# 
Date 
Topics 
Slides 
Matlab 
Homework 
1 
Jan 16 
Class logistics

Lecture 1  
2 
Jan 18 
Random experiments.

Lecture 2  
3 
Jan 23 
Definitions of probability: inductive or logical Combinatorics Birthday problem 

4 
Jan 25 
Combinatorics: Polya Urn problem Axioms of probability Conditional probability Event independence 
Lecture 4  
5 
Jan 30 
Circuit problems Bayes theorem. 
Lecture 5  
6 
Feb 1 
Simpson's paradox Monty Hall problem 
Lecture 6  
7 
Feb 6 
Random variables: discrete vs continuous PMF, CDF, CCDF, mean, variance, standard deviation, skewness, geometric mean Uniformly distributed random variables 
Lecture 7 

hw1.pdf 
8 
Feb 8 
Bernoulli trial Binomial distribution Matlab exercises 
Lecture 8 


9 
Feb 13 
Poisson Distribution Genome Assembly. Applications of the Poisson distribution 
Lecture 9 

hw1 solutions 
10 
Feb 15 
Geometric Distribution. Mitochondrial Eve and 
Lecture 10 


11 
Feb 20 
MRCA in nuclear part of the genome Negative binomial distribution. Driver and passesnger mutations in cancer 
Lecture 11 


12 
Feb 22 
Continuous random variables: PDF Continuous uniform distribution 
Lecture 12 

hw2.pdf 
13 
Feb 27 
Gaussian or Normal Distribution. Standardizing random variables. 
Lecture 13  exponential_gamma_template.m  
14 
Feb 29 
Erlang distribution  Lecture 14  
15 
Mar 5 
Protein Protein Interations (PPIs) Lognormal Distribution Two random variables Joint Distributions Marginal, conditional probabilities 
Lecture 15  PINT_binding_energy.mat  
16 
Mar 7 
Continuous Joint Distributions Covariance and Correlation 
Lecture 16  correlation_template.m  hw2_solutions 
17 
Mar 19 
Descriptive statistics Samples of i.i.d. random variables Median, quartiles, percentiles 
Lecture 17  
18 
Mar 21 
Misterm review  Lecture 18  
Mar 26 
MIDTERM during regular lecture hours  
19 
Mar 28 
Boxplot, vase and violin diagrams Probability plots: light and heavytailed distributions Sample statistic:Sample mean, its average value and standard deviation. Sampling distribution of the sample mean: Central Limit Theorem. 
Lecture 19  
20 
Apr 2 
Parameter point estimation Sample variance Method of Moments 
Lecture 20  moment_estimators_template.m  
21 
Apr 4 
Method of Maximum Likelihood Estimation Confidence intervals. Tstatistic and Student's Tdistribution 
Lecture 21  hw3.pdf  
22 
Apr 9 
Chisquared distribution Hypothesis testing : Type I and TypeII errors 
Lecture 22  Chisquared distribution  
23 
Apr 11 
Hypothesis testing with two samples Bonferroni correction for multiple hypotheses Chisquared goodness of fit test with k classes. Test of statistical independence.

Lecture 23  
24 
Apr 16 
Two variable linear regression  Lecture 24 


25 
Apr 18 
How to avoid overfitting the data. Training and testing datasets Double descent Multiple linear regression Adjusted Rsquared 
Lecture 25  hw4.pdf  
26 
Apr 23 
Clustering data  Lecture 26  
27 
Apr 25 
gephi_network_analysis_exercise.pdf 

28  Apr 30  
FINAL EXAM 