Math and Probability for Life Sciences

Incarcat la data: 19 Aprilie 2011

Autor: Admin

By Herbert Enderton - University of California, Los Angeles
Licence: Creative Commons Attribution-NonCommercial-ShareAlike 3.0

Course Description:
This is a math course aimed at students with life science majors covering elementary probability, probability distributions, random variables, and limit theorems.
Lectures:
Lecture 1 - Introduction: Probability and Counting

Outcomes, sample, space, events, and probability functions.

 
Lecture 2 - Probability Functions

Probability functions, permuations.

 
 
 
Lecture 5 - Conditional Probability

Conditional probability.

 
 
Lecture 7 - Independent Events

independence of 3 or more events.

 
 
Lecture 9 - Expected Values

Random variables (continued), expected value, standard deviations.

 
Lecture 10 - Binomial Distributions

Standard distribution, binomial distribution, two random variables.

 
 
Lecture 12 - Multinomial Distributions

Multivariable distribution, binomial distribution, Bernoulli trials, geometric distributions.

 
 
Lecture 14 - Poisson Distributions

Poisson distribution, continuous trials, poisson processes.

 
Lecture 15 - Poisson Distributions (continued)

Poisson distribution, poisson processes.

 
Lecture 16 - Density Function

Density funtion, continuous random variables, uniform distribution.

 
Lecture 17 - Exponential Distributions

Continuous random variables, exponential distribution.

 
 
Lecture 19 - Normal Distributions (continued)

Standard normal distribution, cumulative distribution function.

 
Lecture 20 - Standard Normal Distributions

Nomal distribution continued.

 
Lecture 21 - Central Limit Theorem

Central limit theorem, normal distribution applications.

 
Lecture 22 - Hitstogram Correction

Normal approximation, histogram correction.

 
 
Lecture 24 - Analyzing Data in Probability

Analyzing data in probability, samples, incomplete data, means.

 
Lecture 25 - Analyzing Data in Probability (continued)

Analyzing data in probability, samples, incomplete data, means.

 
Lecture 26 - Limit Theorems

Limit theorems, Markovs inequality theorem, Chebyshevs inequality theorem, Law of large numbers.

 
Lecture 27 - Limit Theorems (continued)

Limit theorems, Markovs inequality theorem, Chebyshevs inequality theorem, Law of large numbers.

 
 

Source: http://academicearth.org/courses/math-and-proability-for-life-sciences

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