4. Our R² implies that lots of stuff, other than health, also affects doctor visits. One such thing is aperson's insurance status. The data file includes a third variable that records whether the person hadhealth insurance during 2019. Estimation a regression of the form y = Bo + B₁x1 + B₂x₂ where x₁ is thehealth status variable from above, but now x₂ records whether the person had insurance.a) Interpret the estimate of B₁ in words.b) Interpret the estimate of B₂ in words.c) Forecast a person's number of doctor visits in 2019 if he/she was in excellent health, but did not haveinsurance.d) Forecast a person's number of doctor visits in 2019 if he/she was in poor health, and did haveinsurance.e) The R² for this regression is

As per our guidelines we are supposed to answer only 3 sub-parts. a) In the regression…

Answered: 4. Our R² implies that lots of stuff,…

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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Similar questions

Nine pairs of data yield a regression equation of y=0.93x + 19.4, with r= 0.967 and an average y value of 64.70. What is best predicted value for y when x =65? Is it 79.85, 25.74, 89.61, 57.82, 70.55, 96.70, 19.40, or 64.70?
Suppose you are estimating a wage regression, where salary is the dependent variable and age, years of education and a dummy variable for male are your independent variables. You are interested in measuring how salary differs between those who have at least a college education with those who have less than a college education. If a person is considered as having a college education when she has more than 12 years of education, how can you measure the difference in salary between college and non-college educated individuals? Select one: a. Multiply coefficient for years of education in original regression by 12 O b. Re-estimate model replacing years of education with a dummy variable for college c. Re-estimate model replacing years of education with a dummy variable for college and one for no college O d. Re-estimate model interacting years of education with a dummy variable for college e. Calculate the difference in predicted salary between an individual with 14 years of education and…
If the estimated intercept of the regression equation is negative, we can say the estimated correlation coefficient between the two variables is also negative. O True O False
The object in linear regression is to obtain an equation of a curve that minimizes the sum of squared vertical deviations of data points from the line. true or false?
A regional transit authority is concerned about the number of riders on one of its bus routes. In setting up the route, the assumption is that the number of riders is the same on every day from Monday through Friday. A random sample of 100 riders yielded the following results: Day Monday Tuesday Wednesday Thursday Friday Using a = 10%, determine whether the transit authority's assumption is correct. Number of Riders 20 15 30 17 16
Develop a scatterplot and explore the correlation between customer age and net sales by each type of customer (regular/promotion). Use the horizontal axis for the customer age to graph. Find the linear regression line that models the data by each type of customer. Round the rate of changes (slopes) to two decimal places and interpret them in terms of the relation between the change in age and the change in net sales. What can you conclude? Hint: Rate of Change = Vertical Change / Horizontal Change = Change in y / Change in x
Ariel was running analyses over and over in census data and came across a correlation between weight and debt (r=.78). Independent variable is weight and dependent variable is debt. b) Curious Ariel noted some statistics on these weight (M=160lb, SD=15lb) and debt (M=196k, SD=20k). If Ariel wanted to calculate a regression equation, what would her slope and intercept be?
** Based on the regression results, answer the following questions ** A sample of data is collected (from 1999 and 2000) concerning the compensation of the executives (compensation is measured in 1000’s of $’s) of a number of public companies along with other firm-specific data. The dependent variable is total compensation, CEOANN is a dummy variable =1 for an individual who is a CEO and =0 for individuals who are not CEO’s, EMPL is total employees, MKTVAL is the natural logarithm of the market value of the firm, EPSIN is earnings per share, YEAR is a dummy variable = 1 for the year 2000 and =0 for year 1999, and ASSETS is the natural logarithm of the total assets of the company. Based on the regression results, answer the following questions b) What is the estimated regression equation? c) What percentage of the variation in income in explained by the regressors? d) What is the standard error of the error term in the regression equation?
Can a causal relationship be established between a variable y and a variable x by running the following regressions: i) y = f(x) and ii) x = f(y). Explain in less than 75 words.
In a fisheries researchers experiment the correlation between the number of eggs in tge nest and the number of viable (surviving ) eggs for a sample of nests is r=0.67 the equation of the regression line for number of viable eggs y versus number of eggs in the nest x is y =0.72x + 17.07 for a nest with 140 eggs what is the predicted number of viable eggs ?
8. Which is the linear regression equation for a scatterplot with these points rounded to the nearest tenth: (4, 35), (6.5, 92), (2. 10). (5, 50), (6, 85), (10, 110)?

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