Statistics (MATH414)

This introductory course is aimed at providing a theoretical foundation in Statistics intending to build a strong quantitative orientation. The course assumes some basic knowledge of calculus and builds on the probability theory course offered in the earlier term. The course is designed to be mathematical (theoretical) in nature and many results and theorems will be derived and proved. The students are expected to learn and implement them primarily using R. Some of these will be covered through assignments.

Texts and Readings ❤️

Here are some texts that will be used in the course:

• John A Rice: Mathematical Statistics and Data Analysis, Cengage, 3rd edition
• Robert V Hogg, Joseph W McKean, and Allen T Craig: Introduction to Mathematical Statistics, 8th edition, Pearson.
• George Casella and Roger L Berger: Statistical Inference, Second Edition, Cengage
• Siva Athreya, Deepayan Sarkar, and Steve Tanner, Probability and Statistics with Examples using R, November 2024, Download here!
• R.A. Johnson, G.K. Bhattacharya, Statistics: Principles and Methods, 8th edition, Wiley.

Slide decks for lectures ❤️❤️

• Slide deck for lecture 2
• Slide deck for lecture 3
• Slide deck for lecture 4
• Slide deck for lecture 5
• Slide deck for lecture 6
• Slide deck for lecture 7
• Slide deck for lecture 8
• Slide deck for lecture 9
• Slide deck for lecture 10
• Slide deck for lecture 11
• Slide deck for lecture 12
• Slide deck for lecture 13
• Slide deck for lecture 14
• Slide deck for lecture 15
• Slide deck for lecture 16

Assignments ❤️❤️❤️

• Assignment 1
• Assignment 2
• Assignment 3
• Assignment 4

R Worksheets ❤️❤️❤️❤️

• Worksheet 1
• Worksheet 2
• Worksheet 3