University of Essex Online · CertHE Computer Science · Level 4 · Tutor: Ali Edisen
This module built the mathematical and statistical foundations required for computer science, moving from discrete mathematics through to applied statistical analysis.
Apply counting principles, permutations, and combinations to solve discrete mathematics problems.
Work with sets, universal sets, complements, and set operations, expressing solutions with clear notation.
Calculate and interpret measures of central tendency (mean, median, mode) and represent data using histograms and frequency distributions.
Identify and classify variable types correctly, and select appropriate representations and analyses for each.
State hypotheses, select appropriate statistical tests, determine sample sizes, and justify test choices.
Understand and apply non-parametric statistical methods where parametric assumptions do not hold.
Assessment in this module was practical and completed directly on the learning platform. The artefacts below are the assessed components, with the grades and tutor feedback received.
A multiple-choice individual quiz covering the early foundations of the module, including combinatorics and set theory. Completed directly on the learning platform.
"Excellent work! Keep it up!"
A discussion forum task requiring a worked solution to a set theory problem (finding the complement of set A), followed by peer responses. My post defined the universal set, explained the concept of a complement, and showed the working step by step to reach the correct answer (A' = {1,3,5,7,9,10}).
The answer was confirmed correct, and the post praised as well-structured: it defined the universal set clearly, explained what a complement means, showed working step by step, and reached a clear, correct final answer. Peer responses to other students described as excellent and specifically helpful. Areas to improve: include a Harvard reference (which was required) and mention real-world applications.
A timed online class test of ten written-answer questions spanning the full module: measures of central tendency, variable classification, histograms, frequency distributions, hypothesis testing, sample size estimation, and statistical test selection. This assessment required reasoning to be written out, in contrast to the earlier multiple-choice quiz.
Strong performance across most questions (marks of 7–9 out of 10), with correct calculations and clear working consistently noted — for example, accurate mean (5.42), median (5.4) and mode, correct frequency distribution tables, and correct test identification. One question scored lower (3/10) because the answer was submitted only as a PDF attachment with no summary in the main response, meaning the content could not be verified there.
Written using the 3 W's framework (What / So What / What Next), as recommended by the UoEO Department of Computing.
Coming into this module, I was a little rusty, as it had been a long time since I had done any statistics calculations. However, I adapted well and got the hang of it. I came to see that mastering mathematics works the same way as mastering programming: through practice. The more you practise, the more it becomes fixed in your mind, and the faster and better you get. The module covered combinatorics, sets, descriptive statistics, and non-parametric tests, assessed through an individual quiz, a discussion forum, and an end-of-module class test.
My results across the module showed an interesting contrast. I scored 100% on the Unit 2 quiz, but 73% on the End of Module Class Test. The difference came down to format: the quiz was multiple choice, whereas the final test required written answers explaining my reasoning.
I found the format of the final test a little confusing. We were allowed to submit PDFs showing how we worked out the calculations, but it had not been made clear that the full reasoning also needed to be written directly on the site. As a result, I lost some marks on one question (3/10) for submitting only a PDF attachment without a summary in the main response. Despite this, I performed well overall. The test was somewhat difficult due to the short time available, and because the questions were more complex — requiring me to apply new concepts and tools I had only recently learned in the module.
The Unit 4 discussion forum was a valuable experience. Although fairly simple, it acted as a form of peer review: I provided structured feedback to other students on their work, which the tutor noted positively.
One specific learning point was referencing. I had the problem of not including a Harvard reference in my forum post because this was very new to me — I did not know that referencing was required even in mathematics and in assessments. This was an important lesson in applying academic conventions consistently, across every subject.
I am certain I will use almost everything from this module going forward. While it is still a little unclear exactly how and where I will apply each concept, I know this knowledge will be important not only for the rest of the course, but also in day-to-day work. Going forward, I will carry two lessons in particular: to apply Harvard referencing consistently even outside written essays, and to read submission instructions carefully so that my reasoning is presented in the required format. Above all, I will keep practising — because, as with programming, practice is what makes mathematics stick.
An assessment of the skills gained or enhanced during this module, with evidence and a forward-looking action plan.
| Skill | Before | After | Evidence | Action Plan |
|---|---|---|---|---|
| Combinatorics & Set Theory | Rusty | Proficient | 100% on Unit 2 quiz; Distinction on set theory forum | Apply set logic to data structures and database design |
| Descriptive Statistics | Rusty | Competent | Correct mean, median, mode and frequency tables in class test | Apply to data analysis and reporting tasks |
| Hypothesis & Statistical Testing | None | Developing | Correct test identification and sample sizing in class test | Revisit when working with real datasets in future modules |
| Mathematical Communication | Basic | Competent | Clear step-by-step working praised in forum feedback | Always present full reasoning, not just final answers |
| Peer Review | None | Developing | Helpful, specific peer feedback noted by tutor | Continue engaging constructively in collaborative tasks |
| Submission & Referencing Discipline | None | Developing | Lessons learned: Harvard required even in maths; format matters | Read briefs carefully; reference consistently across all subjects |