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## ​

Amrik's lecture notes

Set 1: (pdf) "up to some named distributions"
Set 1.0.1: (pdf"basics of probability"
Set 1.0.2: (pdf"example of Bayes theorem"
Set 1.1: (pdf) "random walk on a lonely island"
Set 1.2: (pdf) "recurrence relations & solutions"
Set 1.3: (pdf) "reference book on basic probability"
Set 1.4: (pdf) "summary of discrete random variables"
Set 1.5: (pdf) "solns. to numerical problems on discrete
probability distribution"
Set 2: (pdf) "up to end of basics of probability"
Set 2.1: (pdf) "summary of continuous random variables"
Set 2.2: (pdf) "problems on composite probability distributions"
Set 2.3: (pdf) "Composite PDFs: discrete vs continuous"
Set 3: (pdf) "up to end of discrete Markov chains"
Set 3.1: (pdf) "introduction to DTMC"
Set 3.2: (pdf) "advanced concepts in DTMC"
Set 3.3: (pdf) "advanced concepts in DTMC: numerical examples"
Set 4: (pdf) "Motivating e.g. for CTMC (server-queue problem)"
Set 5: (pdf) "Notes on CTMC (concepts and theory)"
Set 6: (pdf) "Applications of Kolmogorov Balance eqns."

Data: Brooklyn_COVID.csv
Set 7: (pdf) "Sampling distributions: for mean & variance"
Set 7.1: (pdf) "slides on Sampling distributions"
Set 8: (pdf) "Hypothesis tests & ANOVA (1-way)"
Set 8.1: (pdf) "introduction to hypothesis tests"
Data: Coke.csv

Set 8.2: (pdf) "Two sample t-test for means"
Set 8.3: (pdf) "One-way ANOVA"
** for 2-way ANOVA, refer pp. 565-572 in Walpole's book.
Set 9: (pdf) "Time series analysis"

Data: jobs.csv

Data: World_Bank_Data.csv

Data: EnergyConsumptionMP_1996-2018.csv
Set 9.1: (pdf) "Time series: introductory concepts"
Set 9.2: (pdf) "Time series: MA(1)"
Set 9.3: (pdf) "Time series: AR(1)"
Set 10: (pdf) "Principal component analysis"
Set 10.1: (pdf) "Principal component analysis"
Set 11: (pdf) "Least squares regression"

Links to ZOOM recording of lectures
Probability Distributions: review
Lecture 1.0: (here - for PCL 108, DMC 013)
Lecture 1.1: (here - for PCL 108, DMC 013)
Lecture 2: (here - for PCL 108, DMC 013
Lecture 3: (here - for PCL 108, optional for DMC 013)
Lecture 4: (here - for PCL 108, optional for DMC 013)
Lecture 5: (here - for PCL 108, optional for DMC 013)
Lecture 6: (here - PCL 108)
Lecture 7: (here - PCL 108, DMC 013)
Lecture 8: (here - PCL 108, DMC 013)
Lecture 9: (here - PCL 108)
Lecture 10: (here - PCL 108)

Discrete Time Markov Chains (DTMC)
Lecture 11: (here PCL 108)
Lecture 13: (here - PCL 108)
Lecture 14: (here - PCL 108)
Lecture 15: (here - PCL 108)

Least Squares Regression
Lecture 12: (here - DMC 013, PCL 108)

Sampling Dn, Hypothesis tests & ANOVA
Lecture 16: (here - DMC 013, PCL 108)
Lecture 17: (here - DMC 013, PCL 108)
Lecture 18: (here - DMC 013, PCL 108)
Lecture 19: (here - DMC 013, PCL 108)

Time Series Analysis
Lecture 20: (here- DMC 013, PCL 108)
Lecture 21: (here- DMC 013, PCL 108)
Lecture 22: (here- DMC 013, PCL 108)

Principal Component Analysis
Lecture 23: (here- PCL 108)
Lecture 24: (here- PCL 108)