Question

In: Statistics and Probability

We have seen that adding useless predictors to a regression model will increase R2. Here, let's...

We have seen that adding useless predictors to a regression model will increase R2. Here, let's examine what our inference methods say if the predictors are in fact useless. Suppose the true/pop fit is y = 1,(i.e., no x at all), and so a possible sample from the population could be the following:


set.seed(123)

n = 20

y = 1 + rnorm(n,0,1)


a) Write code to make data on 10 useless predictors (and no useful predictors) each from unif(-1,+1), fit the model y = alpha + beta1 x1 + ... + beta10 x10, perform the test of model utility, and perform t-tests on each of the 10 coefficients to see if they are zero. Show/turn-in your R code.


b) According to the F-test of model utility, are any of the predictors useful at alpha = 0.1?


c) According to the t-tests, are any of the predictors useful at alpha = 0.1?

Solutions

Expert Solution


Related Solutions

Now that we have seen Euler in action, let's return to examining the content of the...
Now that we have seen Euler in action, let's return to examining the content of the M-File Euler.m. We have already explained the first line, where we defined the parameters our function takes. To see the meaning behind the third and fourth lines, type: >> x = zeros(10,1); y = zeros(10,1); [x,y] Thus we can see that the third and fourth lines of our M-File zero out the contents of our arrays x and y before we begin. Now, you'll...
In a multiple linear regression model with 2 predictors (X1and X2),                               &n
In a multiple linear regression model with 2 predictors (X1and X2),                                TRUE     or     FALSE In a multiple linear regression model with 2 predictors (X1and X2), then SSR(X1)+SSR(X2|X1) = SSTO–SSE(X1,X2)   TRUE     or    FALSE In a multiple linear regression model with 2 predictors (X1and X2), if X1and X2are uncorrelated, SSR(X1) = SSR(X1|X2).       TRUE     or    FALSE In a multiple linear regression model with 2 predictors (X1and X2), SSR(X1) + SSR(X2|X1) = SSR(X2) + SSR(X1|X2).       TRUE     or    FALSE In simple linear regression, then (X’X)-1is  2x2.    TRUE    or     FALSE In simple linear regression, the hat-matrix is 2x2.    TRUE    or     FALSE
In Nonlinear regression analysis, if we have a data set and if we need to model...
In Nonlinear regression analysis, if we have a data set and if we need to model nonlinear, once we enter the data either in R or SPSS software we observe the results, but we cannot see the exact equation as we can write for linear regression.as an example if we want to see the relationship between Sales the response variable and the advertising budget for TV media and News paper we have to independent variables,once the data we entered how...
We have seen increase in prices of various goods for example Sugar during this period of...
We have seen increase in prices of various goods for example Sugar during this period of COVID-19 pandemic. Suggest the possible measures that should be taken as far as International Trade is concerned
As we get started here, let's think about experiences you have had working with individuals from...
As we get started here, let's think about experiences you have had working with individuals from backgrounds different from yours. How would these experiences translate into working within a healthcare environment and with patients?
Which of the following is a false statement? A. In a multiple regression model, adding more...
Which of the following is a false statement? A. In a multiple regression model, adding more explanatory variables to the model is always a good idea because R2 always increases as more explanatory variables are added to the model. B. In a multiple regression model, the explanatory variables, or X variables, are often correlated. C. In a multiple regression model, the goals are to describe the relationship between Y and two or more X variables and to predict the value...
Let's say we are planning on adding a very large modern sign to attract customers to...
Let's say we are planning on adding a very large modern sign to attract customers to our marijuana and tattoo shop that we run just north of Denver. We've completed a ton of market analysis and we are fairly confident that the sign will increase sales by $50,000 per year for the first two years, and then we think it will result in an increase of $35,000 per year for the next four years. The margins we earn on our...
We give JMP output of regression analysis. Above output we give the regression model and the...
We give JMP output of regression analysis. Above output we give the regression model and the number of observations, n, used to perform the regression analysis under consideration. Using the model, sample size n, and output: Model: y = β0+ β1x1+ β2x2+ β3x3+ ε       Sample size: n = 30 Summary of Fit RSquare 0.956255 RSquare Adj 0.951207 Root Mean Square Error 0.240340 Mean of Response 8.382667 Observations (or Sum Wgts) 30 Analysis of Variance Source df Sum of Squares Mean Square...
We give JMP output of regression analysis. Above output we give the regression model and the...
We give JMP output of regression analysis. Above output we give the regression model and the number of observations, n, used to perform the regression analysis under consideration. Using the model, sample size n, and output: Model: y = β0 + β1x1 + β2x2 + β3x3 + ε       Sample size: n = 30 Summary of Fit RSquare 0.987331 RSquare Adj 0.985869 Root Mean Square Error 0.240749 Mean of Response 8.382667 Observations (or Sum Wgts) 30 Analysis of Variance Source df Sum...
When we estimate a linear multiple regression model (including a linear simple regression model), it appears...
When we estimate a linear multiple regression model (including a linear simple regression model), it appears that the calculation of the coefficient of determination, R2, for this model can be accomplished by using the squared sample correlation coefficient between the original values and the predicted values of the dependent variable of this model. Is this statement true? If yes, why? If not, why not? Please use either matrix algebra or algebra to support your reasoning.
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT