Output - Aster Analytics

Teradata AsterĀ® Analytics Foundation User GuideUpdate 2

Product
Aster Analytics
Release Number
7.00.02
Published
September 2017
Language
English (United States)
Last Update
2018-04-17
dita:mapPath
uce1497542673292.ditamap
dita:ditavalPath
AA-notempfilter_pdf_output.ditaval
dita:id
B700-1022
lifecycle
previous
Product Category
Software

The output table shows the model statistics.

GLM Example 1 Model Statistics
predictor estimate std_error z_score p_value significance
(Intercept) 1.07751 2.92076 0.368914 0.712192  
masters.no 2.21655 1.01999 2.17311 0.0297719 *
gpa -0.113935 0.802573 -0.141962 0.88711  
stats.Novice 0.0406848 1.11567 0.0364667 0.97091  
stats.Beginner 0.526618 1.2229 0.430631 0.666736  
programming.Beginner -1.76976 1.069 -1.65553 0.0978177 .
programming.Novice -0.98035 1.14004 -0.859923 0.389831  
ITERATIONS # 4 0 0 0 Number of Fisher Scoring iterations
ROWS # 40 0 0 0 Number of rows
Residual deviance 38.9038 0 0 0 on 33 degrees of freedom
Pearson goodness of fit 37.7905 0 0 0 on 33 degrees of freedom
AIC 52.9038 0 0 0 Akaike information criterion
BIC 64.726 0 0 0 Bayesian information criterion
Wald Test 9.89642 0 0 0.19452  
Dispersion parameter 1 0 0 0 Taken to be 1 for BINOMIAL and POISSON.

For categorical variables, the model selects a reference category. In this example, the Advanced category was used as a reference for the stats variable.

The query below returns the output shown in the following table:

SELECT * FROM glm_admissions_model ORDER BY attribute;

The example uses stepwise selection only to show which predictors are included in the regression. The predicted output models are not used in any prediction function. The following table is only a collection of the coefficients estimated in each step.

GLM Example 1 Output Table (Columns 1-4)
attribute predictor category estimate
-1 Loglik   -19.4519
0 (Intercept)   1.0775
1 masters yes  
2 masters no 2.21655
3 gpa   -0.113935
4 stats Advanced  
5 stats Novice 0.0406848
6 stats Beginner 0.526618
7 programming Advanced  
8 programming Beginner -1.76976
9 programming Novice -0.98035
GLM Example 1 Output Table (Columns 5-8)
std_err z_score p_value significance
40 6 0  
2.92076 0.368914 0.712192  
1.01999 2.17311 0.0297719 *
0.802573 -0.141962 0.88711  
1.11567 0.0364667 0.97091  
1.2229 0.430631 0.666736  
1.069 -1.65553 0.0978177 .
1.14004 -0.859923 0.389831