EBA 2910 Mathematics for business analytics - Exam Preparation June 2020
How to write the exam
- The exam should be handwritten and delivered as one PDF file.
- It is almost always best to write on paper and scan. Handwritten notes from iPad or similar devices are also ok.
- Be prepared and test that you can scan well before the exam. Remember top/bottom margins.
How to prepare for the exam
- To prepare, I recommend you to do former final exams (MET11807/MET11803). I also recommend that you look at midterm exams (multiple choice) and Problem set 1-31.
- Many exam problems will be of a similar type as former final exam problems. Others may be of a type similar to midterm exams problems or problems from Problem Sets.
- A significant part of the final exam will be on topics taught in the spring semester.
- Below is a list of topics from the autumn semester that I find important. Many of these topics have been used quite a
lot in the spring semester:
- Derivatives and application of the derivative (max/min, increasing/decreasing, convex/concave, tangents)
- Functions and graphs (lines, parabolas, hyperbolas, circles/ellipses, asymptotes, inverse functions, limits)
- Present value computations (discrete and continuous time)
- When preparing, you should of course solve many problems completely.
- I think it is a very useful to look at many more problems (that you don't have time to solve completely) and check that you know, in principle, how to solve them.
How to write your solutions
- You should give reasons for your answers. A correct answer on its own give no score.
- You should practise giving reasons for your answers. It is not necessary to give references, but you write your
reasons based on theory in the course. Below are some examples:
- We compute the determinant of A using cofactor expansion along the first row: det(A) = ... (computation) = (answer)
- We use the substitution u = ... , du = ... (u') dx to solve the integral: ... (computation)
- Where you should give graphs/figures, they should be drawn by hand based on what you know, not made by computer.