Attaching package: 'scales'
The following object is masked from 'package:purrr':
discard
The following object is masked from 'package:readr':
col_factor
Code
# Importing datasetsNYC_2019 <-read_csv("/Users/karenkimble/Documents/UMass/SPP/Fall 2022/DACSS 603/DACSS Final Project/NYC School Data/2018-2019_School_Demographic_Snapshot.csv", col_types =cols(`Grade PK (Half Day & Full Day)`=col_skip(), `# Multiple Race Categories Not Represented`=col_skip(), `% Multiple Race Categories Not Represented`=col_skip()))
Error: '/Users/karenkimble/Documents/UMass/SPP/Fall 2022/DACSS 603/DACSS Final Project/NYC School Data/2018-2019_School_Demographic_Snapshot.csv' does not exist.
Error in number(x = x, accuracy = accuracy, scale = scale, prefix = prefix, : object 'NYC_2019' not found
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NYC_2021 <-read_csv("/Users/karenkimble/Documents/UMass/SPP/Fall 2022/DACSS 603/DACSS Final Project/NYC School Data/2020-2021_Demographic_Snapshot_School.csv", col_types =cols(`Grade 3K+PK (Half Day & Full Day)`=col_skip(), `# Multi-Racial`=col_skip(), `% Multi-Racial`=col_skip(), `# Native American`=col_skip(), `% Native American`=col_skip(), `# Missing Race/Ethnicity Data`=col_skip(), `% Missing Race/Ethnicity Data`=col_skip()))
Error: '/Users/karenkimble/Documents/UMass/SPP/Fall 2022/DACSS 603/DACSS Final Project/NYC School Data/2020-2021_Demographic_Snapshot_School.csv' does not exist.
Code
# In order to bind the data, I had to remove columns that were not present in the other spreadsheet: Grade PK or 3K, Native American, the different multi-racial categories, and Missing Dataschool_data <-rbind(NYC_2019, NYC_2021)
Error in rbind(NYC_2019, NYC_2021): object 'NYC_2019' not found
Code
# Making values coded as "above 95%" to equal 95% and "below 5%" to equal 5% for the purposes of this analysisschool_data$`% Poverty`<-recode(school_data$`% Poverty`, "Above 95%"="95%", "Below 5%"="5%")
Error in recode(school_data$`% Poverty`, `Above 95%` = "95%", `Below 5%` = "5%"): object 'school_data' not found
Error in eval(expr, envir, enclos): object 'school_data' not found
Code
school_data$`Economic Need Index`<-as.numeric(school_data$`Economic Need Index`)
Error in eval(expr, envir, enclos): object 'school_data' not found
Research Question
The research question I want to explore is whether child poverty has increased in schools that are predominantly made up of non-white students from the 2014-2015 school year to the 2020-2021 school year. I think this is extremely important to look at because of the pandemic’s impact on not only child learning but also families’ economic resources. According to the Columbia University Center on Poverty and Social Policy, “nearly a quarter of children ages 0-3 live in poverty and nearly half of the city’s young children live in lower-opportunity neighborhoods where the poverty rate is at least 20 percent” (“Poverty”). Unfortunately, research shows that poverty is disproportionately felt according to one’s race or ethnicity. In New York State, as of 2021, child poverty among children of color is almost 30%, with Black or African American children more than twice as likely to live in poverty than White, Non-Hispanic children (“New York State”, 2021). With this disproportionate level of economic need in children of color, it seems important to investigate if the poverty level within New York City schools that are predominately non-White has increased significantly compared to schools that are predominantly White. When searching the UMass Libraries databases and other sources, it was hard to find studies that used this data in this way. It is important to understand if there is increasing poverty levels within an already vulnerable group.
Hypothesis
I hypothesize that the poverty rate in NYC schools that are predominantly children of color will have increased more between the 2014-2015 and the 2020-2021 school years than the poverty rate in schools that are predominantly White. Since I have not found many previous studies on this, it is hard to know if this hypothesis was tested before. However, this data is fairly recent and also relates to the pandemic’s effects on economics, so I think it is still a significant contribution to test this hypothesis.
