Page 175 - Intermediate Statistics for Dummies
P. 175
13_045206 ch08.qxd 2/1/07 10:00 AM Page 154
154
Part II: Making Predictions by Using Regression
In the case of the movie and age data, the model-building part of the Minitab
output is shown in Figure 8-2. The model-fitting part of the Minitab output
from the logistic regression analysis is in Figure 8-4. In the following sections,
you see how to use this output to build the best-fitting logistic regression
model for your data and to check the model’s fit.
Figure 8-2:
The model-
building part
Logistic Regression Table
of the movie
Odds 95% CI
and age
Coef
Z
P
SE Coef
Predictor
data’s
3.39
1.43434
Constant
4.86539
0.93
0.76
0.000
0.84
0.0499620
–3.52
–0.175745
Age
logistic
regression
output.
Finding the coefficients 0.001 Ratio Lower Upper
and making the model
After you have Minitab run a logistic regression analysis on your data, you
can find the coefficients b 0 and b 1 and put them together to form the best-
fitting logistic regression model for your data.
Figure 8-2 shows part of the Minitab output for the movie enjoyment and age
data. I call this portion of the output the model-building part of the output. (I
discuss the remaining output in the section “Checking the fit of the model.”)
The first column of numbers is labeled Coef, which stands for the coefficients
in the model. The first coefficient, b 0, is labeled Constant. The second coeffi-
cient is in the row labeled by your explanatory variable, x. (In the movie and
age data, the explanatory variable is age. This age coefficient represents the
value of b 1 in the model.)
According to the Minitab output in Figure 8-2, the value of b 0 is 4.87 and the
value of b 1 is –0.18. After you’ve determined the coefficients b 0 and b 1 from
the Minitab output to find the best-fitting S-curve for your data you put these
/ e b 0 + b x
1
two coefficients into the general logistic regression model: p = b 0 + b x . For
1
1
8
/ e . 487 - 0 . x 1 + e
the movie and age data, you get p = . x , which is the best-fitting logis-
1 + e . 487 - 01 8
tic regression model for this data set.

