Introduction to Statistics and Computation with Data


  • Basic Information

    •
    • Instructor : Siva Athreya .
    • Email : athreya@isibang.ac.in
    • Classes : Tuesday and Thursday: 9:00-9:50 and 10:00-10:50
    • Scoring : Final Exam: 40%, Midterm Exam: 20%, Quizzes: 25%, In-class Worksheets: 10%, and Homework: 5%.

  • References

  • Syllabus

    • R- Basics: Installing R, Variables, Functions, Workspace, External packages and Data Sets.
    • Introduction to exploratory Data analysis using R: Descriptive statistics; Graphical representation of data: Histogram, Stem-leaf diagram, Box-plot; Visualizing categorical data.
    • Review of Basic Probability: Basic distributions, properties; simulating samples from standard distributions using R commands.
    • Sampling distributions based on normal populations: $t$, $\chi^2$ and $F$ distributions.
    • Model fitting and model checking: Basics of estimation, method of moments, Basics of testing including goodness of fit tests, interval estimation; Distribution theory for transformations of random vectors;
    • Nonparametric tests: Sign test, Signed rank test,Wilcoxon-Mann-Whitney test.
    • Bivariate data: covariance, correlation and least squares.
    • Resampling methods: Jackknife and Bootstrap.

  • Week 1 : January 18th and January 20th

    •
  • These contain the R-code compilation from the slides for the respective week. These are written as R-script files with comments. This effort is entirely student (volunteer) driven.
    (Thanks: Deepta Basak)


  • Week 2 : January 25th and January 27th

    •

  • These contain the R-code compilation from the slides for the respective week. These are written as R-script files with comments. This effort is entirely student (volunteer) driven.
    (Thanks: Deepta Basak)
    • ggplot basics
      • Aesthetic mappings
      • Facets
      • Geometric objects
      • Statistical transformations
      • Position adjustments
      • Coordinate systems
      • The layered grammar of graphics



  • Week 3 : February 1st and February 3rd

    •

  • These contain the R-code compilation from the slides for the respective week. These are written as R-script files with comments. This effort is entirely student (volunteer) driven.
    (Thanks: Deepta Basak)
    • Data frames in R
    • Reading Data frames into R
    • Generating Random Data sets in R

  • Week 4 : February 8th and February 10th

    •


  • Week 5 : February 15th and February 17th

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  • Week 6 : February 22nd and February 24th

    •

    • Emprical Distribution Function
    • Sample Mean and Variance
    • $\chi^2$, $t$ and $F$: sampling distribution

  • Week 7 : March 1st and March 3rd


    • Estimator
    • Method of Moments
    • Maximum Likelihood Estimate

  • Week 8 : March 15th and March 17th


  • Homework 7.
    • These contain the R-code compilation from the slides for the respective week. These are written as R-script files with comments. This effort is entirely student (volunteer) driven.
      (Thanks: Deepta Basak)
      • Central Limit Theorem- Revisited
      • Confidence Intervals

    • Week 9 : March 22nd and March 24th


  • Homework 8.

    • Week 10 : March 29th and March 31st


  • Homework 9.
      • Bivariate-Data
      • Covariance, Correlation
      • Method of Least squares

    • Week 11 : April 5th and April 7th


  • Homework 10
      • $t$-confidence Interval
      • Hypothesis Testing:- Introduction

    • Week 12 : April 12th


  • Homework 11
      • Hypothesis Testing: $z$-test and $t$-test

    • Week 13 : April 19th and April 21st


  • Homework 12
      • Hypothesis Testing: $\chi^2$-goodness of fit.
      • These contain the R-code compilation from the slides for the respective week. These are written as R-script files with comments. This effort is entirely student (volunteer) driven.
        (Thanks: Bikram Halder)

      • n=10,p=1/3

      • n=10, p =1/2

      • n=10, p=2/3

      • n=10, p=5/6


    • Week 14 : April 26th and April 28th


  • Final Homework
      • Hypothesis Testing: Non-parametric- Sign, Sign-ranked Test (Wilcox), Fisher Exact test for independence
      • Resampling Bootstrap
      • These contain the R-code compilation from the slides for the respective week. These are written as R-script files with comments. This effort is entirely student (volunteer) driven.
        (Thanks: Bikram Halder)
    Last Modified: May 5th, 2022. Courses Page Teaching Page