future_changes

course website:
* include in required materials: LaTex
* Add link to this: https://statmodeling.stat.columbia.edu/wp-content/uploads/2020/07/raos_tips.pdf

labs overall
* show only broom and kable for creating table summaries throughout
* in lab 9, show them papaja in depth (add links to other options, like stargazer, apaTables, and sjPlot to just create tables in Word)
* incorporate in-text R code to summarize results throughout 

final-project.html
  * More specific guidelines. suggestions commented out in file. 

1-correlation.html

  * edit -- choppy and unstructured
  * add power to correlation lectures -- when do correlations stabilize?

  * when talking about Galton (and Pearson and Fisher), discuss racist attitudes and eugenics
	- important to know history, think twice before revering these men
	- should we stop using these tools? Of course not! The tools themselves are not racist, and we can do a lot of good with them. 
	- what are the implications for our tools? How have these tools been used in the past? What assumptions are made by people using these tools and how does it perpetuate norms about their use
		- examples: using white, cis, able-bodied men as control groups; try to use these methods as justification for racist policies
	- link to Moin's essay: https://cla.umn.edu/psychology/news-events/story/psychology-must-reckon-its-racist-past-and-present
		

1-lab.html

  * maybe add missingness (but included in class already) -- minihack?
  
3-regression.html

  * add notes to slide 18
  * add the squares
  * move regression to the mean here

  * add this! https://joshualoftus.com/post/2020-11-23-least-squares-as-springs/least-squares-as-springs/ 
  
3-lab.html

  * it was particularly helpful to draw out the matrices on the board during the matrix algebra section (i.e. draw the Y vector and the X matrix with column of 1’s) and to keep track of matrix dimensions, etc. while explaining the B vector.
  
7-partial.html
  * when to use each: only care about X and Y and controlling for variable; comparions between diff x's and incremental validity; network analysis
  
9-m_regression.html

  * better clarification for adding multiple predictors
  * add slides to walk through predicting Y from dummy codes
  * how was wisdom measured in the psych science article?
  * if time, show how factor variable is doing the same as dummy codes (how?)
  
10-m_regression.html

  * demonstrate that degrees of freedom are the same (ANOVA table and F-test of omnibus)
  * Make F-distribution plot number-free (don't give numbers that don't correspond to example)
  * reiterate example before diving back into R code
  * remind students to do reading?
  
11-diagnostics.html
* add something about weighted least squares (homoscedasticity)

homework-1.html

Question 10.1
* last bullet point should not say "#5 and #6" but should refer to specific models. Suggestions have been made in Markdown files. 

13-dag.html
* add something before about dag models are pre-data collection tools
* add paper by Grosz, Rohrer, & Thoemmes (2020) "The taboo against explicit causal inference in non experimental psychology." As optional reading. Describe during class? 

homework-2.html
* make due last week of class
* weights are 1/predicted values, not predicted values!!!

lab-8.html
* change eemmeans() to lsmeans()
* use pairs() instead of contrast()
* need to specify contrasts before running the model `options(contrasts = c("contr.sum", "contr.poly"))` in order for the apaTables apa.aov.table() function to be correct
* download papaja before lab 9 (this often has errors!!!! do this soon so we can skip troubleshooting in lab 9)
* laTex may need admin privleges 

17-interactions.html
* don't mention regression sums of squares
* remove "most common" sums of squares in slides
* add SPSS and SAS defaults are type III
* add to FA and Regression comparison slide: compare output
* take out sjPlot main effects

lab-9.html
* we will NOT troubleshoot installing papaja at the beginning of this lab