Standard Multiple Regression performs standard regression analysis for
the continuous dependent variable on the continuous independent variables.
Both standard regression and regression through the origin (intercept=0)
can be computed. Predicted and residual values can be computed as an option.

For deployed data sets, the previously estimated regression equation will
be applied to the data.

**General**

**Detail of
computed results reported**. Specifies the detail of computed
results reported in the results. If Comprehensive is selected, partial
correlations and redundancy statistics are reported; if All results are
requested the current sweep matrix, and the covariances of regression
coefficients are computed. This parameter also determines the detail of
residual statistics that are computed (see the Residual analysis parameter).

**MD Deletion**.
Specifies the missing data can be deleted Casewise, Pairwise, or missing
data can be substituted by the means for the respective variables.

**Intercept**. You can include the intercept
in the regression analysis (select Intercept included) or force the regression
line through the origin ((intercept forced to zero, regression through
the origin; select Set to zero).

**Tolerance
(for matrix inversion)**. Specifies the minimum tolerance value
for matrix inversion (for detecting matrix singularity). The tolerance
of a variable is defined as 1 minus the squared multiple correlation of
the variable with all other independent (predictor) variables in the regression
equation. The smaller the tolerance of a variable, the more redundant
is its contribution to the regression.

**Computes
residual statistics**. Computes predicted and residual statistics
for each case. If All results are requested (for the Level-of-detail)
the Durbin-Watson statistic for the residuals, histograms, normal probability
plots, and other plots are also reported.

**p for highlighting
results**. Specifies the default p-value for highlighting is
.05; significant predictors with p less than or equal this value will
be shown in the highlight color in the results spreadsheets.

**Generate
datasource, if N for input less than**. Generates a data source
for further analyses with other Data Miner nodes if the input data source
has fewer than k observations, as specified in this edit field; note that
parameter k (number of observations) will be evaluated against the number
of observations in the input data source, not the number of valid or selected
observations.

**Deployment. **Deployment is
available if the Statistica installation is licensed for this feature.

**Generates
C/C++ code**. Generates C/C++ code for deployment of predictive
model.

**Generates SVB code**. Generates Statistica Visual
Basic code for deployment of predictive model.

**Generates
PMML code**. Generates PMML (Predictive Models Markup Language)
code for deployment of predictive model. This code can be used via the
Rapid Deployment options to efficiently compute predictions for (score)
large data sets.