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{\plain \f1\fs32 }{\plain \b\f1\fs32 BLACK STUDENT IMPROVEMENTS ON THE TAAS EXAM 
1995-98\par
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{\plain \f1 A REPORT OF THE\par
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{\plain \f1 TEXAS EDUCATIONAL EXCELLENCE PROJECT\par
}\pard \sl0\tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\tx9360 
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{\plain \f1 Number 7 October 1999\par
}{\plain \f1 \par
}{\plain \f1 \par
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}{\plain \f1 \par
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{\plain \f1 Kenneth J. Meier\par
}{\plain \f1 Robert D. Wrinkle\par
}{\plain \f1 J.L. Polinard\par
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{\plain \f1 \par
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}{\plain \f1 \par
}{\plain \f1 For further information contact: 
http://people.tamu.edu/~kmeier/teep/\par
}{\plain \f1 \par
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{\plain \f1 Kenneth J. Meier, Department of Political Science, Texas 
A&M University, 409-845-4232 kmeier@polisci.tamu.edu\par
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{\plain \f1 Robert D. Wrinkle, Department of Political Science, 
University of Texas-Pan American, 956-381-3341 
rdwe116@panam1.panam.edu\par
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{\plain \f1 }{\plain \b\f1 Black Student Improvements on the TAAS Exam}{\plain \f1  }{\plain \b\f1 1995-98}{\plain \f1 \par
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{\plain \f1 \tab Between 1995 and 1998 the pass rate for black students on 
the TAAS exam increased by almost 25 percentage points.  
Despite these gains, the pass rate for black students in 1998 
remains behind that of white students--only 62.6 percent vs. 
87.9 percent--by a substantial margin.  While the 1998 scores 
represent a narrowing of the black-white gap from 36.5 
percentage points, to one of just over 25 percentage points, a 
considerable gap remains.  The first step in improving black 
tests scores is to identify school districts that do a better 
job of educating black students.\par
}{\plain \f1 \par
}{\plain \f1 \tab The Texas Educational Excellence Project uses a technique 
of analysis known as multiple regression to identify school 
districts that do a better job of educating black students. 
This analytical tool makes it possible to develop 
generalizations about the overall performance of Texas school 
districts in how well they educate black students, while also 
providing information that can be used to make comparisons 
across individual school districts.  Our model is based on 
what is generally know as an education \'93production function\'94 
where student performance (defined as black pass rates on the 
TAAS) is a function of inputs into the educational process, 
such as operating expenditures, student-teacher ratios, and 
various educational policies. Estimation of this production 
function results in predictions about how well districts are 
expected to do, given the level of inputs available to them. 
Based on the results of the production function model, we 
compare how well districts}{\plain \i\f1  actually}{\plain \f1  perform to how well the 
statistical model }{\plain \i\f1 predicts}{\plain \f1  they should perform based on their 
inputs. The difference, if any, between the actual results and 
the predictions indicates how well districts are doing in 
educating black students.\par
}{\plain \f1 \par
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{\plain \b\f1 An Education Production Function \par
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{\plain \f1 \tab School districts are organizations; they receive inputs 
(resources and students) from their environment and produce 
outputs (educated students among others).  A vast literature 
has designated a variety of education production functions 
whereby the outputs of school systems can be evaluated 
relative to their inputs (Burtless 1996; Smith 1995; Hanushek 
}{\plain \f1 1986; 1989; 1996).  \par
}{\plain \f1 \par
}{\plain \f1 \tab Our dependent variable is the school districts pass rate 
for black students on the TAAS exam.  Texas requires all 
school districts to administer exams to students in several 
grades on an annual basis. We make no claim that results on 
TAAS exams account for all of the overall learning experience 
of black students. Student performance is a multi-dimensional 
concept that can be measured in variety of different ways. 
