Summary SPSS Guideline and Hypotheses Testing for Regressions
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Module
New venture creation and growth
Institution
Tilburg University (UVT)
Book
Statistical Methods for Business and Economics
The document is an SPSS guideline on obtaining the covariance, correlation, confidence intervals, reading the ANOVA table, the coefficients table, interaction terms, dummy variables, and testing the model assumptions. Additionally, I provided a summary of when to use what test and when to reject th...
SPSS Guidelines and Hypothesis Tests
SPSS Guideline
Obtaining the Covariance and Correlation
- Analyze → Correlate → Bivariate
- Drag your variables in the "Variables Box"
- For Covariance:
- Options → Cross-product deviations and covariance
- Click OK
- Read from the first variable in the table the covariance and correlation on the right in the
table
95% Confidence Intervals
- Analyze → Regression → Linear
- Determine the dependent variable and the independent variable(s)
- Click "Statistics" → "Confidence Intervals"
- Set Level
- Click "Continue" and "Ok"
Reading the ANOVA table
Source Sum of Degrees of Mean Square F-value P-value
Squares Freedom (SPSS will
state Sig.
which is the
P-value)
Regression SSR x x x x
Residual SSE x x
Total SST
Reading the Coefficients table
Variable Unstandardized Standard Standardize t-value P-value
B Error d (SPSS will
Coefficients state Sig.
which is the
P-value)
Constant x x x x x
B₁ Regression x x x x
Coefficient of
B₁
B₂ Regression x x x x
Coefficient of
B₂
, Prediction Intervals and Confidence Intervals
- For a certain value of a variable
- Type the value of the variable under the last observation
- Analyze → Regression → Linear → Determine variables
- Click "Save" and
- Tick "Unstandardized" under "Predicted Values"
- Tick "Mean" and "Individual" under "Prediction intervals"
- Set CI to 95%
- Click "Continue" and "Ok" In data view you can see the interval
Definitions:
Mean Confidence Interval = LMCI and UMCI
Individual Confidence Interval = LICI and UICI
Directly Finding the Partial F-Test Statistic Value
- Analyze → Regression → Linear
- Determine the dependent variable and the independent variable(s) of the full model
- Click "Next"
- Drag the variables which are not in the reduced model in "Block 2 of 2"
- Select as method "Remove"
- Click "Statistics" → Tick "R squared change"
Model 1 = Full Model and Model 2 = Reduced Model
Squared and Interaction Terms
For Square Term:
- Transform → Compute Variable → Name Variable
- Numeric Expression type: Variable₁ * Variable₁
For Interaction Term:
- Transform → Compute Variable → Name Variable
- Numeric Expression type: Variable₁ * Variable₂
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