Hypothesis: Gender moderates the relationship between believe in God and satisfaction with your life.

  1. Check the outliers: Check if there are any extreme values.
  2. Create inter variable: You have to create a new variable. We usually name it as inter: gender multiplied by religion. Check your new variable in the Variable View window and label it.
  3. Run the regression: Dependent variable: satisfaction with your life Independent variables: religion, gender and inter.
  4. Interpret the results: The interpretation depends on what you coded 0 and 1. Before the interpretation make sure that you know how the values are coded. Best is if you write it down on a paper or on a note that: 0-does not believe in God , 1 – believe in God, 0 – female, 1 – male

0-does not believe in God, 1 – believe in God, 0 – female, 1 – male

b0: The average level of satisfaction with life for women who do not believe in God is 6.968.

b1: Women who believe in God score 0.059 less than women who do not believe in God. This is statistically not significant, so there is a 7,9% probability that we got this result by chance. (p=0,079)

b2: Men who do not believe in God score 0.142 less than women who do not believe in God. (p<0,05)

b3: Among those who believe in God the effect of gender is 0.107 higher than among those who do not believe in God. We could also say that among men the effect of religion is 0.107 higher than among women. (p<0,05)

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