However, pass rates on TAAS exams }{\plain \b\f1 do}{\plain \f1  measure whether students 
are picking up basic academic skills from grade to grade. Our 
dependent variable, therefore, focuses primarily on how well 
districts perform in teaching black students basic skills, and 
should not be construed \par
}{\plain \f1 as an overall measure of black student learning.               \par
}{\plain \f1 \par
}{\plain \f1 \tab The independent variables fall into four general types--environmental constraints, financial resources, teacher 
qualifications, and district policies.  Environmental 
constraints are factors that restrict agency performance; in 
the case of education the key constraint is how difficult/easy 
it is to educate students. In the context of educational 
policy, poverty is a serious constraint on student 
performance.  The measures of constraint are the percent of 
poor students (defined as those eligible for free school 
lunches) and the percentage of black families that live in 
poverty.  We also measure the educational level of blacks in 
the school district using the percentage of blacks in the 
school district over age 25 with a least a high school 
diploma. The education variable should be positively related 
to student performance and the other two measures should be 
negatively related to black pass rates.\par
}{\plain \f1 \par
}{\plain \f1 \tab Financial resources are the basic raw materials of any 
organization's attempt to meet its goals.  Three measures of 
financial resources are included--per student instructional 
funds, average teacher's salary, and percent of funds received 
via state aid.  These represent total resources devoted to 
education, the attractiveness of teaching positions in a 
competitive market place, and state efforts to overcome the 
unequal distribution of local financial resources. The 
relationship between expenditures and educational outcomes is 
one of the most contested questions in all of educational 
policy. Hanushek (1986; 1989; 1996) contends that there is no 
consistent relationship between money and student outcomes.  
Although this finding has been challenged by others (Hedges 
and Greenwald 1996), it remains the conventional wisdom.  In 
recent longitudinal studies, however, Murray (1995), Evans, 
Murray and Schwab (1997), and Murray, Evans and Schwab (1995) 
found that districts that increased expenditures had improved 
performance afterward. Bohte (1999) found that expenditures 
were correlated with higher test scores even when controlling 
for the previous year's test scores. We consider expenditures 
a critical variable for inclusion in the model. All 
relationships should be positive.\par
}{\plain \f1 \par
}{\plain \f1 \tab The two teacher qualification measures (or lack thereof) 
are the percent of teachers who hold a temporary certification 
in a subject specialty (as opposed to a permanent 
certification) and the average number of years of teacher 
experience.  The relationship for noncertification should be 
negative, while the expectation is that more experienced 
teachers will lead to higher student outcomes.\par
}{\plain \f1 \par
}{\plain \f1 \tab Finally, the education production function contains three 
policy measures--the percentage of students taking gifted 
classes, class size, and student attendance (percent attending 
on an average day).  Performance should be positively related 
to gifted classes and attendance and negatively related to 
class size.\par
}{\plain \f1 \par
}{\plain \f1 \tab Texas has a large number of school districts; many are 
very small or deal with a homogeneous student body.  In an 
effort to use a set of organizations relatively similar in the 
task that they perform, we have restricted our analysis to 
school districts with a least 1000 students and at least 10 
percent black students.  These restrictions resulted in a 
total of 170 districts in the study.\par
}{\plain \f1 \par
}{\plain \f1 \tab The data analysis is a pooled time series with data from 
the years 1995 through 1998.  In any pooled time series one 
needs to control for serial correlation resulting from any 
trend in the variables over time.  A series of dummy variables 
are introduced to achieve this.\par
}{\plain \f1 \par
}{\plain \f1 \tab The basic production function is shown in table 1.  
