14) - Part Ajavascript:WebForm_DoCallback('__Page',H_6.Chapter 7Q Search tA regression model relating x, number of salespersons at a branch office, to`y, annual sales at the office (in thousands of dollars) provided the following regression output. WhereTtotal = 26,ANOVAdfSSMS FSignificance FRegression7,191.1ResidualTotal9,555.8CoefficientsStandard Errort StatP-valueIntercept71.011.707Number of57.05.893Salespersonsa. Write the estimated regression equation (to whole number).b. Compute the F statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals)F-valueНо, we - Select your answer -p-value is - Select your answer -c. Compute the t statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals)t StatV, we, we- Select your answer - v Ho: B, =p-value isSelect your answer-d. Predict the annual sales at the Memphis branch office. This branch employs 11 salespersons.24thousand (to whole number)MacBook Air

The independent variable is number of sales persons. The dependent variable is annual sales. We have…

Answered: A regression model relating x, number…

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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** had to resubmit this question because the first time the data was duplicated and reflected incorrectly. The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 1 2 3 4 5 5.5 6 Overall Grades 96 89 87 77 76 68 64 **Please circle the answer for each step so I don't get confused. Thanks in advance for helping me with the breakdown and notes** Step 1 of 6 : Find the…
please anwer whatever you are allowed too. Thank you. A regression was run to determine if there is a relationship between the happiness index (y) and life expectancy in years of a given country (x).The results of the regression were: ˆyy^=a+bxa=-1.68b=0.168 (a) Write the equation of the Least Squares Regression line of the formˆyy^= + x(b) Which is a possible value for the correlation coefficient, rr? -1.417 1.417 0.702 -0.702 (c) If a country increases its life expectancy, the happiness index will increase decrease (d) If the life expectancy is increased by 0.5 years in a certain country, how much will the happiness index change? Round to two decimal places.(e) Use the regression line to predict the happiness index of a country with a life expectancy of 69 years. Round to two decimal places.
A regression was run to determine if there is a relationship between the happiness index (y) and lifeexpectancy in years of a given country (x). The results of the regression were: y^=a+bx ; a=-0.423 ,b=0.07 a. Write the equation of the Least Squares Regression line.b. Find the value for the correlation coefficient, r?c. If a country increases its life expectancy, the happiness index will Increase or decrease ( circleone)d. If the life expectancy is increased by 1 year in a certain country, how much will the happinessindex change? Round to two decimal places.e. Use the regression line to predict the happiness index of a country with a life expectancy of 85years. Round to two decimal places.-
To determine if the listing price of a house influences the selling price; a financial analyst sampled fifty houses and collected data on sale price,Y,(in $’000) and listed price,X,(in$’000) and fitted a regression model to the data
The following linear regression model predicts a person's height (cm) from the length of their shoe print (cm) Height^=3.5×Shoe Print+80 What is the predicted height of a person with a 30 cm shoe print? Assume extrapolation is not an issue. 185 cm 80 cm 202.5 cm 167.5 cm
The following data table shows the historical data for the first semester 2020, of the amount of sales of the company "IRC", which sells sneakers. Utilizing multiple lineal regression (as shown on the image), find an equation that estimates the number of sneakers sold by the company, based on advertising and revenue. Also, determine the standard error of estimation, the coefficient of determination, and the correlation coefficient. Write down what was the quantity in thousands sold in July if the amount of ads was 8 and the income for each unit was $135
a. what is the equation of the regression line? b. interpret r of the regression line c. interpret r^2 of the regression line L1 - 4,15,12,11,8,6,7,2,7,14,20,3,13 L2 - 120,200,140,110,120,80,190,100,120,190,190,110,120
Write short note on regression line?
Consider the points {(1,4), (3,11), (4,10)}, whose slope* of the linear regression model is 2.21. What would be the y-intercept* of the linear model with this same slope, but adjusted to the following data: {(14.41), (18.54), (22.67)}
The number of initial public offerings of stock issued in a 10-year period and the total proceeds of these offerings (in millions) are shown in the table. Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 628. The equation of the regression line is y = 31.645x+17,909.644. ^ 187 154 451 698 475 494 386 62 66 18,700 28,176 44,414 31,249 35,820 35,165 21,462 12,081 31,272 28,256| Issues, x 424 Proceeds, y Click the icon to view a table of critical values for the t-distribution. Construct and interpret a 95% prediction interval for the proceeds when the number of issues is 628. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest million dollars as needed. Type your answer in standard form where "3.12 million" means 3,120,000.) A. There is a 95% chance that the predicted proceeds given 628 issues is between $ and $ B. We can be 95% confident that when there are 628 issues, the proceeds will…
Please answer all parts of the question, thank you
Create scatterplots using the data in the spreadsheet linked above and display the equation for the regression line. What is the equation for the regression line that predicts home equity using credit score as the explanatory variable? Y^=x+() What is the interpretation of the slope? What is the interpretation of the intercept? data from spreadsheet Credit score Home equity 709 7,075 699 28,133 720 15,006 711 3,063 706 22,033 733 64,526 701 24,155 723 30,181 727 47,226 705 19,661 727 43,211 725 52,811 717 19,872 715 99,246 723 156,178 724 101,346 714 89,711 712 67,690 713 31,142 713 98,423 726 63,359 680 -7,002 683 117 701 50,773 694 49,677 682 18,414 692 21,915 677 -4,251 704 37,980 667 8,093 694 27,380 682 -9,411 681 10,641 690 13,720 680 21,976 709 21,803 687 -11,464 707 102,833 696 54,641 708 186,909 718 122,187…

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