From 28794ae5a0215186a165c7001c0c3ed8a00de4ea Mon Sep 17 00:00:00 2001 From: "Alan T. Arnholt" Date: Sat, 24 Aug 2024 10:30:22 -0400 Subject: [PATCH] tweaks --- PS05_source.html | 59 +++++++++--------- PS05_source.qmd | 47 +++++++------- PS05_source_files/figure-html/fig-extra-1.png | Bin 43469 -> 42116 bytes 3 files changed, 53 insertions(+), 53 deletions(-) diff --git a/PS05_source.html b/PS05_source.html index cb8d320..550acfb 100644 --- a/PS05_source.html +++ b/PS05_source.html @@ -100,7 +100,7 @@

Problem Set 05: Regression with One Categorical Variable

Published
-

Last modified on August 07, 2023 17:01:47 Eastern Daylight Time

+

Last modified on August 24, 2024 10:29:36 Eastern Daylight Time

@@ -466,8 +466,8 @@

Hate Crimes and Trump Support

Below we calculate the group means of hate crimes for the high, medium and low levels of Trump support. How do these numbers compare to the three possible fitted values \(\widehat{y}\) for this model?

-
hate_crimes %>% 
-group_by(trump_support) %>% 
+
hate_crimes |> 
+group_by(trump_support) |> 
   summarize(mean_hate_crimes = mean(hate_crimes, na.rm = TRUE))
# A tibble: 3 × 2
@@ -970,7 +970,7 @@ 

EXTRA

# Reordering trump_support
 library(forcats)
-hate_crimes <- hate_crimes %>% 
+hate_crimes <- hate_crimes |> 
   mutate(trump_support = fct_relevel(trump_support, 
             "low", "medium", "high"))
 ggplot(data = hate_crimes, aes(x = trump_support, y = hate_crimes)) + 
@@ -1035,12 +1035,12 @@ 

Logging out of the Server

sessionInfo()
-
R version 4.2.3 (2023-03-15)
-Platform: x86_64-pc-linux-gnu (64-bit)
-Running under: Red Hat Enterprise Linux 9.2 (Plow)
+
R version 4.4.1 (2024-06-14)
+Platform: x86_64-redhat-linux-gnu
+Running under: Red Hat Enterprise Linux 9.4 (Plow)
 
 Matrix products: default
-BLAS/LAPACK: /usr/lib64/libopenblasp-r0.3.21.so
+BLAS/LAPACK: FlexiBLAS OPENBLAS-OPENMP;  LAPACK version 3.9.0
 
 locale:
  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
@@ -1050,32 +1050,35 @@ 