Several variables are powerful predictors of black student 
pass rate.  These include expenditure, background, and policy 
variables.  Teacher salaries are strongly and positively 
related to the black student pass rate, as is the percentage 
of black adults age 25 and older with at least a high school 
education.  Attendance also is strongly and positively related 
to the black student pass rate.  The greater the percentage of 
low income students in the district, the lower the black 
student pass rate.  No other variable achieved statistical 
significance.\par
}{\plain \f1 \par
}{\plain \f1 \tab The results of this model allow us to compare school 
districts as to how well they do above (or below) 
expectations.  As an illustration, the model predicted that 
the Houston Independent school district would have an average 
black pass rate of 47.78% from 1995-98.  Houston\'92s actual pass 
rate of 54.83 represents a 7.05 percentage point improvement 
over this standard.  Based on this method, the top ranked 
school district for black students in Texas was Ferris with a 
rating of +21.6% followed closely by Pittsburg with a +21.14 
score and Hooks with a +17.76 score.\par
}{\plain \f1 \par
}{\plain \f1 \tab The top 25 districts are shown in table 2.  The first 
column is the numerical score on which the districts are 
ranked.  The second column is the 1998 score and the third 
column is the average pass rate for black students from 1995 
to 1998 in this district. These twenty-five districts 
represent a variety of different types of school districts 
located throughout the state. As mentioned above, Ferris again 
is the top ranked school district for black students.  Again, 
it is notable that Houston, a large, metropolitan school 
district makes the list of the top twenty-five, as it did last 
year.\par
}{\plain \f1 \par
}{\plain \f1 \tab Table 3 reports the 25 best districts for black students 
in 1998 along with the 1995-1998 average scores.  A comparison 
of this table with Table 2 gives some indication of relative 
movement among the rankings of school districts.  Pittsburg 
with a 1998 score of 25.74 ranks first in 1998, with Linden-Kildare (23.95) second, Hooks (22.73) and Ferris (20.11) 
fourth.  Recent gains are likely the result of the benefits of 
policies adopted earlier so these are the districts that are 
likely to continue to be rated highly in future studies.\par
}{\plain \f1 \par
}{\plain \f1 \tab The table in the Appendix gives an alphabetical listing 
of all of the school districts examined in this study, along 
with their scores.  Any person interested in a specific school 
district can examine the Appendix to locate that district and 
identify the score and rank.\par
}{\plain \f1 \par
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{\plain \f1 }{\plain \b\f1 Conclusion}{\plain \f1 \par
}\pard \tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\tx9360
{\plain \f1 \par
}{\plain \f1 \tab This study has identified those school district in Texas 
that performed better than expected on the pass rate for black 
students.  These districts should serve as role models for 
other districts in Texas.  The districts have a wide variety 
of programs for early diagnosis, coordination of curriculum, 
and parental involvement.  If specific programs and 
performances are identified, then they can be transferred to 
other districts with an overall benefit to black students.\par
}{\plain \f1 \par
}{\plain \f1 \tab Although this study examined exemplary districts, that 
should not detract from the relatively low pass rate for black 
students in Texas.  A great deal of additional improvement is 
needed in these districts as well as other districts to close 
the test gap between black and Anglo students.  Substantial 
progress has been made in the last few years; a great distance 
remains to be done.  Improving educational opportunities for 
all Texas Children requires a long term commitment to 
education.  Problems developed over a period of decades; 
solutions require both time and hard work.\par
}\pard \tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\tx9360
