MATH 1050Y Lecture Notes - Lecture 1: Statistical Inference, Statistical Parameter, Standard Deviation

• School: Trent University
• Department: Mathematics
• Course: MATH 1050Y
• Professor: Boue Michelle

Document Summary

Lecture #1: inference for numerical data; relationships between variables. Review: types of variables, populations and samples, notation: types of variables. Numerical continuous, and discrete (this semester only going to learn about this) Categorical regular categorical and ordinal: population and sample. Population: whole group of objects or people we wish to study. Population: collected of all possible objects or people of interest, information is difficult to collect, the quantities we calculate are parameters. Sample: a subset of the population, information is easier to collect, the quantities we calculate are statistic with inferential statistics, we learn about the population by studying the data in our sample, population parameter(census, sample statisti(cid:272) Is pro(cid:374)ou(cid:374)(cid:272)ed (cid:858)(cid:373)u(cid:859) a(cid:374)d de(cid:374)otes the (cid:373)ea(cid:374) of all (cid:448)alues i(cid:374) populatio(cid:374) unless there is a census, its value is unknown and is estimated by the sample mean. Notation: variance and standard deviation for population and sample. Sigma denotes the standard deviation of all possible values in a population.