Hello i need help with this question of multiple regression.
In the area of STATISTICS.
Please very explicit answers step by step.
Homework Answers
Add Answer to:
Hello i need help with this question of multiple regression.
In the area of STATISTICS.
Please...
Considering multiple linear regression models, we compute the regression of Y, an n x 1 vector,...
Considering multiple linear regression models, we compute the regression of Y, an n x 1 vector, on an n x (p+1) full rank matrix X. As usual, H = X(XT X)-1 XT is the hat matrix with elements hij at the ith row and jth column. The residual is e; = yi - Ýi. (a) (7 points) Let Y be an n x 1 vector with 1 as its first element and Os elsewhere. Show that the elements of the...
Considering multiple linear regression models, we compute the regression of Y, an n x 1 vector,...
Considering multiple linear regression models, we compute the regression of Y, an n x 1 vector, on an n x (p+1) full rank matrix X. As usual, H = X(XT X)-1 XT is the hat matrix with elements hij at the ith row and jth column. The residual is e; = yi - Ýi. (a) (7 points) Let Y be an n x 1 vector with 1 as its first element and Os elsewhere. Show that the elements of the...
2) Suppose you have multiple regression set up Ynxi XnxpBpxi Sxl and f ~ N(0nx1, σ21.). P Po X(X,...
linear statistics modeling and regression
2) Suppose you have multiple regression set up Ynxi XnxpBpxi Sxl and f ~ N(0nx1, σ21.). P Po X(X,X)-X, be the projection matrix on the column space of X. a) Show residual vector, e = (1,-P)Y. Here e is the vector of residuals ei S. b) Show that the variance of e, is 1 - Pi, where P is the i, j th entry of the matrix P c) Show that the sample covariance of...
Figure 2 Regression Output SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard...
Figure 2 Regression Output SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.921261 0.848722 0.8055 0.711125 10 ANOVA Significance MS 0.001347 Regression Residual Total 19.86011 9.930053 19.63628 3.539894 0.505699 23.4 Standard Error Upper 95% Coefficients 0.20018 2.211198 0.07185 tStat P-value Lower 95% Intercept Size (cubic Metres) Weight (00's kg 2.19481 1.794453 0.676122 3.270412 0.013667 0.612423 3.809974 0.47295 0.329255 0.84353 -0.23731 0.819212 0.169626 0.42356 0.684594 (a)Based on the above regression output, interpret the regression coefficients...
Hello I really need help with my probability and statistics homework. Can you explain step by...
Hello I really need help with my probability and
statistics homework. Can you explain step by step how you got the
answer. thank you very much
Discrete Random Variable random variable X takes on the values according to the following probability chart 4 2c 3c 4c 3c 2c 4 Find C so that this is a probability distribution. CHECK Click here for the solution Find DF(2; X) DF(2, X) CHECK Click here for the solution Find μ CHECK Click here...
10.Hello, I need help with this question, please very explicit and clear answers step by step....
10.Hello, I need help with this question, please very explicit
and clear answers step by step.
10. Let {Nt} t 0 be a Poisson process with parameter ?. It shows that conditional on a jump occurring in the interval [s, s t], the moment in which the jump occurred is evenly distributed in that interval.
SUMMARY OUTPUT Regression Statistics Multiple R 0.818616296 R Squa...
SUMMARY OUTPUT Regression Statistics Multiple R 0.818616296 R Square 0.67013264 Adjusted R Square 0.658351663 Standard Error 9.16867179 Observations 30 ANOVA df SS MS F Significance F Regression 1 4781.80995 4781.80995 56.8826 3.2455E-08 Residual 28 2353.807187 84.06454239 Total 29 7135.617137 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 28.21496731 3.739591617 7.544932763 3.22E-08 20.55476114 35.87517349 Dividend 2.367177613 0.313863719 7.542055589 3.25E-08 1.724256931 3.010098296 c. You run a regression analysis using Data Analysis to answer the following question: Is stock selling...
Consider a multiple regression model of the dependent variable y on independent variables x1, x2, and x3: Using data with n = 12 observations for each of the variables, a researcher obtains the follo...
Consider a multiple regression model of the dependent variable y on independent variables x1, x2, and x3: Using data with n = 12 observations for each of the variables, a researcher obtains the following estimated regression equation for the above model y0.5216 + 1.2419x1 + 0.3049x2 - 0.0217x3 The standard error of estimate for this equation is s0.6489 The table below gives the values for the independent and dependent variables and their corresponding predicted values, residuals, and leverage Predicted Value...
Hello, I have computed a regression model where the dependent variable is "earn" as in how...
Hello, I have computed a regression model where the dependent variable is "earn" as in how much money the student will earn after college. My independent variables include "public" as in was this college public(1) or private(0), "academic ability" (a score calculated as the average score from SAT/ACT data of admitted students), "Average Cost" of tuition and "population" (of the city the college is in). Are public colleges better or private ones? SUMMARY OUTPUT Regression Statistics Multiple R 0.649 R Square...
