HTHSCI 2S03 Lecture Notes - Lecture 3: Random Variable, Sampling Distribution, Standard Deviation

• School: McMaster University
• Department: Health Sciences
• Course: HTHSCI 2S03
• Professor: D R.fisher

Document Summary

Lecture 3: probability distributions, normal distribution, sampling distribution. Definition: the probability distribution of a discrete random variable is a table, graph, formula, or any other device that specifies all possible values of a discrete random variable along with their corresponding probabilities. The most important distribution in stats is normal distribution. Sigma (cid:840) (cid:841) is standard deviation of the distribution. The % of values falling within 1, 2, & 3 standard deviations of the mean is known. Normal distribution is a family of distributions with each member distinguished from another one based on the values of and . Often interested in the % of values above/below a given value or within a range - we would have to calculate this using the probability density formula for each normal distribution curve - solution: standard normal distribution. We can standardize all normal distributions so each has mean (cid:840) (cid:841) = 0 and standard deviation (cid:840) (cid:841)