part 1: describe data

aug 22 software, data, and description [cm01] [hw01]

aug 29 histograms [cm02] [hw02]

sep 05 Labor Day :: no class

sep 12 data wrangling [cm03] [hw03]

sep 19 location, scale, and the normal approximation [cm04] [hw04]

sep 26 scatterplot, correlation, and regression [cm05] [hw05]

part 2: inference, intuitively

oct 03 box model: chance processes in the long run [cm06] [hw06]

oct 10 sample surveys and confidence intervals [cm07] [hw07]

oct 17 hypothesis tests + t.test() [hw08]

part 3: probability theory

oct 24 basics of probability [hw09]

oct 31 probability mass functions

nov 07 probability density functions [hw11]

part 4: inference, formally

nov 14 point estimates [hw12]

nov 21 interval estimates [hw13]

nov 28 hypothesis tests + mc simulations [hw14]

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Carlisle Rainey