updates after having completed teaching in 2021

01-introduction.Rmd

@@ -62,7 +62,6 @@ library("tidyverse")    # everything else
 
 # Visualization
 library("patchwork")    # making figure panels
-library("cowplot")      # making figure panels
 library("ggpol")        # for making fancy boxplots
 library("ggridges")     # for making joyplots 
 library("gganimate")    # for making animations
@@ -71,13 +70,13 @@ library("ggrepel")      # for labels in ggplots
 library("corrr")        # for calculating correlations between many variables
 library("corrplot")     # for plotting correlations
 library("DiagrammeR")   # for drawing diagrams
+library("ggeffects")    # for visualizing effects
 library("bayesplot")    # for visualization of Bayesian model fits 
 
 # Modeling 
 library("afex")         # also for running ANOVAs
 library("lme4")         # mixed effects models 
 library("emmeans")      # comparing estimated marginal means 
-library("broom")        # getting tidy model summaries
 library("broom.mixed")  # getting tidy mixed model summaries
 library("janitor")      # cleaning variable names 
 library("car")          # for running ANOVAs
@@ -91,6 +90,7 @@ library("multilevel")   # Sobel test
 library("extraDistr")   # additional probability distributions
 library("effects")      # for showing effects in linear, generalized linear, and other models
 library("brms")         # Bayesian regression
+library("parameters")   # For extracting parameters 
 
 # Misc 
 library("tictoc")       # timing things
@@ -99,8 +99,22 @@ library("lsr")          # for computing effect size measures
 library("extrafont")    # additional fonts
 library("pwr")          # for power calculations
 library("arrangements") # fast generators and iterators for permutations, combinations and partitions
+library("stargazer")    # for regression tables
+library("sjPlot")       # for regression tables
+library("xtable")       # for tables
 ```
 
+## Installing packages 
+
+```{r, eval=FALSE, include=FALSE}
+# Note: To get greta to work on my mac, I had to run the following commands 
+devtools::install_github("greta-dev/greta")
+greta::install_tensorflow(method = "conda",
+                   version = "1.14.0",
+                   extra_packages = "tensorflow-probability==0.7.0")
+```
+
+
 ## Session info
 
 ```{r, echo=F}

02-visualization1.Rmd

@@ -20,7 +20,7 @@ library("tidyverse") # for plotting (and many more cool things we'll discover la
 
 # these options here change the formatting of how comments are rendered
 # in RMarkdown 
-opts_chunk$set(comment = "#>",
+opts_chunk$set(comment = "",
                fig.show = "hold")
 ```
 
@@ -740,11 +740,11 @@ Here, I've set `color = "black"` within the `geom_smooth()` function, and now on
 
 ### Cheatsheets
 
-- [RStudio IDE](figures/cheatsheets/rstudio-ide.pdf) --> information about RStudio
-- [RMarkdown](figures/cheatsheets/rmarkdown.pdf) --> information about writing in RMarkdown
-- [RMarkdown reference](figures/cheatsheets/rmarkdown-reference.pdf) --> RMarkdown reference sheet
-- [Data visualization](figures/cheatsheets/visualization-principles.pdf) --> general principles of effective graphic design
-- [ggplot2](figures/cheatsheets/data-visualization.pdf) --> specific information about ggplot
+- [RStudio IDE](figures/rstudio-ide.pdf) --> information about RStudio
+- [RMarkdown](figures/rmarkdown.pdf) --> information about writing in RMarkdown
+- [RMarkdown reference](figures/rmarkdown-reference.pdf) --> RMarkdown reference sheet
+- [Data visualization](figures/visualization-principles.pdf) --> general principles of effective graphic design
+- [ggplot2](figures/data-visualization.pdf) --> specific information about ggplot
 
 ### Datacamp courses
 
@@ -758,28 +758,27 @@ Here, I've set `color = "black"` within the `geom_smooth()` function, and now on
 - [R graphics cookbook](http://www.cookbook-r.com/Graphs/) --> quick intro to the the most common graphs
 - [ggplot2 book](https://ggplot2-book.org/) 
 - [R for Data Science book](http://r4ds.had.co.nz/)
-  + [R Markdown](https://r4ds.had.co.nz/r-markdown.html)
-	+ [Data visualization](http://r4ds.had.co.nz/data-visualisation.html)
-	+ [Graphics for communication](http://r4ds.had.co.nz/graphics-for-communication.html)
+  + [Data visualization](http://r4ds.had.co.nz/data-visualisation.html)
+  + [Graphics for communication](http://r4ds.had.co.nz/graphics-for-communication.html)
 - [Data Visualization -- A practical introduction (by Kieran Healy)](http://socviz.co/)
   + [Look at data](http://socviz.co/lookatdata.html#lookatdata)
   + [Make a plot](http://socviz.co/makeplot.html#makeplot)
   + [Show the right numbers](http://socviz.co/groupfacettx.html#groupfacettx)
-- [Fundamentals of Data Visualization](https://clauswilke.com/dataviz/) --> very nice resource that goes beyond basic functionality of `ggplot` and focuses on how to make good figures (e.g. how to choose colors, axes, ...)
+- [Fundamentals of Data Visualization](https://serialmentor.com/dataviz/) --> very nice resource that goes beyond basic functionality of `ggplot` and focuses on how to make good figures (e.g. how to choose colors, axes, ...)
 
 ### Misc
 
-- [learn R demos](https://github.com/poldrack/learnr_demos) --> tutorials on learning R created by Russ Poldrack for Psych 10 (the Stanford undergraduate statistics class)
 - [nice online ggplot tutorial](https://evamaerey.github.io/ggplot2_grammar_guide/about)
 - [how to read R help files](https://socviz.co/appendix.html#a-little-more-about-r)
 - [ggplot2 extensions](http://www.ggplot2-exts.org/gallery/) --> gallery of ggplot2 extension packages
-- [ggplot2 gui](https://github.com/dreamRs/esquisse) --> ggplot2 extension package
 - [ggplot2 visualizations with code](http://r-statistics.co/Top50-Ggplot2-Visualizations-MasterList-R-Code.html) --> gallery of plots with code
-- [R Markdown for class reports](http://www.stat.cmu.edu/~cshalizi/rmarkdown/)
-- [styler](https://github.com/r-lib/styler) --> RStudio add-in that re-formats code
 
 ## Session info
 
 ```{r, echo=F}
 sessionInfo()
 ```
+
+```{r, echo=FALSE, fig.cap="Defense at the reproducibility court.", out.width="95%"}
+include_graphics("figures/reproducibility_court.jpg")
+```

03-visualization2.Rmd

@@ -775,17 +775,17 @@ Here are some snippets I use:
 
 ```{r, eval=FALSE}
 snippet snbar
-	ggplot(data = ${1:data}, mapping = aes(x = ${2:x}, y = ${3:y})) +
-		stat_summary(fun = "mean", geom = "bar", color = "black") +
-		stat_summary(fun.data = "mean_cl_boot", geom = "linerange")
-		
+  ggplot(data = ${1:data}, mapping = aes(x = ${2:x}, y = ${3:y})) +
+    stat_summary(fun = "mean", geom = "bar", color = "black") +
+    stat_summary(fun.data = "mean_cl_boot", geom = "linerange")
+    
 snippet sngg
-	ggplot(data = ${1:data}, mapping = aes(${2:aes})) +
-		${0}
+  ggplot(data = ${1:data}, mapping = aes(${2:aes})) +
+    ${0}
 
 snippet sndf
-	${1:data} = ${1:data} %>% 
-		${0}
+  ${1:data} = ${1:data} %>% 
+    ${0}
 ```
 
 To make a bar plot, I now only need to type `snbar` and then hit TAB to activate the snippet. I can then cycle through the bits in the code that are marked with `${Number:word}` by hitting TAB again. 
@@ -806,23 +806,21 @@ usethis::edit_rstudio_snippets()
 
 This command opens up a separate tab in RStudio called `r.snippets` so that you can make new snippets and adapt old ones more quickly. Take a look at the snippets that RStudio already comes with. And then, make some new ones! By using snippets you will be able to avoid typing the same code over and over again, and you won't have to memorize as much, too. 
 
-## Additional resources  
+## Additional resources 
 
 ### Cheatsheets 
 
 - [shiny](figures/shiny.pdf) --> interactive plots 
 
 ### Data camp courses 
 
-- [ggplot (intermediate)](https://learn.datacamp.com/courses/intermediate-data-visualization-with-ggplot2)
-- [shiny 1](https://www.datacamp.com/courses/building-web-applications-in-r-with-shiny)
-- [shiny 2](https://www.datacamp.com/courses/building-web-applications-in-r-with-shiny-case-studies)
+- [shiny](https://www.datacamp.com/courses/building-web-applications-in-r-with-shiny-case-studies)
 
 ### Books and chapters
 
 - [R for Data Science book](http://r4ds.had.co.nz/)
-	+ [Data visualization](http://r4ds.had.co.nz/data-visualisation.html)
-	+ [Graphics for communication](http://r4ds.had.co.nz/graphics-for-communication.html)
+  + [Data visualization](http://r4ds.had.co.nz/data-visualisation.html)
+  + [Graphics for communication](http://r4ds.had.co.nz/graphics-for-communication.html)
 - [Data Visualization -- A practical introduction (by Kieran Healy)](http://socviz.co/)
   + [Refine your plots](http://socviz.co/refineplots.html#refineplots)
 
@@ -840,4 +838,4 @@ Information about this R session including which version of R was used, and what
 
 ```{r}
 sessionInfo()
-```
+```

04-data_wrangling1.Rmd

@@ -9,13 +9,6 @@ In this lecture, we will take a look at how to wrangle data using the [dplyr](ht
 - See different ways for getting a sense of one's data. 
 - Master key data manipulation verbs from the `dplyr` package (incl. `filter()`, `arrange()`, `rename()`, `relocate()`, `select()`, `mutate()`) as well as the helper functions `across()` and `where()`.
 
-## Install packages 
-
-```{r install-packages, eval=FALSE}
-install.packages(c("skimr", "visdat", "summarytools", "DT"))
-```
-
-
 ## Load packages 
 
 Let's first load the packages that we need for this chapter. 
@@ -27,6 +20,9 @@ library("visdat")       # for visualizing data
 library("summarytools") # for visualizing data 
 library("DT")           # for visualizing data 
 library("tidyverse")    # for data wrangling
+
+opts_chunk$set(comment = "",
+                      fig.show = "hold")
 ```
 
 ## Some R basics 
@@ -874,12 +870,12 @@ Compute the body mass index for `masculine` characters who are `human`.
 # write your code here 
 ```
 
-## Additional resources   
+## Additional resources  
 
 ### Cheatsheets 
 
-- [base R](figures/cheatsheets/base-r.pdf) --> summary of how to use base R (we will mostly use the tidyverse but it's still important to know how to do things in base R)
-- [data transformation](figures/cheatsheets/data-transformation.pdf) --> transforming data using `dplyr`
+- [base R](figures/base-r.pdf) --> summary of how to use base R (we will mostly use the tidyverse but it's still important to know how to do things in base R)
+- [data transformation](figures/data-transformation.pdf) --> transforming data using `dplyr`
 
 ### Data camp courses
 
@@ -897,12 +893,10 @@ Compute the body mass index for `masculine` characters who are `human`.
 - [Chapters 9-15 in "R for Data Science"](https://r4ds.had.co.nz/wrangle-intro.html)
 - [Chapter 5 in "Data Visualization - A practical introduction"](http://socviz.co/workgeoms.html#workgeoms)
 
-### Misc 
-
-- [Tidyverse style guide](https://style.tidyverse.org/)
+## Session info 
 
-## Session info
+Information about this R session including which version of R was used, and what packages were loaded. 
 
