Biostat 2021 Rough Schedule

	A	B	C	D	E	F	G	H	I	K
1	class #	date	topic			Major assignment due		Dream
2	0	1/20/21	Intro to class					intro to class / install download R / RStudio / tidyverse / first ggplot
3	1	1/22/21	What is Stats					dplyr
4	2	1/25/21	Data					data in R
5	3	1/27/21	R					intro to stats w. DAG / causality
6	4	1/29/21	Data in R I					good plots w.o r
7	5	2/1/21	Data in R 2					data summaries - mean, variance, covvariance, correlation	adding summaries to plots
8	6	2/3/21	ggplot1					sampling
9	7	2/5/21	Data summaries					estimating w uncertainty / bootstrapping	coding and writing functions
10	8	2/8/21	sampling					quiz 1
11	9	2/10/21	estimating with uncertainty					prob 1
12	10	2/12/21	r review					prob II
13	11	2/15/21	plots 2					prob III. - binomial disribution
14	12	2/17/21	More plots			Data exploration		r revciew	quiz 2 due after class
15	13	2/19/21	stats review / midterm					hypothesis testing - concepts	DAGS
16	14	2/22/21	probability one -- simulation			hange order		hpothesis testin permutation coding and writing functinos
17	15	2/24/21	probability two -- math					permute / bootstrap two cotinuous vars
18	16	2/26/21	hypothesis testing 1					contingency tests by permutation. ummary stats & chi2
19	17	3/1/21	permute / bootstrap one cotinuous one categorical vars					hypothesis testing II simulaiton and math - binomial example
20	18	3/3/21	permute / bootstrap two cotinuous vars					review / project I
21	19	3/5/21	contingency tests by permutation. ummary stats & chi2					quiz 3
22	20	3/8/21	binomial distribution / and likelihood / baysian intro					normal
23	21	3/10/21	review					t	causal inference
24	22	3/12/21	normal distribution and the idea of disrtibutions and more likelihood					linear models and modeling
25	23	3/15/21	t-values					anova	causal inference
26	24	3/17/21	linear models and modelling				assumptions	posthoc
27	25	3/19/21	two ts			Hypothesis testing		multiple testing	take home exam
28	26	3/22/21	ANOVA and multiple testing					exam 1
29	27	3/24/21	Regression 1					regression1
30	28	3/26/21	regression 2.	two factors				regression2	causal inference
31	29	3/29/21	regression 3	with interaction				regression 3	causal inference
32	30	3/31/21	experimental desgin and power		classic R and programming			exam 1
33	31	4/2/21	bias and racist stats???	straight up				bias and racit stasts
34		4/5/21	SPRING BREAK
35		4/7/21	SPRING BREAK
36		4/9/21	SPRING BREAK
37	32	4/12/21	what is science and nhst doing			n class exam		what is science and nhst doing
38	33	4/14/21	causal inference					fancy plots I
39	34	4/16/21	work on project			linear modeling		markdown
40	35	4/19/21	likelihood based inference					dplyr and data manipulation review
41	36	4/21/21	glm1					reproducibility		exam
42	37	4/23/21	glm2					likelihoods
43	38	4/26/21	random effects 1
44	39	4/28/21	random effects 2					indepedent exploration I
45	40	4/30/21	fancy data set	do in groups				indepedent exploration II
46	41	5/3	take home exam			in class they		indepedent exploration III
47			1:30 to 3:30 p.m., Wednesday, May 12					presenting indep explor
48								final project
49						potential indepednet exploration topics
50						glm
51						mixed effects
52						bayse	they want more design
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54
55
56
57
58	Hypothesis testing
59	Evaluating Causal Claims
60	Modleing
61	Bias
62	R
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