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
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