{\plain \*\cs25\f3 \par
}{\plain \*\cs25\f3 \par
}{\plain \f1 \tab The Texas Educational Excellence Project (TEEP) is a 
joint program of Texas A&M University and the University of 
Texas-Pan American.  TEEP seeks to apply scholarly research to 
educational policy issues in order to make recommendations for 
greater quality and equity in Texas school systems.\par
}\pard\page 
\pard \sl480\tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\tx9360 
{\plain \f4 \par
}\pard \tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\tx9360
{\plain \b\f4 \tab Table 1. The Education Production Function\par
}{\plain \*\cs25\f4 \par
}\pard \qc\tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\tx9360 
{\plain \*\cs25\f4 Dependent Variable = % of black students passing the TAAS 1995-98\par
}\pard \tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\tx9360
{\plain \*\cs25\f4 \par
}{\plain \*\cs25\f4 }{\plain \*\cs25\ul\f4 Independent Variable              Coefficient      Standard Error\par
}{\plain \*\cs25\f4 \par
}{\plain \*\cs25\f4 Low Income Students                -.0580             .0339\par
}{\plain \*\cs25\f4 \par
}{\plain \*\cs25\f4 Gifted Classes                      .1527             .1059\par
}{\plain \*\cs25\f4 \par
}{\plain \*\cs25\f4 Attendance                         3.0641             .4924 \par
}{\plain \*\cs25\f4 \par
}{\plain \*\cs25\f4 Teacher Salaries (000)             1.0310             .3131\par
}{\plain \*\cs25\f4 \par
}{\plain \*\cs25\f4 Class Size                         -.2893             .3998\par
}{\plain \*\cs25\f4 \par
}{\plain \*\cs25\f4 NonCertified Teachers              -.0485             .1284\par
}{\plain \*\cs25\f4 \par
}{\plain \*\cs25\f4 Teacher Experience                 -.1483             .3000\par
}{\plain \*\cs25\f4 \par
}{\plain \*\cs25\f4 State Funding Percent               .0294             .0268\par
}{\plain \*\cs25\f4 \par
}{\plain \*\cs25\f4 Instructional Funding Per Student   .0009             .0018\par
}{\plain \*\cs25\f4 \par
}{\plain \*\cs25\f4 Black Education (25+)               .2418             .0653\par
}{\plain \*\cs25\f4 \par
}{\plain \*\cs25\f4 Black Poverty                      -.0409             .0424\par
}{\plain \*\cs25\f4 \par
}{\plain \*\cs25\f4 \par
}{\plain \*\cs25\f4 R-Square           .63\par
}{\plain \*\cs25\f4 \par
}{\plain \*\cs25\f4 Omitted are coefficients for individual year dummy variables.        \par
}{\plain \*\cs25\f1 \par
}\pard\page 
\pard \qc\tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\tx9360 
{\plain \f4 }{\plain \b\f4 Table 2\par
}\pard \qc\tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\tx9360 
{\plain \b\f4 Top 25 Districts for Black Students 1995-98}{\plain \f4 \par
}\pard \tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\tx9360
{\plain \f4 \par
}{\plain \ul\f4 Rank  Name               Score   98 Score  Average}{\plain \f4 \par
}{\plain \f4   1 Ferris               21.60     20.11     68.93\par
}{\plain \f4   2 Pittsburg            21.14     25.74     67.93\par
}{\plain \f4   3 Hooks                17.76     22.73     66.10\par
}{\plain \f4   4 Linden\_Kildare       15.11     23.95     66.75\par
}{\plain \f4   5 Sweeny               14.32     11.47     66.45\par
}{\plain \f4 \par
}{\plain \f4   6 Del Valle            13.64     15.73     57.63\par
}{\plain \f4   7 Connally             13.13     10.01     67.23\par
}{\plain \f4   8 McGregor             12.58     20.08     66.78\par
}{\plain \f4   9 Texas City           11.93     10.27     59.38\par
}{\plain \f4  10 Tatum                11.65     13.96     61.17\par
}{\plain \f4 \par
}{\plain \f4  11 Stafford MSD         11.38      7.19     69.18\par
}{\plain \f4  12 Sulpher Springs      10.87      9.39     62.75\par
}{\plain \f4  13 Atlanta              10.72     18.08     62.22\par
}{\plain \f4  14 Wilmer\_Hutchins      10.28     11.24     54.70\par
}{\plain \f4  15 Kountze              10.07     16.06     55.17\par
}{\plain \f4 \par
}{\plain \f4  16 Liberty\_Eylau         9.63     10.22     59.47\par
}{\plain \f4  17 Daingerfield\_Lo       8.75     10.26     59.50\par
