GradingCSE167F20

From Immersive Visualization Lab Wiki
Revision as of 20:48, 15 December 2020 by Jschulze (Talk | contribs)

(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to: navigation, search

Contents

Grading

  • Projects 1-4: 20% each
  • Final exam: 20%

There will be no assignment or indication of letter grades corresponding to scores on the individual exams and homework projects. The final grade depends on a weighted average of all the scores. The following grading key will be used:

Final Score Letter Grade
100+ A+
95+ A
90+ A-
85+ B+
80+ B
75+ B-
70+ C+
65+ C
60+ C-
55+ D+
50+ D
45+ D-
<45 F

For undergraduate students with the P/NP option: A pass (P) grade will be given for an average score of 60 or higher.

For graduate students with the S/U option: A satisfactory (S) grade will be given for an average score of 75 or higher.

Late Submission Policy for Projects

If you miss the submission deadline you have a second opportunity to submit within 7 days from the original due date. However, there will be a late penalty: you will get only 75% of the score you would have received for a timely submission.

Tips for Final Exam Preparation

  • Review the course slides, available as PDF files on the class schedule.
  • Solve previous CSE 167 exams (find links on the current and previous course schedules).
  • Read relevant chapters in the textbooks to deepen your knowledge of the material.
  • Get lots of sleep during the night before the exam.

Final Exam Rules

It is important for you to understand the concepts covered in class, as well as the math. You will need to know how to multiply matrices of any dimensionality with one another, but all calculations will be simple enough to do without a calculator. The same is true for matrix-vector multiplications, scalar products, dot products, vector magnitude, and the rest of the linear algebra used in the lectures.

Academic Integrity

This course implements UCSD's integrity guidelines.