Summary Statistics for Premasters (800547-B-6) APA templates
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Course
Statistics for Premasters CIS (800547B6)
Institution
Tilburg University (UVT)
In this summary, I have created step-by-step APA templates for all the tests you need to perform during the Statistics for Premasters CIS (800547-B-6) course. You can use these templates during the exam and copy paste them. Of course, you have to change the text based on the assignment.
STATISTICS FOR PREMASTERS CIS (800547-B-6) – APA TEMPLATES FOR ALL TESTS
Instructions
In this document I listed the APA templates of all the tests you need for the exam of the
course Statistics for Premasters CIS (800547-B-6). This course is very similar to the course
Statistiek voor Bachelors CIW (800551-B-6) but with a few small differences! So you can use
these templates for that course as well, but at your own risk.
I listed the templates in order of the PU’s. You can copy and paste these templates and adjust
them accordingly to the assignment. Be aware that I listed all possible steps, so only include
the steps you actually used in your answer.
- Cursive = instructions
- Grey = instructions/titles
- Normal text = you can copy this text exactly, does not need to be adjusted
- Bold = you need to adjust this text according to the information of the assignment
- Red = steps you don’t need to do, only add them when specifically asked on the exam
Good luck! 😊
, APA templates t-tests
ONE SAMPLE T-TEST
To test whether hypothesis, a one sample t-test was performed.
If a scale was used:
Dependent variable was measured with a scale consisting of X items on a X-point
Likert scale (e.g. ‘example question?’). The reliability of the scale was good, α = .xx.
If data was normally distributed:
don’t mention, only when asked on exam!
The data was normally distributed (z-score skewness = xx.xx and z-score kurtosis =
xx.xx).
If data was not normally distributed:
The data was not normally distributed (z-score skewness = xx.xx and z-score kurtosis
= xx.xx). Therefore, the p-value may not be reliable and more weight should be placed
on the bootstrapped 95% confidence interval that will be provided.
On average, the tested variable (M = xx.xx, SD = xx.xx) was lower/higher than fixed value.
This difference was/was not significant (Mdif = xx.xx, t(x) = xx.xx, p </= .xxx). The
difference represents a small/medium/large effect size, d = .xx.
If not normally distributed:
The data generalizes/does not generalize to the population as the bootstrapped 95%
confidence interval does not cross/crosses zero (95% CI [xx.xx, xx.xx]).
If normally distributed:
don’t mention 95% CI, only when asked on exam!
Therefore, it can be concluded that the hypothesis is/is not supported by the data.
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