10. Categorical Association: Practical 10
Chi-square Goodness of Fit Test
Imagine you expect that the answers to the statement 'Using less water makes me unhappy' (i.e. variable unhappy from the WD dataframe) are equally distributed over the #5# categories ranging from 1= Strongly disagree to 5 = Strongly agree.
You test this by performing a #X^2#-Goodness of Fit test. Is the observed frequency significantly different from the expected frequency at a significance level of #\alpha = 0.1#?
Round your answers for the #X^2#-statistic and the #p#-value to #3# decimal points.
You test this by performing a #X^2#-Goodness of Fit test. Is the observed frequency significantly different from the expected frequency at a significance level of #\alpha = 0.1#?
Round your answers for the #X^2#-statistic and the #p#-value to #3# decimal points.
The #X^2#-statistic #=# and the #p#-value #=# .
Hence, the null hypothesis be rejected.
Hence, the null hypothesis be rejected.
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