Hypothesis Testing
One of the topics that I would love to eventually study the affect of attending Friday prayers at the mosque by Muslim women. I hypothesize that Muslim women who attend Friday prayers at the mosque are happier than those who do not. One of the views in Islam is that it is best for a woman to stay at home when the men attend prayers. It is also part of the religious view that a woman’s place is best in her home. However, I wonder what affect that has on a woman’s overall psychological health. It has been hypothesized in other studies that a large number of Muslim women are in fact suffering from depression because of their lack of social interaction and ability to get outside of the house.
In this study, my independent variable would be attending the Friday prayer at a mosque since it’s the variable I have control over and I can manipulate (Stangor, 2014). It will also affect my dependent variable, which is their level of depression or happiness since it depends on the independent variable.
The null hypothesis of my study is that attending Friday prayers at the mosque has no effect on happiness. Therefore, a Type I error would occur if we reject the null hypothesis and it’s actually true (Stangor, 2014). If we reject the null hypothesis in this case, it means that attending the mosque for Friday prayers does in fact have some effect on happiness. If the null hypothesis is true, then it doesn’t have an effect at all.
In a Type II error, it means I did not reject a null hypothesis that is false (Stangor, 2014). In this case, it would show that attending the mosque for Friday prayers did not have an effect on happiness when in fact it did. We use the effect size to measure the strength between two variables (Stangor, 2014). And therefore, the higher the effect size, the higher the correlation. In my study, this means that my groups were different, but only slightly. This could be in the form of showing that only a few Muslim women were happier when attending Friday prayer at the mosque.