Hypothesis: Students who are satisfied with the content of modules of the MSc programme know what to do to pass the programme.
Question AF: How are you satisfied with the content of modules of the MSc Programme?
Question AP: I know what I need to do to pass my MSc?
We would like to know whether the hypothesis in this case holds or not using an appropriate analytical method. The two questions can be categorized into categorical data since they have directions towards nominal and ordinal. Chi-square is thus the suitable test to use in testing the hypothesis.
One can argue that there is no a noticeable relationship between being satisfied with the contents of the MSc module and knowing how to pass the MSc. Therefore it might not be a good hypothesis at a glance since the two questions are not relevant enough. I would hence not like to change the hypothesis and questions given that I had the chance to do so.
In this case, the independent variable is how are you satisfied with the content of modules of the MSc programme, which are identified in question AF. The second variable is I know what I need to do to pass my MSc. Since the level of I know is affected by the first variable, it is the dependent variable whose values are given by the answers of question AP. A first reason for this it is the unexpected relationships that need to be tested to ensure the hypothesis and not the significant ones
The Chi-square value is 19.778, P = 0.071. The observed frequency and expected frequency have obvious phenomena since P< 0.05. This therefore shows that there is a statistically significant relationship between being satisfied with the contents of the MSc module and knowing how to pass MSc. Both values of the variables have the same measurement which is the ratio. The design here is not relevant whether it is within or between since the variables are not categorical
Also, the widest range of tests is possible. In situations of data being parametric, even regressions (which are very powerful tests) can be run. This is the reason as to why I would not change my hypothesis. One needs to use descriptive statistics if the data from the questions are parametric.
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 19.778a 12 .071
Likelihood Ratio 19.318 12 .081
N of Valid Cases 209
a. 11 cells (55.0%) have expected count less than 5. The minimum expected count is .54.
Result: The chi-square value is 19.778 and P is 0.071 which is lower than 0.005, hence this hypothesis is available. The question AF which is how satisfied are you with the contents of the MSc module and question AP which is I know how to pass my MSc are relevant to each other.
Cleared data:
This table below tells us to understand that mean is 2.19, minimum is 1 and the maximum is 3.
Descriptive Statistics
N Range Minimum Maximum Mean Std. Deviation Variance Skewness
Statistic Statistic Statistic Statistic Statistic Statistic Statistic Statistic Std. Error
How satisfied are you with the content of the MSc module 209 2 1 3 2.19 .564 .318 -1.745 .092
Valid N (listwise) 209
From the table below on I know what I need to do to pass my MSc, the minimum is 1 and the maximum is 6. The standard deviation is 1.09.
Descriptive Statistics
N Range Minimum Maximum Mean Std. Deviation Variance Skewness
Statistic Statistic Statistic Statistic Statistic Statistic Statistic Statistic Std. Error
I know what I need to do to pass my MSc 209 5 1 6 3.15 1.09 1.1881 .798 .216
Valid N (listwise) 209