Logging out of the Server

[9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C +time zone: America/New_York +tzcode source: system (glibc) + attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: -[1] forcats_1.0.0 readr_2.1.4 moderndive_0.5.5 dplyr_1.1.2 -[5] ggplot2_3.4.2 knitr_1.43 +[1] forcats_1.0.0 readr_2.1.5 moderndive_0.6.1 dplyr_1.1.4 +[5] ggplot2_3.5.1 knitr_1.48 loaded via a namespace (and not attached): - [1] tidyselect_1.2.0 xfun_0.39 janitor_2.2.0 - [4] purrr_1.0.1 operator.tools_1.6.3 snakecase_0.11.0 - [7] colorspace_2.1-0 vctrs_0.6.3 generics_0.1.3 -[10] htmltools_0.5.5 yaml_2.3.7 utf8_1.2.3 -[13] rlang_1.1.1 pillar_1.9.0 glue_1.6.2 -[16] withr_2.5.0 infer_1.0.4 bit64_4.0.5 -[19] lifecycle_1.0.3 stringr_1.5.0 munsell_0.5.0 -[22] gtable_0.3.3 htmlwidgets_1.6.2 evaluate_0.21 -[25] labeling_0.4.2 tzdb_0.4.0 fastmap_1.1.1 -[28] parallel_4.2.2 fansi_1.0.4 broom_1.0.5 -[31] backports_1.4.1 scales_1.2.1 vroom_1.6.3 -[34] jsonlite_1.8.7 farver_2.1.1 bit_4.0.5 -[37] hms_1.1.3 digest_0.6.33 stringi_1.7.12 -[40] formula.tools_1.7.1 grid_4.2.2 cli_3.6.1 -[43] tools_4.2.2 magrittr_2.0.3 tibble_3.2.1 -[46] crayon_1.5.2 tidyr_1.3.0 pkgconfig_2.0.3 -[49] lubridate_1.9.2 timechange_0.2.0 rmarkdown_2.23 -[52] rstudioapi_0.15.0 R6_2.5.1 compiler_4.2.2
+ [1] utf8_1.2.4 generics_0.1.3 tidyr_1.3.1 + [4] stringi_1.8.4 hms_1.1.3 digest_0.6.36 + [7] magrittr_2.0.3 evaluate_0.24.0 grid_4.4.1 +[10] timechange_0.3.0 fastmap_1.2.0 operator.tools_1.6.3 +[13] jsonlite_1.8.8 backports_1.5.0 purrr_1.0.2 +[16] fansi_1.0.6 scales_1.3.0 infer_1.0.7 +[19] cli_3.6.3 rlang_1.1.4 crayon_1.5.3 +[22] bit64_4.0.5 munsell_0.5.1 withr_3.0.1 +[25] yaml_2.3.10 tools_4.4.1 parallel_4.4.1 +[28] tzdb_0.4.0 colorspace_2.1-1 broom_1.0.6 +[31] vctrs_0.6.5 R6_2.5.1 lifecycle_1.0.4 +[34] lubridate_1.9.3 snakecase_0.11.1 stringr_1.5.1 +[37] htmlwidgets_1.6.4 bit_4.0.5 vroom_1.6.5 +[40] janitor_2.2.0 pkgconfig_2.0.3 pillar_1.9.0 +[43] gtable_0.3.5 glue_1.7.0 xfun_0.47 +[46] tibble_3.2.1 tidyselect_1.2.1 rstudioapi_0.16.0 +[49] farver_2.1.2 htmltools_0.5.8.1 labeling_0.4.3 +[52] rmarkdown_2.28 formula.tools_1.7.1 compiler_4.4.1
diff --git a/PS05_source.qmd b/PS05_source.qmd index efe8795..af77e7b 100644 --- a/PS05_source.qmd +++ b/PS05_source.qmd @@ -6,7 +6,7 @@ date-format: "[Last modified on] MMMM DD, YYYY HH:mm:ss zzz" format: html: default pdf: default -editor: visual +editor: source --- ```{r include = FALSE} @@ -89,7 +89,7 @@ Create a visual model of these data (a graph) that will allow you to conduct an ::: ::: {.callout-important icon="false" collapse="false" title="Problem 2 Answers"} -* Delete this and put your text answer here. +- Delete this and put your text answer here. ::: ::: {.callout-note icon="false" title="Problem 3"} @@ -108,7 +108,7 @@ What does the intercept mean in this regression table? ::: ::: {.callout-important icon="false" collapse="false" title="Problem 4 Answers"} -* Delete this and put your text answer here. +- Delete this and put your text answer here. ::: ::: {.callout-note icon="false" title="Problem 5"} @@ -116,7 +116,7 @@ What does the model estimate as the number of hate crimes per 100,000 people in ::: ::: {.callout-important icon="false" collapse="false" title="Problem 5 Answers"} -* Delete this and put your text answer here. +- Delete this and put your text answer here. ```{r} # Type your code and comments inside the code chunk @@ -134,7 +134,7 @@ Does the model estimate that hate crimes are more frequent in states that show " ``` -* Delete this and put your text answer here. +- Delete this and put your text answer here. ::: ::: {.callout-note icon="false" title="Problem 7"} @@ -147,7 +147,7 @@ How much greater were hate crimes in "medium" Trump-support states compared to " ``` -* Delete this and put your text answer here. +- Delete this and put your text answer here. ::: ::: {.callout-note icon="false" title="Problem 8"} @@ -160,25 +160,25 @@ What are the three possible fitted values $\hat{y}$ for this model? Hint: use th ``` -* Delete this and put