3. In the multiple regression model shown in the previous question, which one of the following st...
3. In the multiple regression model shown in the previous question, which one of the following statements is incorrect: (b) The sum of squared residuals is the square of the length of the vector ü (c) The residual vector is orthogonal to each of the columns of X (d) The square of the length of y is equal to the square of the length of y plus the square of the length of û by the Pythagoras theorem In all...
Considering multiple linear regression models, we compute the regression of Y, an n x 1 vector, on an n x (p+1) full rank matrix X. As usual, H = X(XT X)-1 XT is the hat matrix with elements hij at the ith row and jth column. The residual is e; = yi - Ýi. (a) (7 points) Let Y be an n x 1 vector with 1 as its first element and Os elsewhere. Show that the elements of the...
Considering multiple linear regression models, we compute the regression of Y, an n x 1 vector, on an n x (p+1) full rank matrix X. As usual, H = X(XT X)-1 XT is the hat matrix with elements hij at the ith row and jth column. The residual is e; = yi - Ýi. (a) (7 points) Let Y be an n x 1 vector with 1 as its first element and Os elsewhere. Show that the elements of the...
linear statistics modeling and regression
2) Suppose you have multiple regression set up Ynxi XnxpBpxi Sxl and f ~ N(0nx1, σ21.). P Po X(X,X)-X, be the projection matrix on the column space of X. a) Show residual vector, e = (1,-P)Y. Here e is the vector of residuals ei S. b) Show that the variance of e, is 1 - Pi, where P is the i, j th entry of the matrix P c) Show that the sample covariance of...
Figure 2 Regression Output SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.921261 0.848722 0.8055 0.711125 10 ANOVA Significance MS 0.001347 Regression Residual Total 19.86011 9.930053 19.63628 3.539894 0.505699 23.4 Standard Error Upper 95% Coefficients 0.20018 2.211198 0.07185 tStat P-value Lower 95% Intercept Size (cubic Metres) Weight (00's kg 2.19481 1.794453 0.676122 3.270412 0.013667 0.612423 3.809974 0.47295 0.329255 0.84353 -0.23731 0.819212 0.169626 0.42356 0.684594 (a)Based on the above regression output, interpret the regression coefficients...
Hello I really need help with my probability and
statistics homework. Can you explain step by step how you got the
answer. thank you very much
Discrete Random Variable random variable X takes on the values according to the following probability chart 4 2c 3c 4c 3c 2c 4 Find C so that this is a probability distribution. CHECK Click here for the solution Find DF(2; X) DF(2, X) CHECK Click here for the solution Find μ CHECK Click here...
10.Hello, I need help with this question, please very explicit
and clear answers step by step.
10. Let {Nt} t 0 be a Poisson process with parameter ?. It shows that conditional on a jump occurring in the interval [s, s t], the moment in which the jump occurred is evenly distributed in that interval.
Consider a multiple regression model of the dependent variable y on independent variables x1, x2, and x3: Using data with n = 12 observations for each of the variables, a researcher obtains the following estimated regression equation for the above model y0.5216 + 1.2419x1 + 0.3049x2 - 0.0217x3 The standard error of estimate for this equation is s0.6489 The table below gives the values for the independent and dependent variables and their corresponding predicted values, residuals, and leverage Predicted Value...
3. In the multiple regression model shown in the previous question, which one of the following statements is incorrect: (b) The sum of squared residuals is the square of the length of the vector ü (c) The residual vector is orthogonal to each of the columns of X (d) The square of the length of y is equal to the square of the length of y plus the square of the length of û by the Pythagoras theorem In all...
Most questions answered within 3 hours.
-
Consider the prisoners’ dilemma we discussed in class, with the
following twist. If both prisoners choose...
asked 1 second ago -
The length of a pencil is measured to be 10.00 cm with a ruler.
What is...
asked 11 minutes ago -
A 120 cm^3 box contains helium at a pressure of 1.80 atm and a
temperature of...
asked 17 minutes ago -
Given that Kb for the weak base analine is 3.8 X
10-10, which of the following...
asked 19 minutes ago -
A uniform, solid sphere of radius 4.50 cm and mass 4.50 kg
starts with a purely...
asked 16 minutes ago -
A sniper fires a rifle bullet into a gasoline tank, making a
hole 51.0 m below...
asked 19 minutes ago -
The US Census Bureau gathered data regarding yearly gas sales
for residents of different states. Wyoming...
asked 39 minutes ago -
A person in a casino decides to play blackjack until he loses a
game, but he...
asked 43 minutes ago -
mode field diameter (MFD) is an important parameter in
characterizing single mode fibre properties which takes...
asked 34 minutes ago -
Question 4: What is the significance of those strange
“36.79%” and “63.21%” numbers the procedure? That...
asked 39 minutes ago -
Rules of implementation!:
You may NOT modify any of the files except Expression.java in
ANY way....
asked 41 minutes ago -
Arbitration of disputes under the purview of "lemon laws" under
state statute is:
not required by...
asked 55 minutes ago