4. 160-120 Days of poor AQ – 1558 Schools 91-105 Days of poor AQ – 343 Schools 76-90 Days of poor AQ – 3335 Schools 61-75 Days of poor AQ – 1888 Schools **Schools not heavily impacted: 5523

5. Total Number of Asthma Hospitalizations

7. -According to the Rand Corporation, in 2009, there were 343 public schools that had a daily attendance under 90%.

8. Sources: Environmental Protection Agency. “Air Compare- County Comparisons.” http://www.epa.gov/aircompare/compare.htm http://www.epa.gov/aircompare/compare.htm California Breathing. “Asthma Profiles: County Comparison Charts.” http://www.californiabreathing.org/asthma-data/county-comparisons Rand Corporation. “Enrollment Statistics.” http://ca.rand.org/stats/education/enroll.html Rand Corporation. “Average Daily Attendance.” http://ca.rand.org/stats/education/attendance.html Rand Corporation. “Annual Per Pupil Spending by District.” http://ca.rand.org/stats/education/perpupil.html California Department of Education. “Public School Database.” http://www.cde.ca.gov/ds/si/ds/pubschls.asp http://www.cde.ca.gov/ds/si/ds/pubschls.asp

9. Skills Used: -Slide 3: inset map -Slide 7: aggregating attribute fields - “Perc_ada < 90” - Percent average daily attendance < 90% -Slide 6: creating indices - “ Co_perc_ad * co_enrollment = avg_ada” - (average % daily attendance) * (county enrollment) = (average number of kids per day in attendance) - co_enrollment – avg_ada = avg_absences - (county enrollment) – (avg. number of kids per day in attendance) = (avg. number of daily absences) -Slide 7: point graduated symbol -Slide 7: geocoding -Slide 4: geocoding and graph