your text answer here. +- Delete this and put your text answer here. -* Delete this and put your text answer here. +- Delete this and put your text answer here. -* Delete this and put your text answer here. +- Delete this and put your text answer here. ::: ::: {.callout-note icon="false" title="Problem 9"} Below we calculate the group means of hate crimes for the `high`, `medium` and `low` levels of Trump support. How do these numbers compare to the three possible fitted values $\widehat{y}$ for this model? ```{r} -hate_crimes %>% -group_by(trump_support) %>% +hate_crimes |> +group_by(trump_support) |> summarize(mean_hate_crimes = mean(hate_crimes, na.rm = TRUE)) ``` ::: ::: {.callout-important icon="false" collapse="false" title="Problem 9 Answers"} -* Delete this and put your text answer here. +- Delete this and put your text answer here. ::: ## The Regression Equation @@ -189,7 +189,6 @@ The regression equation for this model is the following (render the document and hate_mod <- lm(hate_crimes ~ trump_support, data = hate_crimes) ``` - $$ \widehat{\text{hate\_crimes}} = `r coef(hate_mod)[1]` + `r coef(hate_mod)[2]` \times 1_{\text{low support}}(x) + `r coef(hate_mod)[3]` \times 1_{\text{med support}}(x) $$ @@ -233,14 +232,14 @@ Solve the regression equation for a state in which `trump_support` is "high". ::: ::: {.callout-important icon="false" collapse="false" title="Problem 10 Answers"} - Your $LaTeX$ here +Your $LaTeX$ here ```{r} # Type your code and comments inside the code chunk ``` -* Delete this and put your text answer here. +- Delete this and put your text answer here. ::: ::: {.callout-note icon="false" title="Problem 11"} @@ -255,7 +254,7 @@ Do these results surprise you? (There is no right answer to this question.) ``` -* Delete this and put your text answer here. +- Delete this and put your text answer here. ::: # Hate Crimes and Unemployment @@ -292,7 +291,6 @@ Write out the regression equation for `job_mod`. ::: ::: {.callout-important icon="false" collapse="false" title="Problem 14 Answers"} - Write your equation with $LaTeX$ here. ::: @@ -301,12 +299,11 @@ Interpret the estimate of the intercept from the table below. ::: ::: {.callout-important icon="false" collapse="false" title="Problem 15 Answers"} -* Delete this and put your text answer here. +- Delete this and put your text answer here. ::: ::: {.callout-note icon="false" title="Problem 16"} What does the model estimate the number of hate crimes per 100,000 people to be in a state with "low" unemployment? - ::: ::: {.callout-important icon="false" collapse="false" title="Problem 16 Answers"} @@ -315,7 +312,7 @@ What does the model estimate the number of hate crimes per 100,000 people to be ``` -* Delete this and put your text answer here. +- Delete this and put your text answer here. ::: ::: {.callout-note icon="false" title="Problem 17"} @@ -328,7 +325,7 @@ What are the two possible fitted values $\widehat{y}$ for this model? Why are th ``` -* Delete this and put your text answer here. +- Delete this and put your text answer here. ::: ::: {.callout-note icon="false" title="Problem 18"} @@ -341,7 +338,7 @@ Use the `get_regression_points()` function to generate a table showing the fitte ``` -* Delete this and put your text answer here. +- Delete this and put your text answer here. ::: # Hate Crimes and Household Income @@ -362,7 +359,7 @@ Were there more hate crimes in areas with high or low median household incomes? ::: ::: {.callout-important icon="false" collapse="false" title="Problem 20 Answers"} -* Delete this and put your text answer here. +- Delete this and put your text answer here. ::: ::: {.callout-note icon="false" title="Problem 21"} @@ -386,7 +383,7 @@ Take a look at data for Maine (row 2 of `hate_crimes`). Did the model (`job_med_ ``` -* Delete this and put your text answer here. +- Delete this and put your text answer here. ::: # **EXTRA** @@ -398,7 +395,7 @@ Take a look at data for Maine (row 2 of `hate_crimes`). 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