Descriptive Statistics
A description and summary of your data. How was your data collected by its original collectors? What are the important variables of interest for your research question? Use functions like glimpse() and summary() to present your data.
The data was collected by New York City and put on its Open Data source. The data covers NYC schools in the academic years 2014-2015 to 2020-2021. The important variables of interest included in the data are:
Academic year
Number and percentage of Asisan, Black, Hispanic, and White students
Number and percentage of students in poverty
Economic need index, which is the average of students’ “Economic Need Values”
The Economic Need Index (ENI) estimates the percentage of students facing economic hardship
The other variables included are: DBN (district, borough, school number), school name, total enrollment, enrollment numbers for K-12, number and percentage of female and male students, number and percentage of students with disabilities, and number and percentage of English-Language Learner (ELL) students.
Code
glimpse(school_data)
Error in glimpse(school_data): object 'school_data' not found
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summary(school_data)
Error in summary(school_data): object 'school_data' not found
Code
# Note: the summary data for the enrollment numbers split by grade is somewhat off (especially minimums) because there is no variable listed for type of school (i.e., middle versus high school). So, for example, an elementary school would have an enrollment total of 0 for grade 12, which would show up as the minimum.
As we can see from this summary, the median percent of poverty in NYC schools (81.4%) is higher than the mean percent (75.89%), indicating that there may be low outliers with very low percentages of poverty. The same holds true for the Economic Need Index, with the mean (0.691) lower than the median (0.743). It is troubling, however, that both the mean and median percentages of poverty in NYC schools overall is more than three-fourths of the population.
References
New York State Child Poverty Facts. Schuyler Center for Analysis and Advocacy. (2021, February 18). Retrieved from https://scaany.org/wp-content/uploads/2021/02/NYS-Child-Poverty-Facts_Feb2021.pdf
Poverty in New York City. Columbia University Center on Poverty and Social Policy. (n.d.). Retrieved from https://www.povertycenter.columbia.edu/poverty-in-new-york-city#:~:text=Children%20and%20Families%20in%20New%20York%20City&text=Through%20surveys%2C%20we%20find%20that,is%20at%20least%2020%20percent.
Source Code
---title: "DACSS 603 Final Project - Proposal"desription: "First part of final project"date: "10/07/2022"format: html: toc: true code-fold: true code-copy: true code-tools: truecategory: finalpart1---```{r}# Setuplibrary(tidyverse)library(readr)library(scales)# Importing datasetsNYC_2019 <-read_csv("/Users/karenkimble/Documents/UMass/SPP/Fall 2022/DACSS 603/DACSS Final Project/NYC School Data/2018-2019_School_Demographic_Snapshot.csv", col_types =cols(`Grade PK (Half Day & Full Day)`=col_skip(), `# Multiple Race Categories Not Represented`=col_skip(), `% Multiple Race Categories Not Represented`=col_skip()))NYC_2019$`% Poverty`<-percent(NYC_2019$`% Poverty`, accuracy=0.1)NYC_2021 <-read_csv("/Users/karenkimble/Documents/UMass/SPP/Fall 2022/DACSS 603/DACSS Final Project/NYC School Data/2020-2021_Demographic_Snapshot_School.csv", col_types =cols(`Grade 3K+PK (Half Day & Full Day)`=col_skip(), `# Multi-Racial`=col_skip(), `% Multi-Racial`=col_skip(), `# Native American`=col_skip(), `% Native American`=col_skip(), `# Missing Race/Ethnicity Data`=col_skip(), `% Missing Race/Ethnicity Data`=col_skip()))# In order to bind the data, I had to remove columns that were not present in the other spreadsheet: Grade PK or 3K, Native American, the different multi-racial categories, and Missing Dataschool_data <-rbind(NYC_2019, NYC_2021)# Making values coded as "above 95%" to equal 95% and "below 5%" to equal 5% for the purposes of this analysisschool_data$`% Poverty`<-recode(school_data$`% Poverty`, "Above 95%"="95%", "Below 5%"="5%")# Re-coding variables as numericschool_data$`% Poverty`<-sapply(school_data$`% Poverty`, function(x) gsub("%", "", x))school_data$`% Poverty`<-as.numeric(school_data$`% Poverty`)school_data$`Economic Need Index`<-as.numeric(school_data$`Economic Need Index`)```## Research