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SPSS command 2 commands
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SPSS Deeltentamen 2Investigating Influence variabels
A: SETTING UP HYPOTHESES
Vraag A1: What would be the correct null and Alternative Hypoteses?
A null hypothesis is always that there is no (significant) difference.
An alternative hypothesis is always that there is a difference. In this case, you expect men to
have a higher satisfaction than women, so it is a one-sided alternative hypothesis.
Vraag A2: Are we testing our hypothesis one-sided or two-sided
A hypothesis is not always one-sided or always two-sided, it depends on your hypothesis.
If you think that there is a general difference (so men are happier OR women are happier),
then it is two-sided.
In this case you give a direction to your hypothesis, you expect a specific outcome (men are
happier than women, not the other way around), so it is a one-sided hypothesis.
Vraag A3: look at the descriptives of life statisfaction for men and woman separately. What are
their means and standard deviations?
Data > Split File. Select “organize output by groups” and then choose "Groups based on >
Gender"
Then go to Analyze > Descriptives Statistics > Descriptives and look at the descriptive
statistics.
! IPV kiezen voor geslacht kies je voor satisfaction.
B: TESTING HYPOTHES BY USING A T-TEST (COMPARING TWO MEANS)
Vraag B1: Are we going to run a dependent or an independent t-test?
The two groups (men and women) do not influence each other. It's also not the same group
over time. Since the two groups are not related, it's an independent t-test you're going to
use.
It does not matter whether the two variables (gender and satisfaction) are related! Because
you are going to test whether they influence each other or not.
Vraag B2: Now we are going to run the independent t-Test.
First: Make sure you turn off the ‘split file’. Go back to Data > Split file and then select
“analyze all cases, do not create groups”, and press paste and run the syntax code.
Next: go to Analyze > Compare Means > Independent-Samples T-Test.
As the test variable, you choose Satisfaction.
As the grouping variable, you select Gender.
Then press ‘define groups’. Here you give the two values of the grouping variable. If you look
at the ‘Variable view’ and then the values of Gender. You’ll see that men have the value 1
and women have the value 2. So in ‘Define groups’ you have to fill in a 1 and a 2.
Then press paste and run the syntax code.
Vraag B3: look at the P-value which conclusion can you draw about the null hypotheses?
We will only look in the line “equal variances assumed”
You can see that the reported 2-sided P-value is lower than 0.001. We have to divide the
reported P-value by 2, since we conduct a one-tailed hypothesis test.
In any case, the P-value is lower than the alpha (0.05). Therefore the effect is significant. This
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