For Models 1 – 7 the response is the Carbon Monoxide The proposed explanatory va

Question

For Models 1 – 7 the response is the Carbon Monoxide

The proposed explanatory variables are:

X1: Tar (in Milligrams)

X2: Nicotine (in Milligrams)

X3: Weight (in grams)

Model 1 Parameter Estimates

Term Estimate Std Error t Ratio Prob>|t|

Intercept 2.7432776 0.675206 4.06 0.0005*

TAR (in milligrams) 0.800976 0.05032 15.92 <.0001*

Model 2 Parameter Estimates Term Estimat

Term Estimate Std Error t Ratio Prob>|t|

Intercept 1.6646665 0.993602 1.68 0.1074

Nicotine (in milligrams) 12.395406 1.054152 11.76 <.0001*

Model 3 Parameter Estimates

Term Estimate Std Error t Ratio Prob>|t|

Intercept -11.79527 9.721626 -1.21 0.2373

Weight (in grams) 25.068198 9.980282 2.51 0.0195*

Model 4 Parameter Estimates

Term Estimate Std Error t Ratio Prob>|t|

Intercept 3.0896093 0.84377 3.66 0.0014*

TAR (in milligrams) 0.9624741 0.236663 4.07 0.0005*

Nicotine (in milligrams) -2.646272 3.787199 -0.70 0.4920

Model 5 Parameter Estimates

Term Estimate Std Error t Ratio Prob>|t|

Intercept 3.1143337 3.416204 0.91 0.3718

TAR (in milligrams) 0.8041891 0.059035 13.62 <.0001*

Weight (in grams) -0.422874 3.81299 -0.11 0.9127

Model 6 Parameter Estimates

Term Estimate Std Error t Ratio Prob>|t|

Intercept 1.6139779 4.44663 0.36 0.7201

Nicotine (in milligrams) 12.388116 1.244734 9.95 <.0001*

Weight (in grams) 0.0588255 5.023953 0.01 0.9908

Model 7 Parameter Estimates

Term Estimate Std Error t Ratio Prob>|t|

Intercept 3.20219 3.461755 0.93 0.3655

TAR (in milligrams) 0.9625739 0.242244 3.97 0.0007*

Nicotine (in milligrams) -2.631661 3.900557 -0.67 0.5072

Weight (in grams) -0.130482 3.885342 -0.03 0.9735

question 1

How many indicator variables are need to code a categorical variable with 8 levels (Example: A, B, C, D, E, F, G, H)?

question 2

Report the number of indicator variables required to code 2 different categorical variables.

The first categorical variable has 3 levels (example High, Medium, Low)

The second categorical variable has 4 levels (Example: Red, Yellow, Green, Blue)?

question 3

Assume the following population model on books:

y is the mean cost to print books.

What is the population mean difference in the cost of a hardcover book and soft cover book with the same number of pages?

question 4

Error Degrees of Freedom are calculated as n - p - 1 for multiple regression models. The p represents the number of coefficients (not including the intercept) in the estimated model.

Report the Error Degrees of Freedom for this example:

Assume 160 observations are used to estimate a first order model with 4 different numerical explanatory variables.

question 5

Error Degrees of Freedom are calculated as n - p - 1 for multiple regression models. The p represents the number of coefficients (not including the intercept) in the estimated model.

Report the Error Degrees of Freedom for this example:

Assume 160 observations are used to estimate a model with 2 numerical explanatory variables both with a linear relationship to the response and 1 categorical explanatory variable. The categorical variable has 4 levels.

question 6

Error Degrees of Freedom are calculated as n - p - 1 for multiple regression models.  The p represents the number of coefficients (not including the intercept) in the estimated model.

Assume 160 observations are used to estimate a model with 2 numerical explanatory variables both with a linear relationship to the response. In addition there is one categorical variable with 3 levels and another categorical variable with 4 levels.

Report the Error Degrees of Freedom.

question 7

Assume the prob to enter is equal to 0.05.

question 8

Assume the prob to leave is equal to 0.05.

a

plus more for a hardcover book.