}{\plain \f4  18 Aldine                8.69     11.72     59.78\par
}{\plain \f4  19 North Forest          8.36      3.97     56.85\par
}{\plain \f4  20 New Boston            8.34      9.15     61.83\par
}{\plain \f4 \par
}{\plain \f4  21 Garland               8.02      4.42     62.22\par
}{\plain \f4  22 Goose Creek           7.95      7.26     55.20\par
}{\plain \f4  23 Grand Prairie         7.76      5.72     62.13\par
}{\plain \f4  24 Wichita Falls         7.17      5.34     57.72\par
}{\plain \f4  25 Houston               7.05      7.36     54.83\par
}{\plain \f4 \par
}{\plain \f4 }\pard\page 
\pard \qc\tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\tx9360 
{\plain \f4 }{\plain \b\f4 Table 3\par
}\pard \qc\tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\tx9360 
{\plain \b\f4 Best Districts for Black Students 1998}{\plain \f4 \par
}\pard \tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\tx9360
{\plain \f4 \par
}{\plain \ul\f4 Rank Name              98 Score   Average}{\plain \f4 \par
}{\plain \f4   1 Pittsburg            25.74     67.93\par
}{\plain \f4   2 Linden\_Kildare       23.95     66.75\par
}{\plain \f4   3 Hooks                22.73     66.10\par
}{\plain \f4   4 Ferris               20.11     68.93\par
}{\plain \f4   5 McGregor             20.08     66.78\par
}{\plain \f4 \par
}{\plain \f4   6 Atlanta              18.08     62.22\par
}{\plain \f4   7 Kountze              16.06     55.17\par
}{\plain \f4   8 Del Valle            15.73     57.63\par
}{\plain \f4   9 Rockdale             14.67     52.15\par
}{\plain \f4  10 Bay City             14.57     51.88\par
}{\plain \f4 \par
}{\plain \f4  11 Newton               14.25     48.92\par
}{\plain \f4  12 La Grange            14.11     56.22\par
}{\plain \f4  13 Tatum                13.96     61.17\par
}{\plain \f4  14 Angleton             13.02     60.58\par
}{\plain \f4  15 Malakoff             12.78     46.97\par
}{\plain \f4 \par
}{\plain \f4  16 Aldine               11.72     59.78\par
}{\plain \f4  17 Sweeny               11.47     66.45\par
}{\plain \f4  18 Sabine               11.37     56.92\par
}{\plain \f4  19 Wilmer\_Hutchins      11.24     54.70\par
}{\plain \f4  20 Wharton              10.29     51.33\par
}{\plain \f4 \par
}{\plain \f4  21 Texas City           10.27     59.38\par
}{\plain \f4  22 Daingerfield\_Lo      10.26     59.50\par
}{\plain \f4  23 Liberty\_Eylau        10.22     59.47\par
}{\plain \f4  24 Queen City           10.01     51.03\par
}{\plain \f4  25 Connally             10.01     67.23\par
}{\plain \f4 \par
}{\plain \f4 \pard\page \par
}{\plain \b\f4 References}{\plain \f4 \par
}{\plain \f4 \par
}\pard \fi-720\li720\tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\tx9360 
{\plain \f4 Bothe, John, 1999.  "Class Size, Teacher Salaries and Student 
Performance." College \tab Station, TX: Texas Educational 
Excellence Project.\par
}\pard \tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\tx9360
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{\plain \f4 Burtless, Gary. 1996. }{\plain \i\f4 Does Money Matter? The Effect of School 
Resources on Student Achievement and Adult Success}{\plain \f4 . Washington, 
D.C.: Brookings Institution.\par
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}\sect \sectd \sbknone\marglsxn2160\endnhere 
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\pard \fi-720\tx-720\tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640 
{\plain \*\cs25\f4 Hanushek, Eric A. 1986. "The Economics of Schooling: Production and 
Efficiency in Public Schools." }{\plain \*\cs25\f4 }{\plain \*\cs25\i\f4 Journal of Economic Literature}{\plain \*\cs25\f4  
24:1141-77.\par
}\sect \sectd \sbknone\endnhere 
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{\plain \*\cs25\f4 Hanushek, Eric A. 1989. "The Impact of Differential Expenditures on 
School Performance." }{\plain \*\cs25\f4 }{\plain \*\cs25\i\f4 Educational Researcher}{\plain \*\cs25\f4  23 (4): 45-65.\par
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{\plain \*\cs25\f4 Hanushek, Eric A.  1996. "School Resources and Student Performance." 
