make materials for classes 11, 12, and 13 available

_freeze/problem-sets/ps-10/execute-results/html.json

@@ -0,0 +1,15 @@
+{
+  "hash": "a6352b4b43855cb24b2f76516def7003",
+  "result": {
+    "engine": "knitr",
+    "markdown": "---\ntitle: \"Problem Set Stats Bootcamp - class 10\"\nsubtitle: \"Stats intro and history\"\nauthor: \"Neelanjan Mukherjee\"\ndate: last-modified\n---\n\n::: {.cell}\n::: {.cell-output .cell-output-stderr}\n\n```\n── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──\n✔ dplyr     1.1.4     ✔ readr     2.1.5\n✔ forcats   1.0.0     ✔ stringr   1.5.1\n✔ ggplot2   3.5.1     ✔ tibble    3.2.1\n✔ lubridate 1.9.3     ✔ tidyr     1.3.1\n✔ purrr     1.0.2     \n── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──\n✖ dplyr::filter() masks stats::filter()\n✖ dplyr::lag()    masks stats::lag()\nℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors\n\nAttaching package: 'cowplot'\n\n\nThe following object is masked from 'package:lubridate':\n\n    stamp\n```\n\n\n:::\n:::\n\n\n\n\n## Explore coin flip distribution characteristics\n\nWhen we flip a fair coin multiple times (`numFlips`) in a row, we expect to get heads (or tails) 50% of the time on average. This is not always the case for a single round of flipping, but if we do multiple rounds with (`numRounds`) that average should be 50%.\n\n## Problem \\# 1\n\nIn class, we simulated coin flip experiments using two different coins that were either fair (0.5 prob of head) or unfair (0.9 prob of head). We varied the number of flips in a single round (`numFlips`) and the number of rounds of flipping (`numRounds`). For this assignment, use the same to coins and use all possible combinations of `numFlips` and `numRounds` from the table below. Make sure to `set.seed(9)` if you want to get the same results as in the answer key.\n\n| `numFlips` | `numRounds` |\n|------------|-------------|\n| 5          | 10          |\n| 500        | 100         |\n\n: parameters to explore\n\n1.  Create a function called `flippy` that allows your to set `numFlips`, `numRounds`, and `prob` of H.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nflippy <- function(nFlip, nRound, myProb) {\n}\n```\n:::\n\n\n\n\n2.  Plot your result. There should be 4 plots total. Create a 2x2 grid by using `faceting`.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# we want 5 and 500 flips\n\n# we want to do 10 rounds\n\n# we want to do 100 rounds\n\n# combine data and tidy\n\n# plot and facet\n```\n:::\n\n\n\n\nDescribe (couple sentences) how increasing `numFlips` and `numRounds` alters:\n\n3\\. The estimation of the true mean.\n\n4\\. The spread around the true mean.\n\n## Problem \\# 2\n\nWe have seen that scientists played a major role in the eugenics movement, which greatly influenced society through policies. Explore the \\[eugenics archive\\](https://www.eugenicsarchive.ca/), pick on event from the `timeline` or the `connections` section. Describe what happened in a couple sentences and your thoughts on the matter in another couple sentences. Alternatively, you can identify events in Colorado history to describe and comment on. Obviously, there is no wrong answer here. I may pick some of your responses and anonymously share them with the rest of the class.\n",
+    "supporting": [],
+    "filters": [
+      "rmarkdown/pagebreak.lua"
+    ],
+    "includes": {},
+    "engineDependencies": {},
+    "preserve": {},
+    "postProcess": true
+  }
+}

slides/_slides-11.qmd → slides/slides-11.qmd

@@ -382,7 +382,7 @@ mean
 #| echo: true
 #| output-location: column-fragment
 
-mean(p$body_mass_g)
+mn=mean(p$body_mass_g)
 ```
 
 . . .
@@ -393,7 +393,7 @@ median
 #| echo: true
 #| output-location: column-fragment
 
-median(p$body_mass_g)
+md=median(p$body_mass_g)
 ```
 
 ------------------------------------------------------------------------
@@ -406,8 +406,8 @@ ggplot(
   aes(x = body_mass_g)
 ) +
   geom_density() +
-  #  geom_vline() +
-  #  geom_vline() +
+    geom_vline(xintercept = mn,color="red") +
+    geom_vline(xintercept = md,color="blue") +
   theme_cowplot()
 ```