2. Consider a multiple linear regression model with two
independent variables and no intercept. Assume n independent
observations are available.
(a). Write down the model in matrix form. Clearly indicate the
content of every matrix used in this representation.
(b). What is the Rank of X. for the above model? Explain why?
(c). Compute the expressions for the least square estimators of B,
and B2. Do not over-simplify the elements in your matrices.
2. Consider a multiple linear regression model with two independent variables and no intercept. Assume n...
43. A multiple regression analysis is conducted with 5 independent variables and an intercept on a sample of 100 observations. Suppose you want to conduct a hypothesis to test whether the coefficient of the first variable is statistically significant. What will be the degrees of freedom for this test? A.98 B. 99
in a multiple regression model, there are four independent variables and 60 observations. what are the degrees of freedom associated with the error some of squares?
please help me to solve that question Consider two separate linear regression models and For concreteness, assume that the vector yi contains observations on the wealth ofn randomly selected individuals in Australia and y2 contains observations on the wealth of n randomly selected individuals in New Zealand. The matrix Xi contains n observations on ki explanatory variables which are believed to affect individual wealth in Australia, and he matrix X2 contains n observations on k2 explanatory variables which are believed...
9. In a multiple linear regression model with K independent variables, a t-test is applied to test for a single parameter. The degrees of freedom of this t-test is n-2 n-1 n-K-1 n-K
1. In a multiple regression model, changing the scale of one of the independent variables (a) changes the standard error of its own OLS slope estimator (b) changes the standard error of all OLS slope estimators (c) changes the own t-statistic for testing its statistical significance (d) makes its confidence interval larger (e) All of the above
Consider the multiple regression model shown next between the dependent variable Y and four independent variables X1, X2, X3, and X4, which result in the following function: Y = 33 + 8X1 – 6X2 + 16X3 + 18X4 For this multiple regression model, there were 35 observations: SSR= 1,400 and SSE = 600. Assume a 0.01 significance level. What is the predictions for Y if: X1 = 1, X2 = 2, X3 = 3, X4 = 0
1. In order to test whether the multiple linear regression model y bo +b,x1 + b2X2 is better than the average model (lazy model), which of the following null hypotheses is correct: a. Ho' b1 = b2 = 0 Но: B1 B2-0 с. We have a dataset Company with three variables: Sales, employees and stores. To build a multiple linear regression model using Sales as dependent variable, number of stores and number of employees as independent variables, which of the...
The estimated regression equation for a model involving two independent variables and 10 observations follows. y = 32.3322 + 0.7179x1 + 0.7718x2 a. Interpret b1 and b2 in this estimated regression equation - Select your answer - b2 - Select your answer - 180 and x2 b. Estimate y when x1 310 (to 3 decimals).
Question 2 (0.5 mark) Consider the multiple regression model containing three independent variables, under Assumptions MLR.1 through MLR.4: y = B. +B,X,+B2x2 +Bzx3+u You are interested in estimating the sum of the parameters on Xı and xz; call this 0 = + B2 (1) Show that Ô, = B1 + B2 is an unbiased estimator of , (ii) Find Varê, in terms of Varhi). Var(82), and Corr1. B2).
What are other Independent variables (control variables) that I can add to my multiple linear regression model that is supposed to examine the relationship of several independent variables on the "Happiness Index" At the Moment, I have "Hours worked", "GDP per Capita", "Unemployment rate", "Literacy rate" and "Divorce rate". But what are other possibilities?