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Geographic Distributions of the US Population and the Student Population During the Post 1983 Era

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American Education and the Demography of the US Student Population, 1880 – 2014

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Abstract

The American population was on the move, moving West and South, and continued to change the geographic distribution of the American population. The de-industrialization of the North caused many families and person to move in search of employment and affordable housing. Along with this change in the geographic distribution of the US population there was a change in the distribution of the US student population.

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Notes

  1. 1.

    The scattergram displays the association between NHB population change in the South and NHB student enrollment in the South.

    figure a

    Correlation between NHB population movement into the south and NHB student enrollment: 1980 and 2014

  2. 2.

    For example, drop out rates by race and Hispanic origin among 12–13 year olds for the years 1980 to 2014 are displayed below.

    School dropouts among 12–13 year olds by race and Hispanic origin: 1980–2014

    Year

    NHW

    NHB

    NHO

    HISP

    Total

    1980

    0.8

    2.0

    2.2

    1.8

    1.1

    1990

    3.3

    4.4

    3.5

    4.2

    3.6

    2000

    0.9

    1.2

    1.3

    1.7

    1.1

    2014

    1.6

    1.9

    1.3

    1.6

    1.6

    1. Source: Steven Ruggles, Katie Genadek, Ronald Goeken, Josiah Grover, and Mathew Sobek. Integrated Public Use Microdata Series: Version 6.0 [Machine-readable database]. Minneapolis: University of Minnesota, 2015
    2. While the rates are small, they nonetheless raise an important policy concern.
  3. 3.

    This is an estimate based on the following set of equations: 1 = (.725 + (z * x). Where z is the derivate or rate of change in the ORs from 1980 to 2014 and is equal to .003765. Thus, 1 = (.725 + (.003765*x). Solving for X we have

    X = (1 −.725)/.003765 = 73.0469. Hence, it would take over 73 years for the OR to equal 1.0 or parity.

  4. 4.

    Odds ratios are not significant if 1 is within a confidence interval—say, a 95 percent confidence interval. The formula for the upper and lower limits of a confidence interval based on a 2 x 2 table is

    • Upper limit CI = [Ln(OR) + 1.96 √(1/a + 1/b + 1/c + 1/d)]

    • Lower limit CI = [Ln(OR) − 1.96 √ (1/a + 1/b + 1/c + 1/d)]

    However, it is generally the case that the t-statistic will determine the significant of the Log odds and thus the ORs.

  5. 5.

    Probabilities are computed thusly. 1) P1 = c + x*B; 2) P2 = exp(P1); 3) P3 = P2 /(1 + P2).

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Verdugo, R.R. (2018). Geographic Distributions of the US Population and the Student Population During the Post 1983 Era. In: American Education and the Demography of the US Student Population, 1880 – 2014. Applied Demography Series, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-319-89423-2_8

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  • DOI: https://doi.org/10.1007/978-3-319-89423-2_8

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