Course review : CH225

CH225: Data Analysis for Chemists

~ by Ajinkya Dhepe

Disclaimer: The content of this page are opinions expressed by individual students. The information provided is for guidance purposes. Use the information at your own risk.

Credits

6

During which semester & year you took the course ?

Autumn Semester 2019

Course Instructor

Prof. Anil Kumar

What grade was awarded to you?

AA

Course Difficulty (On a scale of 1 to 5)

2

Comment on the grading done by the professor in your opinion?

I feel it was quite moderate

What was the Attendance Policy?

No DX enforced but attendance contributes to grade

Pre-Requisites?

None

This Course evaluation comprises of?

In-Class Quizzes, Mid-Sem, End-Sem

Class Quizzes (15%), Attendance (5%), Mid-sem (30%), End-sem (50%)

What are the topics covered in the course?

The role of statistics, Graphical and numerical methods for describing and summarizing data, Probability, Bayes’ Theorem, Random Variables, Discrete Random Variables, Jointly Distributed Random Variables, Degrees of Freedom, Expectation of Random Variables, Expected Value of sums of Random Variables, Variance and Covariance of Random Variables, Binomial Random Variables, Hypergeometric Random Variables, Poisson Random Variables, Negative Binomial Distribution, Geometric Distribution, Normal Random Variables, Sampling Statistics, Distribution of Sample Mean (Z distribution), Interval Estimator, Sampling Proportions, Lower and Upper Bound Confidence Intervals, t – distribution, chi – squared distribution, Prediction Intervals, Testing statistical hypotheses, Tests concerning two populations, Simple Linear Regression and Correlation, Annova, F-distributions, One factor Annova, Two factor Annova

How were the Lectures for this course?

The overall content covered in the course is easily understandable and the content of the lectures can also be easily grasped. The professor does indulge in some digression and gives some fascinating facts and other general knowledge which is quite helpful to us in the long run (it isn’t quite helpful for the course though). He explains the fundamental concepts very well and goes through each topic at least twice. Also the analysis of the data done in the end is something which was not given in slides and is explained nicely in the lectures. There is 5% weightage for attendance which is taken through the Safe App. I highly recommend going to the lectures on time as the professor tells you to mark the attendance as soon as the class starts and any other time stamps found are marked absent.

How were the Exams for this course?

The quizzes are conducted during a fixed day every week on the Safe App. The quizzes are very easy and generally based on the topics covered in the last week. The questions are mostly multiple choice or numerical. One thorough revision of the slides can easily give a perfect score in each quiz. The mid-sem and end-sem exams are written and have numericals and proofs and many thought provoking questions, including questions of interpretation of the data analysed. They are of moderate difficulty and a deep understanding in the course, especially the various kinds of distributions and linear regression will result in a good score in both exams.

How are the Assignments & Projects for this course?

No Assignments or Projects given. Tutorials were conducted within the lecture hours but did not contribute to any separate weightage towards the grading.

Any tips for the junta to perform well in the course?

The course isn’t difficult and one can easily score a decent grade with a good go-through of slides and by solving tutorial problems and previous years’ papers. Problems in the reference book can be solved for better practice.

References used in this course:

Sheldon M Ross- Introductory Statistics (It’s a great book for solving problems for thorough preparation)

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