NEISD Enrollment Projections:Methodology & Accuracy

Prepared by Anthony A. Athens IIIAugust 11, 2008

Agenda

• Random Variations

• Short Range Projections

• Long-Range Projections

• Accuracy

• Triangulation

Annual Closings, Enrollment Growth, & Enrollment Growth Per

New Unit

500

2500

2000

1500

1000

2001 2002 200520042003 2006 *2008

2007

3000

0.79

0.750.61

0.38

0.63

0.50

0.38 0.52

Enro

llment

Gro

wth

* Projected

Clo

sings

My Summer Reading:Fooled By Randomness by Nassim

Taleb• Author is a former Wall Street trader

• The accuracy of predictions depends on:• Skills – Good & Poor• Luck – Good & Bad

• Acknowledging the role of luck (random unpredictable factors) helps avoid a false sense of confidence

Short-Range Projections• Cohort Model

• For next school year

• Projects enrollment for every grade at every campus

• Census Tract birth data from Metropolitan Health Department

• Historical survival rates calculated for every grade at every campus• Survival rates weighted to best capture recent trends

and discount anomalous data

Short-Range Projection Accuracy

0

10000

20000

30000

40000

50000

60000

70000

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 200793%

94%

95%

96%

97%

98%

99%

100%

Projected Actual Accuracy Average Accuracy

99.4%

Long-Range Projections• 180+ Neighborhood Projection Models

• Aggregated to Campus Level

• Cohort Model• Census Tract Birth Data from Metro. Health Dept.• Weighted Average Historical Survival Rates

• Housing Model• Enrollment Grows with Projected Housing• SA Research• Metrostudy• Other

• Constant Model

Long-Range Projection Accuracy: 1988 Bond

0

10000

20000

30000

40000

50000

60000

70000

80000

1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996

6.4%

Projected

Actual

Long-Range Projection Accuracy: 1995 Bond

0

10000

20000

30000

40000

50000

60000

70000

80000

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

10.4%

Projected

Actual

Long-Range Projection Accuracy: 1998 Bond

0

10000

20000

30000

40000

50000

60000

70000

80000

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

3.9%

Projected

Actual

Long-Range Projection Accuracy: 2003 Bond

0

10000

20000

30000

40000

50000

60000

70000

80000

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

0.4%Projected

Actual

Long-Range Projection Accuracy: 2007 Bond

0

10000

20000

30000

40000

50000

60000

70000

80000

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

2.2%Projected

Actual

Long-Range Projections

0

10000

20000

30000

40000

50000

60000

70000

80000

Bond07Bond03Bond 98Bond95Bond88Actual

Triangulation

• Enrollment projections are periodically recalculated to better capture the latest enrollment and housing trends

• In addition to district-produced projections, outside contractors are hired to produce a second set of projection

Long-Range Projections: NEISD vs. Deskmap

0

10000

20000

30000

40000

50000

60000

70000

80000

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Deskmap

ActualNEISD

Questions