The personnel director of a large hospital is interested in determining the relationship (if any) between an employee's age and the number of sick days the employeetakes per year. The director randomly selects ten employees and records their age and the number of sick days which they took in the previous year.Employee 1 2 3 4 5 6 7 8Age30 50 40 55 30 28 6025Sick Days743 2 91008Copy DataThe estimated regression line and the standard error are given.Sick Days= 14.310162 - 0.2369(Age9 1030 455 2Se = 1.682207Find the 95% confidence interval for the average number of sick days an employee will take per year, given the employee is 26. Round your answer to two decimalplaces.

The defined regression equation is: Sick days=14.310162-0.2369Age. The standard error of the…

Answered: The personnel director of a large…

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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You are a manager at a restaurant and you want to see if there is a relationship between the number of hours your employees work and the number of sales they made. You collect the following data: Employees Hours Worked Sales Made (Y) X2 Laura 6 100 Sarah 8 120 Tim 10 140 Jimmy 12 160 Carter 14 180 Totals determine the correlation coefficient and determine if a statistically significant relationship exists between the two variables. If there is, then they must also supply the linear regression model.
a. Determine the correlation coefficient between the number of periods and the sales. Is time series a good method of predicting the monthly sales for year 4?b. Determine the correlation coefficient between the sales and the number of tourists in the area. Is a linear regression a good method to predict the sales for a month?
Is It Getting Harder to Win a Hot Dog Eating Contest?Every Fourth of July, Nathan’s Famous in New York City holds a hot dog eating contest. The table below shows the winning number of hot dogs and buns eaten every year from 2002 to 2015, and the data are also available in HotDogs. The figure below shows the scatterplot with the regression line. Year Hot Dogs 2015 62 2014 61 2013 69 2012 68 2011 62 2010 54 2009 68 2008 59 2007 66 2006 54 2005 49 2004 54 2003 45 2002 50 Winning number of hot dogs in the hot dog eating contest Winning number of hot dogs and buns Click here for the dataset associated with this question. (a) Is the trend in the data mostly positive or negative? Positive Negative (b) Using the figure provided, is the residual larger in 2007 or 2008?Choose the answer from the menu in accordance to item (b) of the question statement 20072008 Is the residual positive or…
Activity – Correlation & Regression Problem: Given are the dataset of age and height. Determine the correlation coefficient and the regression line equation for this data. Give 5 age values that you want to use in order to determine the possible height of the person. Age 19 Height 172 18 170 18 175 20 170 19 173 20 174 21 178 22 179 24 180 25 183 26 181 185 185 27 29 30 188 30 186
The correlation between first year college GPA and high school GPA is 0.683. If a simple linear regression was conducted to predict first year college GPA from high school GPA what does the correlation tell us about the fit of the model?
Name Her Age His Age Barack and Michelle Obama 45 47 George W. and Laura Bush 54 54 Bill and Hillary Clinton 45 46 Ronald and Nancy Reagan 55 64 Gerald and Betty Ford 59 69 Lyndon and Lady Bird Johnson 56 61 John and Jacqueline Kennedy 31 43 Dwight and Mamie Eisenhower 50 55 (c) Remove the outlier and compute the least-squares regression line for predicting the president's age from first lady's age. Round the slope and y -intercept values to at least four decimal places. Regression line equation: =y
Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $140 million. Use a significance level of a = 0.05. Budget ($)in Millions Gross ($) in Millions 39 22 118 67 77 49 124 66 12 64 128 19 6. 147 9. 118 6. 99 75 127 107 95 99 64 109 209 44 8 293 48 Click the icon to view the critical values of the Pearson correlation coefficient r. The regression equation is y =+x. (Round to one decimal place as needed.)
Post secondary education information was examined for a random selection of states. The data below show the number of community colleges in the number of universities for each particular state. Community: 12, 17, 13, 10, 8 University: 4, 6, 5, 4, 3 A. Create a scatterplot of the given data sets B. Find the correlation coefficient of the sets of data. C. Create the equation of the regression line for the data and evaluate it when X=300.
Correlation and linear regression
Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $135 million. Use a significance level of alpha equals 0.05 . Budget left parenthesis $ right parenthesis in Millions 45 24 115 74 72 48 117 67 4 60 124 24 6 152 8 Gross left parenthesis $ right parenthesis in Millions 115 10 95 69 127 112 93 101 50 102 223 26 18 282 56 The regression equation is ŷ = __ + __x. (Round to one decimal place as needed.)
Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $105 million. Use a significance level of a = 0.05. Budget ($)in Millions Gross ($) in Millions 41 23 114 75 78 47 120 64 10 59 127 22 12 150 2 0 127 18 111 65 113 112 102 94 64 98 211 41 22 288 57 Click the icon to view the critical values of the Pearson correlation coefficient r. ..... x. (Round to one decimal place as needed.) The regression equation is = + The best predicted gross for a movie with a $105 million budget is $ million. (Round to one decimal place as needed.)

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