Hypothesis: A higher proportion of those who were interested in politics voted in the local elections than those who were not interested in politics.

weight off.
fre vote.
RECODE vote (1=1)(2=0) into vote_2cat.
VARIABLE LABELS vote_2cat ‘Voted or not on the last national election?’.
VALUE LABELS vote_2cat 1’voted’ 0’did not vote’. fre vote vote_2cat.

fre POLINTR.
RECODE POLINTR (1 2=1)(3 4=0) into POLINTR_2cat.
VARIABLE LABELS POLINTR_2cat ‘Interested or not in politics’.
VALUE LABELS POLINTR_2cat 1’interested’ 0’not interested’.
fre POLINTR POLINTR_2cat.

LOGISTIC REGRESSION vote_2cat WITH POLINTR_2cat.

*In order to get the data for creating the graph you write the following:.
CROSSTABS vote_2cat BY POLINTR_2cat /cells=column.

1-voted
0-did not vote
0-not interested
1-interested

Exp(b1): The odds of voting among those who are interested in politics are 8.345 times as high as among those who are not interested in politics.

Exp(b0): The odds of voting among those who are not interested in politics are 1.870.

Exp(b0)*Exp(b1)=The odds of voting among those who are interested in politics are (8.345*1.870).

b1: The logarithm of the odds for voting among those who are interested in politics are by 2.122 higher than among those who are not interested in politics.

b0: The logarithm of the odds for voting among those who are not interested in politics is 0.626.

Conclusion: The result support our hypothesis, since the p value is higher than 0,05 and the odds for voting among those who are interested in politics are higher among those who are interested in politics. (Exp(B) for b1 is 8.345).

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