Probability and Statistics III: A Gentle Introduction to Statistics
Learn basic statistical concepts, probability distributions, descriptive statistics, and estimation methods in this comprehensive course. Gain a solid understanding of the normal distribution and the Central Limit Theorem. Explore statistical sampling distributions for practical applications.
What you will learn
- Review a library of discrete and continuous probability distributions
- Recognize the normal distribution and the Central Limit Theorem, and how they are applied in practice
- Recognize elementary methods of descriptive statistics
- Describe methods that can be used to estimate the unknown parameters of a distribution
- Identify statistical sampling distributions
Program Overview
This course provides an introduction to basic statistical concepts.
We begin by walking through a library of probability distributions, where we motivate their uses and go over their fundamental properties.
These distributions include such important folks as the Bernoulli, binomial, geometric, Poisson, uniform, exponential, and normal distributions, just to name a few. Particular attention is paid to the normal distribution, because it leads to the Central Limit Theorem (the most-important mathematical result in the universe, actually), which enables us to make probability calculations for arbitrary averages and sums of random variables.
We then discuss elementary descriptive statistics and estimation methods, including unbiased estimation, maximum likelihood estimation, and the method of moments ? you gotta love your MoM! Finally, we describe the t, X2, and F sampling distributions, which will prove to be useful in upcoming statistical applications.
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