SPSS Correlation and Multiple Linear Regression Analysis

Estimating countries' life expectancy by considering their GDP per capita, adult mortality rate, and health expenditure per capita.

Correlation Analysis

Steps to Find Correlation Scores and Significance Values in SPSS

1. Open SPSS and load your dataset.
2. Correlation Scores:
   • Go to Analyze > Correlate > Bivariate....
   • Select the variables you want to correlate (e.g., Adult Mortality and Life Expectancy).
   • Ensure that the Pearson checkbox is selected.
   • Click OK.
3. Significance Values:
   • The output window will display the correlation coefficients (r) and the significance values (p).
   • Check the p-values to determine statistical significance. If p < 0.05, the correlation is statistically significant.
4. Correlation Directions:
   • Look at the sign of the correlation coefficients. A negative sign indicates a negative direction, and a positive sign indicates a positive direction.

Multiple Linear Regression

Steps to Perform Multiple Linear Regression in SPSS

1. Open SPSS and load your dataset.
2. Multiple Linear Regression:
   • Go to Analyze > Regression > Linear....
   • Select Life Expectancy as the dependent variable.
   • Select Adult Mortality, Percentage Expenditure, and GDP as the independent variables.
   • Click OK.
3. Interpret the Output:
   • R-Square: In the Model Summary table, check the R-Square value. This represents the percentage of variance explained by the model.
   • Significant Variables & Coefficients:
     • In the Coefficients table, check the Sig. column to see the p-values for each independent variable.
     • Look at the B column under Unstandardized Coefficients to see the impact of each variable on the dependent variable.
     • Look at the Beta column under Standardized Coefficients to see the standardized impact.