Alpha refers to where Type I error is which is similar to the significance level is made. For instance, setting the alpha at .05 will signal that researcher is unwilling to take any big risk. Such an action of setting the alpha at .05 makes it nearly impossible to reject the null hypothesis by means of hypothesis testing except when it is on the extreme. When alpha (α) =0.05 its means that P (type I error) = 0.05, therefore rejecting Ho reason being that Ho true is 0.05.
In simple terms, we determine the dissimilarity between the null hypothesis and the results of the experiment. The researcher moves on to compute the probability of a difference, whether large or small. After finding the probability, the researcher compares it to the significance level. In the event that the probability gotten is either equal or less than the significance level, the researcher rejects the null hypothesis set from the start of the experiment. That means that the outcome of the experiment are statistically significant, showing a high chance of causal relationship among the variables.
Question two …show more content…
This means that the mean score of the group watching the film and those that did not watch the movie will be statistically equal on the questionnaire. On the other hand, my alternate hypothesis is that watching a film on institutionalization will change the students’ attitudes about chronically mentally ill patients. The alternative hypothesis means that the mean score of both the group watching the film and those that did not watch the film will be statistically