Explanation / Answer

For Models 1 – 7 the response is the Carbon Monoxide

The proposed explanatory variables are:

X1: Tar (in Milligrams)

X2: Nicotine (in Milligrams)

X3: Weight (in grams)

Model 1 Parameter Estimates

Term Estimate Std Error t Ratio Prob>|t|

Intercept 2.7432776 0.675206 4.06 0.0005*

TAR (in milligrams) 0.800976 0.05032 15.92 <.0001*

Model 2 Parameter Estimates Term Estimat

Term Estimate Std Error t Ratio Prob>|t|

Intercept 1.6646665 0.993602 1.68 0.1074

Nicotine (in milligrams) 12.395406 1.054152 11.76 <.0001*

Model 3 Parameter Estimates

Term Estimate Std Error t Ratio Prob>|t|

Intercept -11.79527 9.721626 -1.21 0.2373

Weight (in grams) 25.068198 9.980282 2.51 0.0195*

Model 4 Parameter Estimates

Term Estimate Std Error t Ratio Prob>|t|

Intercept 3.0896093 0.84377 3.66 0.0014*

TAR (in milligrams) 0.9624741 0.236663 4.07 0.0005*

Nicotine (in milligrams) -2.646272 3.787199 -0.70 0.4920

Model 5 Parameter Estimates

Term Estimate Std Error t Ratio Prob>|t|

Intercept 3.1143337 3.416204 0.91 0.3718

TAR (in milligrams) 0.8041891 0.059035 13.62 <.0001*

Weight (in grams) -0.422874 3.81299 -0.11 0.9127

Model 6 Parameter Estimates

Term Estimate Std Error t Ratio Prob>|t|

Intercept 1.6139779 4.44663 0.36 0.7201

Nicotine (in milligrams) 12.388116 1.244734 9.95 <.0001*

Weight (in grams) 0.0588255 5.023953 0.01 0.9908

Model 7 Parameter Estimates

Term Estimate Std Error t Ratio Prob>|t|

Intercept 3.20219 3.461755 0.93 0.3655

TAR (in milligrams) 0.9625739 0.242244 3.97 0.0007*

Nicotine (in milligrams) -2.631661 3.900557 -0.67 0.5072

Weight (in grams) -0.130482 3.885342 -0.03 0.9735

question 1

How many indicator variables are need to code a categorical variable with 8 levels (Example: A, B, C, D, E, F, G, H)?

question 2

Report the number of indicator variables required to code 2 different categorical variables.

The first categorical variable has 3 levels (example High, Medium, Low)

The second categorical variable has 4 levels (Example: Red, Yellow, Green, Blue)?

question 3

Assume the following population model on books:

y is the mean cost to print books.

What is the population mean difference in the cost of a hardcover book and soft cover book with the same number of pages?

question 4

Error Degrees of Freedom are calculated as n - p - 1 for multiple regression models. The p represents the number of coefficients (not including the intercept) in the estimated model.

Report the Error Degrees of Freedom for this example:

Assume 160 observations are used to estimate a first order model with 4 different numerical explanatory variables.

question 5

Error Degrees of Freedom are calculated as n - p - 1 for multiple regression models. The p represents the number of coefficients (not including the intercept) in the estimated model.

Report the Error Degrees of Freedom for this example:

Assume 160 observations are used to estimate a model with 2 numerical explanatory variables both with a linear relationship to the response and 1 categorical explanatory variable. The categorical variable has 4 levels.

question 6

Error Degrees of Freedom are calculated as n - p - 1 for multiple regression models.  The p represents the number of coefficients (not including the intercept) in the estimated model.

Assume 160 observations are used to estimate a model with 2 numerical explanatory variables both with a linear relationship to the response. In addition there is one categorical variable with 3 levels and another categorical variable with 4 levels.

Report the Error Degrees of Freedom.

question 7

Assume the prob to enter is equal to 0.05.

question 8

Assume the prob to leave is equal to 0.05.

a

plus more for a hardcover book.

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