# 
Date 
Topics 
Slides 
Matlab 
Homework 
Videos 
1 
Aug 22 
Class logistics. Two reasons we need probability and statistics in computational bioengineering. 
Lecture_1  
2 
Aug 24 
Random experiments. 
Lecture_2  
3 
Aug 29 
Definitions of probability: inductive or logical. 
Lecture_3  
4 
Aug 31 
Axioms of probability. 
Lectire_4  circuit_template.m  
5 
Sep 5 
Circuits (continued) Bayes theorem. Secretary problem. Simpson's paradox 
Lecture_5  
6 
Sep 7 
Simpson's paradox Monty Hall problem Discrete random variables: 
Lecture_6  hw1.pdf 


7 
Sep 12 
Random variables: skewness, geometric mean Discrete distributions: Uniform The distribution of Ct values of a viral PCR test 
Lecture_7  
8 
Sep 14 
Binomial distribution Poisson distribution Genome assembly (start) 
Lecture_8  
9 
Sep 19 
Genome assembly (continued) Geometric distribution 
Lecture_9  
10 
Sep 21 
Mitochondrial Eve Negative Binomial Distribution Cancer drivers and passengers 
Lecture_10  
11 
Sep 26 
Review of discrete distributions. Continuous random variables: PDF, CDF, CCDF, mean, variance. Constant rate process. Exponential distribution 
Lecture_11 


12 
Sep 28 
Constant rate process (continued) Memoryless property of the exponential distribution Erlang and Gamma distributions 
Lecture_12  hw2_with_solutions.pdf  
13 
Oct 3 
Work in class on Group_Project_1 


14 
Oct 5 
Gaussian distribution Standardization 
Work in class on Group_Project_2


15 
Oct 10 
Multiple variables: Statistical independence of variables Covariation Correlation coefficients: 
Work in class on Group_Project_3 Joint, Marginal, Conditional probablities, Statistical indepndence of variables

cancer_wdbc.mat  
16 
Oct 12 
Linear Functions of Random Variables Principal Component Ananlysis 
Work in class on Videos relevant for this project: 

17 
Oct 17 
Descriptive statistics. Samples, i.i.d. random variables, Histograms. 
Lecture_17  
18 
Oct 19 
Central Limit Theorem Parameter estimators: 
Lecture_18  hw3.pdf  
19 
Oct 24 
Sample variance S^2 (unbiased estimator) Maximum Likelihood Estimator (MLE) Confidence Intervals  with known population variance, sigma^2 
Lecture_19  
20 
Oct 26 
Confidence Intervals  for population average with estimated population variance via sample variance, S^2. Student Tdistribution  for population variance. Chisquared distribution.  for population fraction 
Lecture_20  hw3_with_solutions.pdf  
21 
Oct 31 
Hypothesis tested (one and twosided). One sample and two samples hypotheses Bonferroni correction for multiple hypotheses 
Lecture_21  dark_vs_milk_chocolate_analysis_template.m  
22 
Nov 2 
Midterm review  Lecture_22  
Nov 7 
MIDTERM  
23 
Nov 9 
Linear regression (single variable) 
Lecture_23 


24 
Nov 14 
Chisquared Goodness of Fit Test. M&M colors exercise  Lecture_24  hw4.pdf  
25 
Nov 16 
Multiple Linear Regression. adjusted Rsquared Use of testing and training samples to avoid overfitting. 
Lecture_25  
26 
Nov 28 
Supervised and unsupervised machine learning. Clustering 
Lecture_26  clustering_template.m  hw4_with_solutions.pdf  
27  Nov 30 
Gene Set Enrichment Analysis (GSE) of biological functions in gene expression clusters using NCI David Netwoek analysis: hubs, PageRank, betweennesscentrality Network visualization using Gephi 
Lecture_27 
coexpression_network_random start.gephi 
hw5.pdf  
28 
Dec 5  Final exam review  Lecture_28  hw5_with_solutions.pdf  
FINAL EXAM 