Probability: Sample spaces, events, counting methods, conditional probability, independence, Bayes theorem. Discrete random variables, mean and variance. Binomial and Poisson. Continuous random variables. The Normal model. Bivariate discrete random variables. Covariance and correlation. Sampling distribution of the mean. Confidence intervals and hypothesis testing: one and two samples, paired samples. Confidence intervals and hypothesis testing for one proportion. Computation...
Learning Outcomes
Describe various types of data using numerical or graphical techniques
Calculate probabilities and conditional probabilities and for unions and intersections of events
Work with discrete random variables, including Binomial and Poisson
Calculate probabilities based on the Normal model
Test statistical hypotheses
Calculate and interpret confidence intervals
Calculate and explain correlation
Calculate, interpret and perform inference using the regression line