Consider a linear regression model where y represents the response variable, x is a quantitative explanatory variable, and d is a dummy variable. The model is estimated as yˆy^ = 14.6 + 4.5x − 3.4d.
a. Interpret the dummy variable coefficient.
Intercept shifts down by 3.4 units as d changes from 0 to 1.
Slope shifts down by 3.4 units as d changes from 0 to 1.
Intercept shifts up by 3.4 units as d changes from 0 to 1.
Slope shifts up by 3.4 units as d changes from 0 to 1.
b. Compute y^ for x = 2 and d = 1. (Round your answer to 1 decimal place.)
c. Compute y^ for x = 2 and d = 0. (Round your answer to 1 decimal place.)
a)Intercept shifts down by 3.4 units as d changes from 0 to 1
b) from given regression equation: y^ =14.6+4.5*2-3.4*1 =20.2
c) y^ =14.6+4.5*2-3.4*0 =23.6
Consider a linear regression model where y represents the response variable, x is a quantitative explanatory...
Consider a linear regression model where y represents the response variable, x is a quantitative explanatory variable, and d is a dummy variable. The model is estimated as yˆy^ = 14.4 + 4.6x − 3.1d. a. Interpret the dummy variable coefficient. Intercept shifts down by 3.1 units as d changes from 0 to 1. Slope shifts down by 3.1 units as d changes from 0 to 1. Intercept shifts up by 3.1 units as d changes from 0 to 1. Slope shifts...
Exercise 17-27 Algo Consider a binary response variable y and an explanatory variable x that varies between 0 and 4. The linear model is estimated as yˆy^ = −1.18 + 0.63x. a. Compute the estimated probability for x = 2 and x = 3. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.) b. For what values of x is the estimated probability negative or greater than one? (Round your answers to 2...
Use the following linear regression equation to answer the questions. x1 = 1.5 + 3.4x2 – 8.3x3 + 2.3x4 (a) Which variable is the response variable? Which variables are the explanatory variables? (b) Which number is the constant term? List the coefficients with their corresponding explanatory variables. constant? x2 coefficient? x3 coefficient? x4 coefficient? (c) If x2 = 1, x3 = 8, and x4 = 6, what is the predicted value for x1? (Use 1 decimal place.) (d) Explain how...
Decide (with short explanations) whether the following statements are true or false. e) In a simple linear regression model with explanatory variable x and outcome variable y, we have these summary statisties z-10, s/-3 sy-5 and у-20. For a new data point with x = 13, it is possible that the predicted value is y = 26. f A standard multiple regression model with continuous predictors and r2, a categorical predictor T with four values, an interaction between a and...
1. Using question 12 (delaying major purchases) as the response variable (Y) compute a regression model with the following questions 9, 25 (gender: males as 0 and females coded as 1) as your predictor variables. You will have to use the data set Economic Gun Legislation Survey Regression Exercise posted for Week 9 on the webpage. Please do the following in exactly this order: a. Excel Output b. Model: write down model like in form y- b, b,X, -b.X. +...
DO NOT ANSWER IF YOU ARE UNSKILLED IN THIS AREA! Consider a binary response variable y and an explanatory variable x that varies between 0 and 4. The linear model is estimated as yˆy^ = −1.19 + 0.53x. a. Compute the estimated probability for x = 2 and x = 3. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.) Estimated probability x = 2 x = 3 b. For what values of...
In the simple linear regression model, the slope represents the: A. change in y per unit change in x B. value of y when x = 0 c. change in x per unit change in y D. value of x when y = 0 In the first-order linear regression model, the population parameters of the y-intercept and the slope are estimated by CA. bo and A CB. bo and b CC. A and Po CD. b and Bo
Part A Consider the Simple Linear Regression model. If the COV[X,Y] = 2.4, VAR[X] = 1.2, X-bar = 9.6, and Y-bar = 23.4, then compute the slope coefficient Beta1. Provide your answer with three decimal places of precision, e.g. 0.001. Part B Consider the Simple Linear Regression model. If the COV[X,Y] = 2.4, VAR[X] = 1.2, X-bar = 9.6, and Y-bar = 23.4, then compute the intercept Beta0. Provide your answer with three decimal places of precision, e.g. 0.001.
2. Consider a simple linear regression i ion model for a response variable Y, a single predictor variable ,i1.., n, and having Gaussian (i.e. normally distributed) errors: This model is often called "regression through the origin" since E(X) = 0 if xi = 0 (a) Write down the likelihood function for the parameters β and σ2 (b) Find the MLEs for β and σ2, explicitly showing that they are unique maximizers of the likelihood function Hint: The function g(x)log(x) +1-x...