|
Date |
Topics |
Slides |
Matlab |
|
Jan 27 |
Why probability and statistics is needed for bioengineering? | Lecture 1 | |
|
Jan 29 |
Random experiments. Sample space, Events, Venn diagramms. Definitions of probability:Statistical (part 1) |
Lecture 2 |
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Feb 3 |
Definitions of probability: Paradoxes of inductive definition of probability Combinatorics |
Lecture 3 | |
|
Feb 5 |
Conditional probability Bayes' theorem Specificity/Sensitivity of tests Circuit diagrams |
Lecture 4 | circuit_template.m |
|
Feb 10 |
Discrete random varibales, Uniform distribution |
Lecture 5 | |
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Feb 12 |
Bernoulli trials Binomial Distribution |
Lecture 6 | poisson_template.m |
|
Feb 17 |
Genome Assembly (cont) Geometric distribution. Mitochondrial Eve and Y-chromosme Adam. Time to the Most Recent Common Ancestor (MRCA) for the nuclear genome |
Lecture 7 |
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Feb 19 |
Mitochondrial Eve & Tree of Life (continued) Negative Binomial Distribution Cancer: Driver and Passenger Genes |
Lecture 8 | |
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Feb 24 |
NO LECTURE. TIME TO PREPARE FOR THE MIDTERM 1 |
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Feb 26 |
Secretary problem Monty Hall problem Simpson's paradox |
Lecture 9 | |
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Mar 3 |
Continuous random variables. Probability Density Function, CDF, CCDF, Mean, Variance, Standard deviation. Skewness. Uniform continuous distribution. |
Lecture 10 |
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Mar 5 |
Constant rate (Poisson) process. Exponential distribution. Erlang and Gamma distributions |
Lecture 11 | exponential_gamma_template.m |
|
Mar 10 |
Gaussian distribution Standardizing and working with the CDF table |
Lecture 12 | |
|
Mar 12 |
Fitting Gaussian distribution to the data for binding energies of protein-protein interactions Multiple random variables. Joint, Marginal, and Conditional PMFs |
Lecture 13 | |
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Mar 17 |
SPRING BREAK | ||
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Mar 19 |
SPRING BREAK | ||
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Mar 24 |
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Mar 26 |
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Mar 31 |
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Apr 2 |
NO LECTURE. THE MIDTERM 2 | ||
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Apr 7 |
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Apr 9 |
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Apr 14 |
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Apr 16 |
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Apr 21 |
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Apr 23 |
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Apr 28 |
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| Apr 30 | |||
| May 5 | |||
| Final Exam |