The shape of educational inequality

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Science Advances  15 Jul 2020:
Vol. 6, no. 29, eaaz5954
DOI: 10.1126/sciadv.aaz5954
  • Fig. 1 Potential models of student capital distributions.

    (A) Probability distribution function for each model. (B) Hazard rate of dropping out specified by each model. Specifically, the vertical axis gives the probability that a student who has k units of student capital will stop their education before earning k + 1 units. In both cases, the trends suggested are qualitative, designed to show the shape of the distribution rather than any specific numbers.

  • Fig. 2 Distribution of credits earned.

    Each graph corresponds to the distribution of students in one college in the dataset within 5 years of enrolling. White bars represent students who dropped out.

  • Fig. 3 QQ plots for the three parametric models.

    Each plot compares a real dataset to a simulated population generated using a fitted model. The columns correspond to discrete normal, geometric, and zeta distributions, respectively. The top three rows each correspond to a single college-year cohort. The bottom row infers the distributions for the complete set of 156,712 students from all 28 colleges. Points close to the red line indicate that the quantiles of the simulated data are very close to the quantiles of the actual data, signifying that the model fits the data better.

  • Fig. 4 Further analysis of the finite resource model.

    (A) Histogram of average student capital. Each data value is the average student capital of a single college-year cohort. (B) Comparison of actual dropout rates and the dropout rates estimated by the finite resource model (n = 140). Each point corresponds to one college-year cohort. The red line corresponds to both values being equal. The blue line is the line of best fit.

Supplementary Materials

  • Supplementary Materials

    The shape of educational inequality

    Christopher L. Quarles, Ceren Budak, Paul Resnick

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