Central limit theorem, normal distribution applications.
Outcomes, sample, space, events, and probability functions.
Probability functions, permuations.
independence of 3 or more events.
Random variables (continued), expected value, standard deviations.
Standard distribution, binomial distribution, two random variables.
Multivariable distribution, binomial distribution, Bernoulli trials, geometric distributions.
Poisson distribution, continuous trials, poisson processes.
Poisson distribution, poisson processes.
Density funtion, continuous random variables, uniform distribution.
Continuous random variables, exponential distribution.
Standard normal distribution, cumulative distribution function.
Nomal distribution continued.
Normal approximation, histogram correction.
Midterm review 2.
Analyzing data in probability, samples, incomplete data, means.
Limit theorems, Markovs inequality theorem, Chebyshevs inequality theorem, Law of large numbers.