Research Question #5: How do education outcomes like dropouts and student achievement from COVID-19 school closures impact the greater society?
Method: Connect the education data to society factors such as decreased earnings potential, increased rates of poverty, crime, depression, health disorders (or lower life spans), and/or drug use. Focus on Texas results and Texas or national potential impact to find drop out rates after.
Texas average yearly wages: These are broken down by county. The Texas school campus reference has the county of each school. There by we can assess the average salary for graduates of each campus and calculate the wage losses from the study delineated in the OECD Study Each person is estimated to work for 45 years with a 3% discount for unemployed.We will review at-risk population in Texas schools to identify the scope of student population vulnerable to societal impact.
knitr::include_graphics('https://www.dropbox.com/s/lwvgvghssh0nzif/TX%20High%20School%20Dropout%20Lifetime%20Lost%20Wages%20.png?dl=1')The following map displays the locations and magnitude of the potential lost Texas wages due top COVID-19 classroom closures and online learning. This map is based on Texas Assn of Counties Average Annual Pay per County.
knitr::include_graphics('https://www.dropbox.com/s/3lb4juzcjqupv6p/TX%20High%20School%20Dropout%20Lifetime%20Lost%20Wages%20Map.png?dl=1')We will be pulling detail for each campus by regions (composed of groups of TX counties) to see the variation how the model reacts to more disadvantaged Texas communities. Below we can see high significance and significant adjusted R squared for the logistic regression for drop out rate, Region(by County),and the economic disadvantage rate.
This indicates a relationship by Attendance_Econ_Disadv_Rate to potential salary losses. Efforts to mitigate salary losses could be directed to these areas.
##
## Call:
## lm(formula = Campus_2020_Annual_Dropout_for_Grades_0912_All_Students_Rate ~
## Average_Annual_Pay_per_Region + Campus_2020_Attendance_Econ_Disadv_Rate,
## data = Data7)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.700 -0.427 -0.253 -0.152 43.548
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.186392 0.148639 7.982 1.66e-15
## Average_Annual_Pay_per_Region$41,225.60 -0.054290 0.161672 -0.336 0.73703
## Average_Annual_Pay_per_Region$42,670.67 0.351513 0.169784 2.070 0.03845
## Average_Annual_Pay_per_Region$43,351.60 0.503311 0.154715 3.253 0.00115
## Average_Annual_Pay_per_Region$44,415.64 0.021498 0.125079 0.172 0.86354
## Average_Annual_Pay_per_Region$45,485.20 -0.018412 0.150049 -0.123 0.90234
## Average_Annual_Pay_per_Region$45,652.33 0.269861 0.169966 1.588 0.11239
## Average_Annual_Pay_per_Region$47,519.16 0.096898 0.128567 0.754 0.45106
## Average_Annual_Pay_per_Region$48,257.40 0.355349 0.136479 2.604 0.00924
## Average_Annual_Pay_per_Region$49,603.53 0.268373 0.113077 2.373 0.01765
## Average_Annual_Pay_per_Region$53,115.54 0.029411 0.131645 0.223 0.82322
## Average_Annual_Pay_per_Region$54,471.77 -0.027675 0.174494 -0.159 0.87399
## Campus_2020_Attendance_Econ_Disadv_Rate -0.010474 0.001133 -9.242 < 2e-16
##
## (Intercept) ***
## Average_Annual_Pay_per_Region$41,225.60
## Average_Annual_Pay_per_Region$42,670.67 *
## Average_Annual_Pay_per_Region$43,351.60 **
## Average_Annual_Pay_per_Region$44,415.64
## Average_Annual_Pay_per_Region$45,485.20
## Average_Annual_Pay_per_Region$45,652.33
## Average_Annual_Pay_per_Region$47,519.16
## Average_Annual_Pay_per_Region$48,257.40 **
## Average_Annual_Pay_per_Region$49,603.53 *
## Average_Annual_Pay_per_Region$53,115.54
## Average_Annual_Pay_per_Region$54,471.77
## Campus_2020_Attendance_Econ_Disadv_Rate ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.192 on 7600 degrees of freedom
## (1274 observations deleted due to missingness)
## Multiple R-squared: 0.01601, Adjusted R-squared: 0.01446
## F-statistic: 10.31 on 12 and 7600 DF, p-value: < 2.2e-16