STAT 101 Lecture Notes - Lecture 7: Binomial Distribution, Statistical Inference, Sample Space

• School: Simon Fraser University
• Department: Statistics
• Course: STAT 101
• Professor: Timothy Swartz

Document Summary

Stat 101 - lecture 7 - probability & binomial distributions. Material covered corresponds to chapters 12 & 14 from textbook. Probability - cornerstone of statistical inference allowing us to learn about populations through sampled data. Although data random, probability provides us w/ tools to better understand randomness in data so we can make assessments about unknowns in populations. When considering experiment producing data, often useful to provide probabilistic description for experiment. Process of assigning probabilistic descriptions - referred to as statistical modelling. Modelling can often provide insights w/ respect to underlying population. For this course, will think of probability of event a as proportion of times a would occur if experiment repeated many times under identical conditions. Important to note that these are hypothetical repetitions of experiment. Personal probability - alternative way of thinking about probability. Sample space - sets of all possible outcomes that may possibly occur in experiment.