STAB22H3 Lecture Notes - Lecture 1: Frequentist Inference, Statistical Inference
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STAB22H3 Full Course Notes
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Quizzes will focus on describing and understanding rather than computation. Two parts to this: data collection, and statistical inference (e. g. frequentist, bayesian) Frequentist inference includes content such as p-values, confidence intervals, etc. Practically, if we could get all the info we need from a census, we would not need stats. Realisti(cid:272)ally, (cid:272)e(cid:374)sus" are (cid:374)ot a(cid:271)le to pro(cid:448)ide all the i(cid:374)for(cid:373)atio(cid:374) (cid:449)e (cid:374)eed (cid:272)o(cid:374)siste(cid:374)tly. Categorical/qualitative: relating to variables that are not measured (e. g. shirt color, automobile type) Nominal scale: categorical variables where the order does not matter. Ordinal scale: categorical variables where the order matters (e. g. letter grades a,b,c, etc. ) Quantitative: relating to variables that are measured (e. g. height, weight, blood alcohol levels) Proportion: relating to a percentage amount expressed as a decimal (e. g. 5% as 0. 05) To get to this, divide the x% by 100; to get from proportion to percentage, multiply by 100.