Linear regression analysis in SPSS is conducted in the following steps: 1) Select the dependent and independent variables by dragging them into the appropriate boxes. 2) Select desired statistics such as regression coefficients, Durbin-Watson, and model fit from the Statistics button. 3) The output displays descriptive statistics, the correlation between variables, regression model summaries including R square and ANOVA tables, and coefficients for the regression model with significance values.

1. Linear Regression
(Procedure and Output in SPSS )

2. Data View
Data view represents the cases/data
points for different variables. Here we
have demand as Dependent Variable
and Price as a Independent Variable.

3. Variable View
Variable view represents the
properties of all variables.
One can toggle between
data and variable view with
the shortcut ctrl + t.

4. Step 1
Running Linear Regression:
Click on the Analyze tab of
Menu bar then click
Regression option and select
Linear.

5. Step 2
Select Continuous
dependent variable and
drag it to Dependent box
and select continuous
independent variable and
drag it to Independent(s)
box.

6. Step 3
Click on Statistics button to
select desired statistics
option

7. Step 4
Select Estimates under
Regression coefficients.
Select Durbin Watson under
Residual box and select
Model fit and Descriptives.

8. Step 5
Click on Ok button to get the
Output window with Results.

9. Descriptive Statistics
This table displays the
Mean, Std. deviation and
sample size for Dependent
and Independent
variables.

10. Correlation
This table displays the
Correlation between
Dependent variable and
Independent variable with it’s
associated significance value..

11. Variable Information
This table displays the
information about
variables in the model and
variable that have been
removed from model in
the Stepwise Method

12. Regression Model Summary
This table displays the R Square Value (Goodness of
Fit for the model) with it’s associated significance
value and Std. error of the estimates.

13. ANOVA Table
This table displays the Statistic for ANOVA with its associated significance
value that test the hypothesis that the model is not having any variability
in Dependent Variable.

14. Coefficients for Regression Model
This table displays the
Coefficients for the
Regression model with it’s
T value and significance
value.

15. Developed and designed by:
Address: Mau - Chitrakoot
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