certain brand. The accompanying table contains data for a sample of a certain make and model that were listed for sale at a car shopping website. b. Fit a quadratic regression model to predict price and state the quadratic regression equation.
In the graph shown below consider the horizontal line to represent the average y value for the data set and the slant line to represent the linear regression equation. use only the graph of the data to do the following: