Update Quiz0 wrap and R review

_freeze/schedule/slides/00-quiz-0-wrap/execute-results/html.json

@@ -1,7 +1,8 @@
 {
-  "hash": "00096b6cfd1ad274a2aab231017fbef6",
+  "hash": "a182d4c0edef7dd0c7f534c6ee0aa900",
   "result": {
-    "markdown": "---\nlecture: \"00 Quiz 0 fun\"\nformat: revealjs\nmetadata-files: \n  - _metadata.yml\n---\n---\n---\n\n## {{< meta lecture >}} {.large background-image=\"gfx/smooths.svg\" background-opacity=\"0.3\"}\n\n[Stat 406]{.secondary}\n\n[{{< meta author >}}]{.secondary}\n\nLast modified -- 13 September 2023\n\n\n\n$$\n\\DeclareMathOperator*{\\argmin}{argmin}\n\\DeclareMathOperator*{\\argmax}{argmax}\n\\DeclareMathOperator*{\\minimize}{minimize}\n\\DeclareMathOperator*{\\maximize}{maximize}\n\\DeclareMathOperator*{\\find}{find}\n\\DeclareMathOperator{\\st}{subject\\,\\,to}\n\\newcommand{\\E}{E}\n\\newcommand{\\Expect}[1]{\\E\\left[ #1 \\right]}\n\\newcommand{\\Var}[1]{\\mathrm{Var}\\left[ #1 \\right]}\n\\newcommand{\\Cov}[2]{\\mathrm{Cov}\\left[#1,\\ #2\\right]}\n\\newcommand{\\given}{\\ \\vert\\ }\n\\newcommand{\\X}{\\mathbf{X}}\n\\newcommand{\\x}{\\mathbf{x}}\n\\newcommand{\\y}{\\mathbf{y}}\n\\newcommand{\\P}{\\mathcal{P}}\n\\newcommand{\\R}{\\mathbb{R}}\n\\newcommand{\\norm}[1]{\\left\\lVert #1 \\right\\rVert}\n\\newcommand{\\snorm}[1]{\\lVert #1 \\rVert}\n$$\n\n\n\n\n\n## Why this class?\n\n* Most say requirements.\n* Interest in ML/Stat learning\n* Expressions of love/affection for Stats/CS/ML\n* Enjoyment of past similar classes\n\n## Why this class?\n\nMore idiosyncratic:\n\n::: incremental\n\n- \"Professor received Phd from CMU, must be an awesome  researcher.\"\n- \"Learn strategies.\"\n- (paraphrase) \"Course structure with less weight on exam helps with anxiety\"\n- (paraphrase) \"I love coding in R and want more of it\"\n- \"Emmmmmmmmmmmmmmmm, to learn some skills from Machine Learning and finish my minor🙃.\"\n- \"destiny\"\n- \"challenges from ChatGPT\"\n- \"I thought Daniel Mcdonald is a cool prof...\"\n- \"I have heard this is the most useful stat course in UBC.\"\n\n:::\n\n\n## Syllabus Q\n\n\n\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![](00-quiz-0-wrap_files/figure-revealjs/unnamed-chunk-1-1.svg){fig-align='center'}\n:::\n:::\n\n\n\n## Programming languages\n\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![](00-quiz-0-wrap_files/figure-revealjs/unnamed-chunk-2-1.svg){fig-align='center'}\n:::\n:::\n\n\n---\n\n## Matrix inversion\n\n\n::: {.cell layout-align=\"center\"}\n\n```{.r .cell-code}\nlibrary(MASS)\nX <- matrix(c(5, 3, 1, -1), nrow = 2)\nX\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n     [,1] [,2]\n[1,]    5    1\n[2,]    3   -1\n```\n:::\n\n```{.r .cell-code}\nsolve(X)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n      [,1]   [,2]\n[1,] 0.125  0.125\n[2,] 0.375 -0.625\n```\n:::\n\n```{.r .cell-code}\nginv(X)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n      [,1]   [,2]\n[1,] 0.125  0.125\n[2,] 0.375 -0.625\n```\n:::\n\n```{.r .cell-code}\nX^(-1)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n          [,1] [,2]\n[1,] 0.2000000    1\n[2,] 0.3333333   -1\n```\n:::\n:::\n\n\n\n\n## Linear models\n\n\n::: {.cell layout-align=\"center\"}\n\n```{.r .cell-code}\ny <- X %*% c(2, -1) + rnorm(2)\ncoefficients(lm(y ~ X))\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n(Intercept)          X1          X2 \n  4.8953718   0.9380314          NA \n```\n:::\n\n```{.r .cell-code}\ncoef(lm(y ~ X))\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n(Intercept)          X1          X2 \n  4.8953718   0.9380314          NA \n```\n:::\n\n```{.r .cell-code}\nsolve(t(X) %*% X) %*% t(X) %*% y\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n          [,1]\n[1,]  2.161874\n[2,] -1.223843\n```\n:::\n\n```{.r .cell-code}\nsolve(crossprod(X), crossprod(X, y))\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n          [,1]\n[1,]  2.161874\n[2,] -1.223843\n```\n:::\n:::\n\n::: {.cell layout-align=\"center\"}\n\n```{.r .cell-code}\nX \\ y # this is Matlab\n```\n\n::: {.cell-output .cell-output-error}\n```\nError: <text>:1:3: unexpected '\\\\'\n1: X \\\n      ^\n```\n:::\n:::\n\n\n\n## Pets and plans\n\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![](00-quiz-0-wrap_files/figure-revealjs/unnamed-chunk-6-1.svg){fig-align='center'}\n:::\n:::\n\n\n---\n\n## Grade predictions\n\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![](00-quiz-0-wrap_files/figure-revealjs/unnamed-chunk-7-1.svg){fig-align='center'}\n:::\n:::\n\n\n* 4 people say 100%\n* 24 say 90%\n* 25 say 85%\n* 27 say 80%\n* Lots of clumping\n\n\n. . .\n\n1 said 35, and 1 said 50. Woof!\n\n## Prediction accuracy (last year)\n\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![](00-quiz-0-wrap_files/figure-revealjs/unnamed-chunk-8-1.svg){fig-align='center'}\n:::\n:::\n\n\n## Prediction accuracy (last year)\n\n\n::: {.cell layout-align=\"center\"}\n\n```{.r .cell-code}\nsummary(lm(actual ~ predicted - 1, data = acc))\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n\nCall:\nlm(formula = actual ~ predicted - 1, data = acc)\n\nResiduals:\n    Min      1Q  Median      3Q     Max \n-63.931  -2.931   1.916   6.052  21.217 \n\nCoefficients:\n          Estimate Std. Error t value Pr(>|t|)    \npredicted  0.96590    0.01025   94.23   <2e-16 ***\n---\nSignif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n\nResidual standard error: 10.2 on 137 degrees of freedom\n  (8 observations deleted due to missingness)\nMultiple R-squared:  0.9848,\tAdjusted R-squared:  0.9847 \nF-statistic:  8880 on 1 and 137 DF,  p-value: < 2.2e-16\n```\n:::\n:::\n",
+    "engine": "knitr",
+    "markdown": "---\nlecture: \"00 Quiz 0 fun\"\nformat: revealjs\nmetadata-files: \n  - _metadata.yml\n---\n\n\n## {{< meta lecture >}} {.large background-image=\"gfx/smooths.svg\" background-opacity=\"0.3\"}\n\n[Stat 406]{.secondary}\n\n[{{< meta author >}}]{.secondary}\n\nLast modified -- 10 September 2024\n\n\n\n\n\n$$\n\\DeclareMathOperator*{\\argmin}{argmin}\n\\DeclareMathOperator*{\\argmax}{argmax}\n\\DeclareMathOperator*{\\minimize}{minimize}\n\\DeclareMathOperator*{\\maximize}{maximize}\n\\DeclareMathOperator*{\\find}{find}\n\\DeclareMathOperator{\\st}{subject\\,\\,to}\n\\newcommand{\\E}{E}\n\\newcommand{\\Expect}[1]{\\E\\left[ #1 \\right]}\n\\newcommand{\\Var}[1]{\\mathrm{Var}\\left[ #1 \\right]}\n\\newcommand{\\Cov}[2]{\\mathrm{Cov}\\left[#1,\\ #2\\right]}\n\\newcommand{\\given}{\\ \\vert\\ }\n\\newcommand{\\X}{\\mathbf{X}}\n\\newcommand{\\x}{\\mathbf{x}}\n\\newcommand{\\y}{\\mathbf{y}}\n\\newcommand{\\P}{\\mathcal{P}}\n\\newcommand{\\R}{\\mathbb{R}}\n\\newcommand{\\norm}[1]{\\left\\lVert #1 \\right\\rVert}\n\\newcommand{\\snorm}[1]{\\lVert #1 \\rVert}\n\\newcommand{\\tr}[1]{\\mbox{tr}(#1)}\n\\newcommand{\\brt}{\\widehat{\\beta}^R_{s}}\n\\newcommand{\\brl}{\\widehat{\\beta}^R_{\\lambda}}\n\\newcommand{\\bls}{\\widehat{\\beta}_{ols}}\n\\newcommand{\\blt}{\\widehat{\\beta}^L_{s}}\n\\newcommand{\\bll}{\\widehat{\\beta}^L_{\\lambda}}\n\\newcommand{\\U}{\\mathbf{U}}\n\\newcommand{\\D}{\\mathbf{D}}\n\\newcommand{\\V}{\\mathbf{V}}\n$$\n\n\n\n\n\n## Why this class?\n\n- \"This is a required course\"\n- \"Heard it's fun!\"\n- \"I want to graduate\"\n- \"8am!\" (/s)\n- \"I want to learn a lot about ML.\"\n- \"I want to dig deeper after taking 306.\"\n- \"I want to get... more comfortable with R.\"\n- \"At first it was because everyone I knew was taking it.\"\n- \"Practical skills in preperation for future careers\"\n\n\n## Syllabus Q\n\n\n\n\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![](00-quiz-0-wrap_files/figure-revealjs/unnamed-chunk-1-1.svg){fig-align='center'}\n:::\n:::\n\n\n\n\n## Programming languages\n\n\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![](00-quiz-0-wrap_files/figure-revealjs/unnamed-chunk-2-1.svg){fig-align='center'}\n:::\n:::\n\n\n\n<!--\n## Matrix inversion\n\n\n\n::: {.cell layout-align=\"center\"}\n\n```{.r .cell-code}\nlibrary(MASS)\nX <- matrix(c(5, 3, 1, -1), nrow = 2)\nX\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n     [,1] [,2]\n[1,]    5    1\n[2,]    3   -1\n```\n\n\n:::\n\n```{.r .cell-code}\nsolve(X)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n      [,1]   [,2]\n[1,] 0.125  0.125\n[2,] 0.375 -0.625\n```\n\n\n:::\n\n```{.r .cell-code}\nginv(X)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n      [,1]   [,2]\n[1,] 0.125  0.125\n[2,] 0.375 -0.625\n```\n\n\n:::\n\n```{.r .cell-code}\nX^(-1)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n          [,1] [,2]\n[1,] 0.2000000    1\n[2,] 0.3333333   -1\n```\n\n\n:::\n:::\n\n\n\n\n\n## Linear models\n\n\n\n::: {.cell layout-align=\"center\"}\n\n```{.r .cell-code}\ny <- X %*% c(2, -1) + rnorm(2)\ncoefficients(lm(y ~ X))\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n(Intercept)          X1          X2 \n  4.8953718   0.9380314          NA \n```\n\n\n:::\n\n```{.r .cell-code}\ncoef(lm(y ~ X))\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n(Intercept)          X1          X2 \n  4.8953718   0.9380314          NA \n```\n\n\n:::\n\n```{.r .cell-code}\nsolve(t(X) %*% X) %*% t(X) %*% y\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n          [,1]\n[1,]  2.161874\n[2,] -1.223843\n```\n\n\n:::\n\n```{.r .cell-code}\nsolve(crossprod(X), crossprod(X, y))\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n          [,1]\n[1,]  2.161874\n[2,] -1.223843\n```\n\n\n:::\n:::\n\n::: {.cell layout-align=\"center\"}\n\n```{.r .cell-code}\nX \\ y # this is Matlab\n```\n\n::: {.cell-output .cell-output-error}\n\n```\nError: <text>:1:3: unexpected '\\\\'\n1: X \\\n      ^\n```\n\n\n:::\n:::\n\n---\n-->\n\n## Plans\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![](00-quiz-0-wrap_files/figure-revealjs/unnamed-chunk-6-1.svg){fig-align='center'}\n:::\n:::\n\n## Grade predictions\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![](00-quiz-0-wrap_files/figure-revealjs/unnamed-chunk-7-1.svg){fig-align='center'}\n:::\n:::\n\n* 5 people say 100%\n* 18 say 90%\n* 20 say 85%\n* 41 say 80%\n",
     "supporting": [
       "00-quiz-0-wrap_files"
     ],

schedule/slides/00-quiz-0-wrap.qmd

@@ -10,46 +10,31 @@ metadata-files:
 
 ## Why this class?
 
-* Most say requirements.
-* Interest in ML/Stat learning
-* Expressions of love/affection for Stats/CS/ML
-* Enjoyment of past similar classes
-
-## Why this class?
-
-More idiosyncratic:
-
-::: incremental
-
-- "Professor received Phd from CMU, must be an awesome  researcher."
-- "Learn strategies."
-- (paraphrase) "Course structure with less weight on exam helps with anxiety"
-- (paraphrase) "I love coding in R and want more of it"
-- "Emmmmmmmmmmmmmmmm, to learn some skills from Machine Learning and finish my minor🙃."
-- "destiny"
-- "challenges from ChatGPT"
-- "I thought Daniel Mcdonald is a cool prof..."
-- "I have heard this is the most useful stat course in UBC."
-
-:::
+- "This is a required course"
+- "Heard it's fun!"
+- "I want to graduate"
+- "8am!" (/s)
+- "I want to learn a lot about ML."
+- "I want to dig deeper after taking 306."
+- "I want to get... more comfortable with R."
+- "At first it was because everyone I knew was taking it."
+- "Practical skills in preperation for future careers"
 
 
 ## Syllabus Q
 
 ```{r load-quiz, include=FALSE}
-quiz <- read_rds(here::here(
-  "..", "..", "..", "WinterT1-2023", "gh-class-management", "lab0",
-  "lab0-anon.rds"
-))
+library(tidyverse)
+quiz <- tibble(read.csv("canvas_quiz0.csv"))
 ```
 
 ```{r}
 #| echo: false
 #| fig-height: 6
 #| fig-width: 12
 quiz |> 
-  ggplot(aes(str_wrap(syllabus, 20))) + 
-  geom_bar(fill = blue) + 
+  ggplot(aes(str_wrap(syllabus_fact, 20))) + 
+  geom_bar(fill = "blue") + 
   scale_y_continuous(expand = expansion(c(0,0.05))) +
   xlab("") 
 ```
@@ -62,14 +47,13 @@ quiz |>
 #| fig-height: 6
 #| fig-width: 12
 quiz |> 
-  ggplot(aes(str_wrap(r_coding, 20))) + 
-  geom_bar(fill = blue) + 
+  ggplot(aes(str_wrap(r_experience, 20))) + 
+  geom_bar(fill = "blue") + 
   scale_y_continuous(expand = expansion(c(0, 0.05))) +
   xlab("")
 ```
 
----
-
+<!--
 ## Matrix inversion
 
 ```{r}
@@ -97,76 +81,40 @@ solve(crossprod(X), crossprod(X, y))
 #| error: true
 X \ y # this is Matlab
 ```
+---
+-->
 
-
-## Pets and plans
+## Plans
 
 ```{r}
 #| echo: false
 #| fig-height: 6
 #| fig-width: 12
 library(cowplot)
-p1 <- quiz %>%
-  ggplot(aes(str_wrap(pets, 30))) +
-  geom_bar(fill = blue) +
-  coord_flip() +
-  scale_y_continuous(expand = expansion(c(0, 0.05))) +
-  xlab("")
-p2 <- quiz %>%
-  ggplot(aes(str_wrap(plans, 20))) +
-  geom_bar(fill = orange) +
-  coord_flip() +
+
+quiz %>%
+  ggplot(aes(str_wrap(graduation_plans, 20))) +
+  geom_bar(fill = "orange") +
   scale_y_continuous(expand = expansion(c(0, 0.05))) +
   xlab("")
-plot_grid(p1, p2)
 ```
 
----
-
 ## Grade predictions
 
 ```{r, echo=FALSE, fig.height=4, fig.width=12, fig.align='center'}
 #| echo: false
 #| fig-height: 4
 #| fig-width: 12
 quiz |>
-  ggplot(aes(grade)) +
+  ggplot(aes(predicted_grade)) +
   geom_histogram(
-    fill = orange, colour = "black", 
+    fill = "orange", colour = "black", 
     breaks = c(0, 50, 54, 59, 63, 67, 71, 75, 79, 84, 89, 101)
   ) +
   scale_y_continuous(expand = expansion(c(0, 0.05)))
 ```
 
-* `r sum(quiz$grade == 100)` people say 100%
-* `r sum(quiz$grade == 90)` say 90%
-* `r sum(quiz$grade == 85)` say 85%
-* `r sum(quiz$grade == 80)` say 80%
-* Lots of clumping
-
-
-. . .
-
-1 said 35, and 1 said 50. Woof!
-
-## Prediction accuracy (last year)
-
-```{r}
-#| echo: false
-acc <- read_rds(here::here(
-  "..", "..", "..", "WinterT1-2022", "final-grades",
-  "prediction-accuracy.rds"
-)) |>
-  rename(predicted = pfg, actual = fg)
-
-ggplot(acc, aes(predicted, actual)) +
-  geom_point(colour = orange) +
-  geom_abline(slope = 1, intercept = 0) +
-  coord_equal(xlim = c(0, 100), ylim = c(0, 100))
-```
-
-## Prediction accuracy (last year)
-
-```{r}
-summary(lm(actual ~ predicted - 1, data = acc))
-```
+* `r sum(quiz$predicted_grade == 100)` people say 100%
+* `r sum(quiz$predicted_grade == 90)` say 90%
+* `r sum(quiz$predicted_grade == 85)` say 85%
+* `r sum(quiz$predicted_grade == 80)` say 80%

schedule/slides/00-r-review.qmd

@@ -514,6 +514,8 @@ fun <- function(x) {
 fun(14)
 ```
 
+. . .
+
 Non-trivial cases are `data-masking` environments.
 
 ```{r}
@@ -614,13 +616,23 @@ What you need is a Reproducible Example or `reprex`.
 * This is a small chunk of code that 
     1. runs in it's own environment 
     1. and produces the error.
-
-#
 
-The best way to do this is with the `{reprex}` package.
 
+---
+
+::: flex
+::: w-50
+![](gfx/reprex_github_1.png){fig-align="center" fig-alt="Reprex example 1"}
+:::
+
+::: w-50
+![](gfx/reprex_github_2.png){fig-align="center" fig-alt="Reprex example 2"}
+:::
+:::
+
+
+## The `{reprex}` package
 
-## Reproducible examples, How it works {.smaller}
 
 1. Open a new `.R` script.
 
@@ -658,6 +670,8 @@ Because Reprex runs in it's own environment, it doesn't have access to any of th
     - lacking basic data types (e.g., hash maps)
     - informal classes (`class(x) <- "a weird new class!"`)
     - tonnes of functions/data/objects in the global namespace
+    - `3 == "3"` (evaluates to TRUE?!!?!)
+    - (Somehow R is weirder than [Javascript](https://www.facebook.com/BangaloreRocks/videos/wat-a-lightning-talk-by-gary-bernhardt-from-codemash-2012/10150507601498579/))
 - Rscript executable treats code *differently than the R REPL*
 
 # Understanding `{tidyverse}`
@@ -795,6 +809,7 @@ This technically works...but at a minimum it makes it hard to extend pipe sequen
 
 
 
+<!--
 ## A new one...
 
 R loves weird pipes. Just stick to `|>`, it results in clear code.
@@ -809,7 +824,7 @@ tib <- tibble(x = 1:5, z = 6:10)
 tib %<>% mutate(b = x + z)
 tib
 ```
-
+-->
 
 
 ## Data processing in `{dplyr}` {.smaller}