Project_1
AZM
2022-10-29
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With all the focus on mainting and developing stem tallent, I’ve always wanted to see if STEM degrees commend a price premium.
In terms of defintion of a STEM degree, I’ll be using DHS’s STEM CIPs Code List (Found here: https://www.ice.gov/doclib/sevis/pdf/stemList2022.pdf)
In addition I will crosswalk the Major Code to CIPs using a crosswalk table defined in: https://forum.ipums.org/t/crosswalk-between-degfieldd-and-cip/4209
Which is allegedly sourced via the census Bureau.
Data Read In
url.data <- "https://raw.githubusercontent.com/fivethirtyeight/data/master/college-majors/all-ages.csv"
raw <- read.csv(url(url.data), header = TRUE,)
summary(raw)## Major_code Major Major_category Total
## Min. :1100 Length:173 Length:173 Min. : 2396
## 1st Qu.:2403 Class :character Class :character 1st Qu.: 24280
## Median :3608 Mode :character Mode :character Median : 75791
## Mean :3880 Mean : 230257
## 3rd Qu.:5503 3rd Qu.: 205763
## Max. :6403 Max. :3123510
## Employed Employed_full_time_year_round Unemployed
## Min. : 1492 Min. : 1093 Min. : 0
## 1st Qu.: 17281 1st Qu.: 12722 1st Qu.: 1101
## Median : 56564 Median : 39613 Median : 3619
## Mean : 166162 Mean : 126308 Mean : 9725
## 3rd Qu.: 142879 3rd Qu.: 111025 3rd Qu.: 8862
## Max. :2354398 Max. :1939384 Max. :147261
## Unemployment_rate Median P25th P75th
## Min. :0.00000 Min. : 35000 Min. :24900 Min. : 45800
## 1st Qu.:0.04626 1st Qu.: 46000 1st Qu.:32000 1st Qu.: 70000
## Median :0.05472 Median : 53000 Median :36000 Median : 80000
## Mean :0.05736 Mean : 56816 Mean :38697 Mean : 82506
## 3rd Qu.:0.06904 3rd Qu.: 65000 3rd Qu.:42000 3rd Qu.: 95000
## Max. :0.15615 Max. :125000 Max. :78000 Max. :210000glimpse(raw)## Rows: 173
## Columns: 11
## $ Major_code <int> 1100, 1101, 1102, 1103, 1104, 1105, 1106…
## $ Major <chr> "GENERAL AGRICULTURE", "AGRICULTURE PROD…
## $ Major_category <chr> "Agriculture & Natural Resources", "Agri…
## $ Total <int> 128148, 95326, 33955, 103549, 24280, 794…
## $ Employed <int> 90245, 76865, 26321, 81177, 17281, 63043…
## $ Employed_full_time_year_round <int> 74078, 64240, 22810, 64937, 12722, 51077…
## $ Unemployed <int> 2423, 2266, 821, 3619, 894, 2070, 264, 2…
## $ Unemployment_rate <dbl> 0.02614711, 0.02863606, 0.03024832, 0.04…
## $ Median <int> 50000, 54000, 63000, 46000, 62000, 50000…
## $ P25th <int> 34000, 36000, 40000, 30000, 38500, 35000…
## $ P75th <dbl> 80000, 80000, 98000, 72000, 90000, 75000…Cases
There are 173 cases in this data set. This data is mostly summaries effectively grouped buy the major code
Type of Study
This is an observational study.
Data Sourcing
There are 3 priary resources:
Data 538-https://raw.githubusercontent.com/fivethirtyeight/data/master/college-majors/all-ages.csv U.S. Census-Crosswalk table-https://forum.ipums.org/t/crosswalk-between-degfieldd-and-cip/4209 DHS-https://www.ice.gov/doclib/sevis/pdf/stemList2022.pdf
Response Variable
The Response variable is the classification of the CIP code (Ie STEM or not STEM)
Explanatory Variable
The Explanatory variable is the income rate, and its numerical.
Summary Stats
summary(raw)## Major_code Major Major_category Total
## Min. :1100 Length:173 Length:173 Min. : 2396
## 1st Qu.:2403 Class :character Class :character 1st Qu.: 24280
## Median :3608 Mode :character Mode :character Median : 75791
## Mean :3880 Mean : 230257
## 3rd Qu.:5503 3rd Qu.: 205763
## Max. :6403 Max. :3123510
## Employed Employed_full_time_year_round Unemployed
## Min. : 1492 Min. : 1093 Min. : 0
## 1st Qu.: 17281 1st Qu.: 12722 1st Qu.: 1101
## Median : 56564 Median : 39613 Median : 3619
## Mean : 166162 Mean : 126308 Mean : 9725
## 3rd Qu.: 142879 3rd Qu.: 111025 3rd Qu.: 8862
## Max. :2354398 Max. :1939384 Max. :147261
## Unemployment_rate Median P25th P75th
## Min. :0.00000 Min. : 35000 Min. :24900 Min. : 45800
## 1st Qu.:0.04626 1st Qu.: 46000 1st Qu.:32000 1st Qu.: 70000
## Median :0.05472 Median : 53000 Median :36000 Median : 80000
## Mean :0.05736 Mean : 56816 Mean :38697 Mean : 82506
## 3rd Qu.:0.06904 3rd Qu.: 65000 3rd Qu.:42000 3rd Qu.: 95000
## Max. :0.15615 Max. :125000 Max. :78000 Max. :210000Pretty Charts
mean <- mean(raw$Median)
sd <- sd(raw$Median)
ggplot(data = raw, aes(x = Median)) +
geom_blank() +
geom_histogram(aes(y = ..density..)) +
stat_function(fun = dnorm, args = c(mean = mean, sd = sd), col = "tomato")## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.