QuestionThe research question I want to explore is whether child poverty has increased in schools that are predominantly made up of non-white students from the 2014-2015 school year to the 2020-2021 school year. I think this is extremely important to look at because of the pandemic's impact on not only child learning but also families' economic resources. According to the Columbia University Center on Poverty and Social Policy, "nearly a quarter of children ages 0-3 live in poverty and nearly half of the city's young children live in lower-opportunity neighborhoods where the poverty rate is at least 20 percent" ("Poverty"). Unfortunately, research shows that poverty is disproportionately felt according to one's race or ethnicity. In New York State, as of 2021, child poverty among children of color is almost 30%, with Black or African American children more than twice as likely to live in poverty than White, Non-Hispanic children ("New York State", 2021). With this disproportionate level of economic need in children of color, it seems important to investigate if the poverty level within New York City schools that are predominately non-White has increased significantly compared to schools that are predominantly White. When searching the UMass Libraries databases and other sources, it was hard to find studies that used this data in this way. It is important to understand if there is increasing poverty levels within an already vulnerable group.## HypothesisI hypothesize that the poverty rate in NYC schools that are predominantly children of color will have increased more between the 2014-2015 and the 2020-2021 school years than the poverty rate in schools that are predominantly White. Since I have not found many previous studies on this, it is hard to know if this hypothesis was tested before. However, this data is fairly recent and also relates to the pandemic's effects on economics, so I think it is still a significant contribution to test this hypothesis.## Descriptive StatisticsA description and summary of your data. How was your data collected by its original collectors? What are the important variables of interest for your research question? Use functions like glimpse() and summary() to present your data.The data was collected by New York City and put on its Open Data source. The data covers NYC schools in the academic years 2014-2015 to 2020-2021. The important variables of interest included in the data are:- Academic year- Number and percentage of Asisan, Black, Hispanic, and White students- Number and percentage of students in poverty- Economic need index, which is the average of students' "Economic Need Values" - The Economic Need Index (ENI) estimates the percentage of students facing economic hardshipThe other variables included are: DBN (district, borough, school number), school name, total enrollment, enrollment numbers for K-12, number and percentage of female and male students, number and percentage of students with disabilities, and number and percentage of English-Language Learner (ELL) students.```{r}glimpse(school_data)``````{r}summary(school_data)# Note: the summary data for the enrollment numbers split by grade is somewhat off (especially minimums) because there is no variable listed for type of school (i.e., middle versus high school). So, for example, an elementary school would have an enrollment total of 0 for grade 12, which would show up as the minimum.```As we can see from this summary, the median percent of poverty in NYC schools (81.4%) is higher than the mean percent (75.89%), indicating that there may be low outliers with very low percentages of poverty. The same holds true for the Economic Need Index, with the mean (0.691) lower than the median (0.743). It is troubling, however, that both the mean and median percentages of poverty in NYC schools overall is more than three-fourths of the population.## ReferencesNew York State Child Poverty Facts. Schuyler Center for Analysis and Advocacy. (2021, February 18). Retrieved from https://scaany.org/wp-content/uploads/2021/02/NYS-Child-Poverty-Facts_Feb2021.pdfPoverty in New York City. Columbia University Center on Poverty and Social Policy. (n.d.). Retrieved from https://www.povertycenter.columbia.edu/poverty-in-new-york-city#:\~:text=Children%20and%20Families%20in%20New%20York%20City&text=Through%20surveys%2C%20we%20find%20that,is%20at%20least%2020%20percent.