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Course

# Math and Probability for Life Sciences

University of California, Los Angeles

This is a math course aimed at students with life science majors covering elementary probability, probability distributions, random variables, and limit theorems.

Home > Mathematics > Calculus > Math and Probability for Life SciencesLectures:
• ### Introduction: Probability and Counting

00:44:25Mark Sawyer

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

• ### Probability Functions

00:48:56Mark Sawyer

Probability functions, permuations.

• ### Permutations

00:51:54Mark Sawyer

Permutations.

• ### Probability Functions (continued)

00:49:35Mark Sawyer

Probability functions.

• ### Conditional Probability

00:49:37Mark Sawyer

Conditional probability.

• ### Conditional Probability (continued)

00:48:59Mark Sawyer

Conditional probability.

• ### Independent Events

00:38:53Mark Sawyer

independence of 3 or more events.

• ### Random Variables

00:50:02Mark Sawyer

Random variables.

• ### Expected Values

00:49:36Mark Sawyer

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

• ### Binomial Distributions

00:51:18Mark Sawyer

Standard distribution, binomial distribution, two random variables.

• ### Midterm Review

00:40:42Mark Sawyer

Midterm review.

• ### Multinomial Distributions

00:41:19Mark Sawyer

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

• ### Geometric Distributions

00:43:50Mark Sawyer

Geometric distributions.

• ### Poisson Distributions

00:47:04Mark Sawyer

Poisson distribution, continuous trials, poisson processes.

• ### Poisson Distributions (continued)

00:51:24Mark Sawyer

Poisson distribution, poisson processes.

• ### Density Function

00:50:19Mark Sawyer

Density funtion, continuous random variables, uniform distribution.

• ### Exponential Distributions

00:51:22Mark Sawyer

Continuous random variables, exponential distribution.

• ### Normal Distributions

00:49:08Mark Sawyer

Normal distribution.

• ### Normal Distributions (continued)

00:49:40Mark Sawyer

Standard normal distribution, cumulative distribution function.

• ### Standard Normal Distributions

00:48:01Mark Sawyer

Nomal distribution continued.

• ### Central Limit Theorem

00:53:09Mark Sawyer

Central limit theorem, normal distribution applications.

• ### Hitstogram Correction

00:49:50Mark Sawyer

Normal approximation, histogram correction.

• ### Midterm Review 2

00:40:44Mark Sawyer

Midterm review 2.

• ### Analyzing Data in Probability

00:49:16Mark Sawyer

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

• ### Analyzing Data in Probability (continued)

00:48:29Mark Sawyer

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

• ### Limit Theorems

00:49:01Mark Sawyer

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

• ### Limit Theorems (continued)

00:44:12Mark Sawyer

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

• ### Course Review

00:45:20Mark Sawyer

Course Review