-```{r, echo=F}
+```{r}
 sessionInfo()
 ```

05-data_wrangling2.Rmd

@@ -620,35 +620,37 @@ save(df.test, df.starwars, file = "data/test_starwars.RData")
 
 ## Additional resources
 
-### Cheatsheets 
+### Cheatsheets
 
-- [wrangling data](figures/cheatsheets/data-wrangling.pdf) --> wrangling data using `dplyr` and `tidyr`
-- [importing & saving data](figures/cheatsheets/data-import.pdf) --> importing and saving data with `readr`
+-   [wrangling data](figures/data-wrangling.pdf) --> wrangling data using `dplyr` and `tidyr`
+-   [importing & saving data](figures/data-import.pdf) --> importing and saving data with `readr`
 
-### Data camp courses 
+### Data camp courses
 
-- [Joining tables](https://www.datacamp.com/courses/joining-data-in-r-with-dplyr)
-- [writing functions](https://www.datacamp.com/courses/writing-functions-in-r)
-- [importing data 1](https://www.datacamp.com/courses/importing-data-in-r-part-1)
-- [importing data 2](https://www.datacamp.com/courses/importing-data-in-r-part-2)
-- [categorical data](https://www.datacamp.com/courses/categorical-data-in-the-tidyverse)
-- [dealing with missing data](https://www.datacamp.com/courses/dealing-with-missing-data-in-r)
+-   [Joining tables](https://www.datacamp.com/courses/joining-data-in-r-with-dplyr)
+-   [writing functions](https://www.datacamp.com/courses/writing-functions-in-r)
+-   [importing data 1](https://www.datacamp.com/courses/importing-data-in-r-part-1)
+-   [importing data 2](https://www.datacamp.com/courses/importing-data-in-r-part-2)
+-   [categorical data](https://www.datacamp.com/courses/categorical-data-in-the-tidyverse)
+-   [dealing with missing data](https://www.datacamp.com/courses/dealing-with-missing-data-in-r)
 
 ### Books and chapters
 
-- [Chapters 17-21 in R for Data Science](https://r4ds.had.co.nz/program-intro.html)
-- [Exploratory data analysis](https://bookdown.org/rdpeng/exdata/)
-- [R programming for data science](https://bookdown.org/rdpeng/rprogdatascience/)
+-   [Chapters 17-21 in R for Data Science](https://r4ds.had.co.nz/program-intro.html)
+-   [Exploratory data analysis](https://bookdown.org/rdpeng/exdata/)
+-   [R programming for data science](https://bookdown.org/rdpeng/rprogdatascience/)
 
-### Tutorials 
+### Tutorials
 
-- __Joining data__:
-  - [Two-table verbs](https://dplyr.tidyverse.org/articles/two-table.html)
-  - [Tutorial by Jenny Bryan](http://stat545.com/bit001_dplyr-cheatsheet.html)
-- [tidyexplain](https://github.com/gadenbuie/tidyexplain): Animations that illustrate how `gather()`, `spread()`, `left_join()`, etc. work
+-   **Joining data**:
+
+    -   [Two-table verbs](https://dplyr.tidyverse.org/articles/two-table.html)
+    -   [Tutorial by Jenny Bryan](http://stat545.com/bit001_dplyr-cheatsheet.html)
+
+-   [tidyexplain](https://github.com/gadenbuie/tidyexplain): Animations that illustrate how `pivot_longer()`, `pivot_wider()`, `left_join()`, etc. work
 
 ## Session info
 
-```{r data-wrangling2-47, echo=F}
+```{r, echo=F}
 sessionInfo()
 ```

06-probability.Rmd

@@ -1,12 +1,6 @@
 # Probability and causality
 
-## Install and load packages, load data, set theme
-
-Let's first install the new packages that you might not have yet. 
-
-```{r, eval=FALSE}
-install.packages(c("arrangements", "kableExtra", "DiagrammeR"))
-```
+## Load packages, load data, set theme
 
 Let's load the packages that we need for this chapter. 
 
@@ -434,22 +428,24 @@ df.rain_given_sprinkler_and_rain %>%
 
 ### Cheatsheets 
 
-- [Probability cheatsheet](figures/cheatsheets/probability.pdf)
+- [Probability cheatsheet](figures/probability.pdf)
 
 ### Books and chapters
 
 - [Probability and Statistics with examples using R](http://www.isibang.ac.in/~athreya/psweur/)
 - [Learning statistics with R: Chapter 9 Introduction to probability](https://learningstatisticswithr-bookdown.netlify.com/probability.html#probstats)
-- [Elements of causal inference; pdf of book can be downloaded for free](https://mitpress.mit.edu/books/elements-causal-inference)
 
 ### Misc 
 
+- [Bayes' theorem in three panels](https://www.tjmahr.com/bayes-theorem-in-three-panels/)
 - [Statistics 110: Probability; course at Harvard](https://projects.iq.harvard.edu/stat110)  
-- [Causal Diagrams: Draw Your Assumptions Before Your Conclusions; Free online course on causal inference](https://www.edx.org/course/causal-diagrams-draw-your-assumptions-before-your)
-- [An introduction to Causal inference; Excellent blog post on causal inference](https://fabiandablander.com/r/Causal-Inference.html)
+- [Bayes theorem and making probability intuitive](https://www.youtube.com/watch?v=HZGCoVF3YvM&feature=youtu.be)
+- [Causal inference with Bayes rule](https://gradientinstitute.org/blog/6/)
+
+## Session info 
 
-## Session info
+Information about this R session including which version of R was used, and what packages were loaded. 
 
-```{r probability-21, echo=F}
+```{r, echo=F}
 sessionInfo()
 ```