Morgan Bank has been encouraging its customers to use its new mobile banking app. While this may be good for business, the bankhas to deal with a number of inquiries it receives about the new app. The accompanying data file includes weekly inquiries the bankhas received over the past 30 weeks.Click here for the Excel Data Filea-1. Estimate the linear trend model.Note: Negative values for regression coefficients should be indicated by a minus sign. Round final answers to 2 decimal places.Predictor VariableConstantWeekCoefficienta-2. Use the estimated model to forecast the number of inquiries over the next two weeks.Note: Round coefficient estimates to at least 4 decimal places and final answers to 2 decimal places.WeekForecast3132 ABCDEFGHK1WeekInquiries234567891011121314151612345678901222222222222228833333728128028130927127528126625428027217182051926520263212332226923248242712522526253272502826329245302043122132333435278243

I will use Excel for run a regression analysis to find the linear trend model, here are the steps…

Answered: Morgan Bank has been encouraging its…

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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The following table shows the percentage of people 25 years and older who have completed four or more years of college. Use the line of best fit (regression line) to predict when (what year) the percentage will reach 37%. Round the slope and y-intercept to four decimal places, if necessary. Round your final answer to the nearest whole number.
need someone to double check
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. E Click the icon to view the monthly data. a. Develop a simple linear regression model between billable hours and overhead costs. Overhead Costs = 5304.4 + (0.0219) × Billable Hours +1 (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.) Monthly overhead costs and billable hours data Overhead Costs Billable Hours O IT $385,000 3,000 $430,000 4,000 $460,000 5,000 $511,000 6,000 $580,000 7,000 $600,000 8,000 Print Done
Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported asy=29.62x+64.57y=29.62x+64.57and the r=0.784r=0.784.What proportion of the variation in y can be explained by the variation in the values of x? r² = %Report answer as a percentage accurate to one decimal place.
Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported as . 72.45х + 93.26 y = - 0.23. and the r = What percentage of the variation in y can be explained by the variation in the values of x? r2 = % (Report exact answer, and do not enter the % sign)
please assist, the question states to "click on the datafile logo to reference the data" but the data is listed already in the question. when clicking that link, it opens up the same information in excel so please do not reject because the data is there already.
Please help.Thanks so much
Refer to the Baseball 2018 data, which reports information on the 2018 Major League Baseball season. Let attendance be the dependent variable and total team salary be the independent variable. Determine the regression equation and answer the following questions. Click here for the Excel Data File Team Salary Year Stadium Opened Attendance Net Worth League ($ mil) HR BA Wins ERA mil $ bil National 143.32 176 0.235 82 3.72 1998 2.242695 1.21 National 130.6 175 0.257 90 3.75 2017 2.555781 1.625 American 127.63 188 0.239 47 5.18 1992 1.564192 1.2 American 227.4 208 0.268 108 3.75 1912 2.895575 2.8 National 194.26 167 0.258 95 3.65 1914 3.181089 2.9 American 71.84 182 0.241 62 4.84 1991 1.608817 1.5 National 100.31 172 0.254 67 4.63 2003 1.629356 1.01 American 142.8 216 0.259 91 3.77 1994 1.926701 1.045 National 143.97 210 0.256 91 4.33 1995 3.01588 1.1 American 130.96 135 0.241 64 4.58 2000 1.85697 1.225 American 163.52 205 0.255 103 3.11 2000…
Please provide a detailed solution for the question below (Table: Physicians per 10,000 Population and Life Expectancy) The table contains a subset of data reported in 2016 by the World Health Organization. Use these data to generate the regression equation for predicting life expectancy in a country from the number of physicians per 10,000 people in that country. To get you started, the mean and the standard deviation for both variables have been calculated. .Please provide detailed solution Table: Physicians per 10,000 Population and Life Expectancy Country Physicians/10,000 people Life expectancy Bangladesh 4.8 72.7 Cambodia 1.7 69.4 United States 25.9 78.5 Egypt 8.1 70.5 France 32.3 82.9 Japan 24.1 84.2
The sheet called HousePr contains data on prices of houses that have sold recently and two attributes of the house – the number of bedrooms and the size. Column 1 is the selling price of the house in thousands of dollars and column 2 is the size in hundreds of square feet.a. Draw a scattergram of price vs size. Discuss whether this scattergram supports an assumption of a linear relationship between price and size.b. Using Excel, obtain the equation of the linear regression line that fits this data for price vs. size.c. Using relevant Excel output, discuss whether the true slope of the regression line is different from zero.d. What is the expected price for a house with size 2000 square feet? Using relevant Excel output, discuss whether the margin of error of this expected price will be low or high.e. Using Excel, obtain the equation of the linear regression line that fits this data for price vs. number of bedrooms. Is the true slope different from zero?f. What is the expected price for…
Develop an estimated multiple regression equation that relates risk of a stroke to a person's age, systolic blood pressure and whether the person is a smoker. x1=persons age x2systrolic blood pressure x3=whether person is a smoker or non smoker
please answer the last question on the screenshot. "what is the interpretation of the intercept?"

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