Statistical Modeling I
Practical in R
Practical in R
In this practical, we will work with the Stackloss dataset (stackloss.csv). We will look at two different models and their analysis.
The data are obtained in a production process of oxidizing ammonia. The variables of interest are:
● Y : the stack loss, which is the percentage of the ingoing ammonia that escapes unab-sorbed;
● X1 : the airflow
● X2 : the cooling water inlet temperature in degrees C;
● X3 : the acid concentration in percent.
1. Fit Model 1: Yi = β0 + β1 x1,i + βx2,i + β3 x3,i + εi with εi i.~.d. N(0, σ2 )
2. Check if there are any apparent problems with the residuals;
3. Test the hypothesis regarding the overall regression by using the F test
4. Test the hypothesis regarding the parameters βj for j = 0, 1, 2, 3 by using the t tests
5. Fit Model 2: Yi = β0 + β1 x1,i + βx2,i + εi with εi i.~.d. N(0, σ2 )
6. Check if there are any apparent problems with the residuals;
7. Test the hypothesis regarding the overall regression by using the F test
8. Test the hypothesis regarding the parameters βj for j = 0, 1, 2 by using the t tests
9. Which is the best model between Model 1 and Model 2 and why?
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