Question 2Here are the total expenditures (in billions of dollars) for nursing home care in the US for the years 2014 through 2017.YearExpenditures2014152.6●2015158.120161632017166.3Let E (t) be the total expenditures (in billions of dollars) for nursing home care in the US t years after 2014.• Use your calculator to perform the linear regression and the exponential regression for this data.Report each regression equation. Be sure to use the variables defined for our data.• Determine which model best fits the data (support your choice).• Use the best fitting model to predict the total expenditures (in billions of dollars) for nursing home care in the US in2030.

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Answered: Here are the total expenditures (in…

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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Analysis of the relationship between the fuel economy (combinedMPG) and displacement (in liters) for 1262 models of cars produces the regression model combinedMPH = 33.472 - 3.317Displacement. Explain what the slope means.
Scenario: A medical researcher wishes to see whether there is a relationship between a person's age, cholesterol level, and systolic blood pressure. Eight people are randomly selected. The data is listed in the table. First, find the multiple regression equation. Next, determine the coefficient of determination. Then, use the regression equation to predict a person's blood pressure reading if the person selected is 50 years old with a cholesterol reading of 220. Age Cholesterol level Blood pressure Person 1 38 220 116 Person 2 41 225 120 Person 3 45 200 123 Person 4 48 190 131 Person 5 51 250 142 Person 6 53 215 145 Person 7 57 200 148 Person 8 61 170 150 Discussion Prompts Respond to the following prompts in your initial post: 1. Identify the explanatory variables and response variable for the data. 2. What is the multiple regression equation for the data? 3. What is the coefficient of determination? 4. If a person 50 years old with a cholesterol of 220 is selected, what is that…
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**Based on the regression results, answer the following questions** Data are collected on the income (measured in $1000’s of $’s), house value (measured in $1000’s of $’s), years in a home, age, sex (=1 for male, =0 for female), and the amount outstanding on a mortgage (measured in $1000’s of $’s). The dependent variable is income. Based on the regression results, answer the following questions e) Are any of the explanatory (independent) variables significant at the 10% level of significance? How do you know? f) What is the predicted value of income for a person that has been in a house for 5 years, is 38 years old, is a male, has a house valued at $250,000, and has $100,000 left on their mortgage? (g) What is the effect on the income of a person being a male versus a female?
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1. Develop a simple linear regression equation for starting salaries using an independent variable that has the closest relationship with the salaries. Explain how you chose this variable.
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While attempting to measure its risk exposure for the upcoming year, an insurance company notices a trend between the age of a customer and the number of claims per year. It appears that the number of claims keep going up as customers age. After performing a regression, they find that the relationship is (claims per year) = 0.385*(age) + 5.218. If a customer is 44.315 years old and they make an average of 11.239 claims per year, the residual is -11.04. Interpret this residual in terms of the problem. Question 10 options: 1) The number of claims per year is 11.04 claims less than what we would expect. 2) The age is 11.04 years larger than what we would expect. 3) The age is 11.04 years less than what we would expect. 4) The number of claims per year is 11.239 claims less than what we would expect. 5) The number of claims per year is 11.04 claims…
Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the value of the independent variable is increased by one unit, then find the change in the dependent variable yˆy^. hour studyings 1 2 4 5 6 midterm grades 62 65 73 75 81

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