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Tag Archives: Education

What is the relationship between rates of suspension by race and free and reduced lunch?

Propublica’s article, Miseducation – Is There Racial Inequality at Your School? by  Lena V. Groeger, Annie Waldman and David Eads, (10/16/18), provides data by state on the percent of nonwhite students, the percent of students who get free/reduced-price lunch, high school graduation rate, the number of times White students are likely to be in an AP class as compared to Black students, and the number of times Black students are likely to be suspended as compared to White students. The comparison is also available for Hispanic students.

The graph here was created with their data and compares the percent of students on free and reduced lunch with the number of times Black students are likely to be suspended  compared to White students (state data isn’t available for HI, ID, MT, NH, NM, OR, UT, or WY).  The red lines uses all the data where as the blue line removes the outliers of DC and ND. The blue regression line has a p-value of 0.012 and R-squared of 0.15.  This suggests that wealthier states, as measured by free and reduced lunch programs, have a greater disparity is suspensions between black and white students. The impact of outliers is instructive here and there are other scatter plots worth graphing from the article. There are also statistics projects waiting to be created with this data.

The article also has an interactive map or racial disparities by districts, but the map can be misleading based on missing data from districts. Can you see how?  This makes the map itself useful for QL courses.  R Script that created this graph. Companion csv file.

Who misses school the most?

The EPI article,  Student absenteeism – Who misses school and how missing school matters for performance by Emma García and Elaine Weiss (9/25/18) provides a detailed account of absenteeism based on race and gender.  For example, their chart here is the percent of students that missed three or more days in the month prior to the 2015 NAEP mathematics assessment. There are noticeable differences. For instance, the percentage of Black, White, and Asian (non ELL) that missed three or more days in the month is 23%, 18.3%, and 8.8% respectively.

Why does this matter?

In general, the more frequently children missed school, the worse their performance. Relative to students who didn’t miss any school, those who missed some school (1–2 school days) accrued, on average, an educationally small, though statistically significant, disadvantage of about 0.10 standard deviations (SD) in math scores (Figure D and Appendix Table 1, first row). Students who missed more school experienced much larger declines in performance. Those who missed 3–4 days or 5–10 days scored, respectively, 0.29 and 0.39 standard deviations below students who missed no school. As expected, the harm to performance was much greater for students who were absent half or more of the month. Students who missed more than 10 days of school scored nearly two-thirds (0.64) of a standard deviation below students who did not miss any school. All of the gaps are statistically significant, and together they identify a structural source of academic disadvantage.

These results “… identify the distinct association between absenteeism and performance, net of other factors that are known to influence performance?”  The article has 12 graphs or charts, with data available for each, including one that reports p-values.

How much do countries spend on education?

The answer to the question depends on how it is measured.  The post  in statista, The Countries Spending the Most on Education by Martin Armstrong (9/12/2018) reports spending as a share of gross domestic product for primary, second and post-secondary non-tertiary education as well as tertiary education.  By this measure Norway spends the most. But, if the measure used is expenditure per student as a share of GDP per capita, the high spender is (south) Korea (Norway is fifth). Our graph here is a scatter plot of the two measures by country.

The data is from OECD.Stat. Go to Education and Training, Education at a Glance, Financial resources invested in education, Education finance indicators, and finally Expenditure per student as share of GDP per capita.  Under indicator at the top of the spreadsheet the measure can be changed.  Definitions of measures can be found in the OECD Handbook for Internationally Comparative Education Statistics (page 99).

Download the csv file and R-script used here.