More of the derivation of the Poisson Distribution.
Random variables. Expected value. Probability distributions (both discrete and continuous). Binomial distribution. Poisson processes.
Basketball binomial distribution
Expected value of a random variable
Expected value of a binomial distributed random variable
Basic idea and definitions of random variables
Introduction to Poisson Processes and the Poisson Distribution.
Defining discrete and continuous random variables. Working through examples of both discrete and continuous random variables.
More on the binomial distribution
Introduction to the binomial distribution
Using Excel to visualize the basketball binomial distribution
Introduction to the law of large numbers
Saving Earth from becoming a mushroom farm.
Random logic puzzles and brain teasers. Fun to do and useful for many job interviews!
Review of what we've learned. Introduction to the standard deviation.
Measures of central tendency and dispersion. Mean, median, mode, variance, and standard deviation.
Turning light bulbs on and off.
Calculating R-Squared to see how well a regression line fits data
Fitting a line to points. Linear regression. R-squared.
Variance as a measure of, on average, how far the data points in a population are from the population mean
The conceptual and notational differences between a parameter for a population and a statistic calculated from a sample.
Introduction to descriptive statistics and central tendency. Ways to measure the average of a set: median, mean, mode
Covariance, Variance and the Slope of the Regression Line
Thinking about how we can estimate the variance of a population by looking at the data in a sample.