In }{\plain \*\cs25\f4 }{\plain \*\cs25\i\f4 Does Money Matter? The Effect of School Resources on Student 
Achievement and Adult Success}{\plain \*\cs25\f4 , Gary Burtless, ed. Washington, 
D.C.: Brookings Institution.\par
}\sect \sectd \sbknone\endnhere 
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{\plain \f4 \tab Hedges, Larry V. and Rob Greenwald.  1996.  "Have Times Changed?  The 
Relation between School Resources and Student Performance." In 
}{\plain \i\f4 Does Money Matter? The Effect of School \tab Resources on Student 
Achievement and Adult Success,}{\plain \f4  ed. Gary Burtless. Washington: 
Brookings.\par
}\pard \tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\tx9360
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{\plain \f4 Murray, Sheila E. 1995. "Two Essays on the Distribution of \tab Education Resources and Outcomes." PhD. diss. Department of 
Economics, University of Maryland.\par
}\pard \tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\tx9360
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{\plain \b\f4 }{\plain \f4 \tab Murray, Sheila E., William N. Evans and Robert M. Schwab. 1995. 
"Money Matters After All: Evidence From Panel Data on the 
Effects of School Resources." University of Kentucky and 
University of Maryland working paper: The Martin School.\par
}\pard \tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\tx9360
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{\plain \*\cs25\f4 Smith, Kevin B.  1995.  "Policy, Markets, and Bureaucracy: 
Reexamining School Choice."  }{\plain \*\cs25\f4 }{\plain \*\cs25\i\f4 Journal of Politics}{\plain \*\cs25\f4  56 (May), 475-491.\par
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}{\plain }\pard\page 
\pard \qc\tx-720\tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640 
{\plain Appendix Table 1\par
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\pard \qc\tx-720\tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640 
{\plain Scores for All Districts\par
}\pard \tx-720\tx0\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640
{\plain \ul Rank  Name                   Score      98 Score    Average}{\plain \par
}{\plain \par
}{\plain  68 Abilene                     1.55       1.75      56.63\par
}{\plain  18 Aldine                      8.69      11.72      59.78\par
}{\plain 122 Alief                      \_4.14      \_2.33      53.90\par
}{\plain  41 Anahuac                     4.45       6.56      51.28\par
}{\plain  26 Angleton                    6.51      13.02      60.58\par
}{\plain 151 Arlington                  \_7.89      \_9.63      49.67\par
}{\plain 165 Athens                    \_11.68     \_12.42      35.55\par
}{\plain  13 Atlanta                    10.72      18.08      62.22\par
}{\plain 145 Austin                     \_6.61      \_8.26      39.40\par
}{\plain  27 Bay City                    6.47      14.57      51.88\par
}{\plain  36 Beaumont                    5.13       6.21      50.92\par
}{\plain 163 Bellville                 \_11.52     \_12.26      36.53\par
}{\plain  92 Bonham                     \_1.06      \_0.78      32.00\par
}{\plain 155 Brenham                    \_9.08     \_14.50      38.55\par
}{\plain  79 Brownsboro                  0.26       0.41      53.88\par
}{\plain 143 Bryan                      \_6.22      \_1.97      41.67\par
}{\plain  34 Caldwell                    5.31       4.47      53.75\par
}{\plain 148 Cameron                    \_7.00      \_6.39      41.15\par
}{\plain 164 Carthage                  \_11.56     \_16.50      39.17\par
}{\plain 105 Cedar Hill                 \_2.47      \_8.60      54.88\par
}{\plain  52 Center                      3.29       4.75      47.47\par
}{\plain 166 Chapel Hill               \_13.18     \_13.57      33.92\par
}{\plain 120 Clarksville                \_3.98     \_11.03      45.63\par
}{\plain 153 Cleveland                  \_8.51     \_13.73      32.00\par
}{\plain 159 Cold Spring\_Oakhurst      \_10.15     \_10.06      30.17\par
}{\plain 149 College Station            \_7.19      \_8.63      48.00\par
}{\plain  30 Columbia\_Brazoria           5.88       2.55      55.15\par
}{\plain  91 Columbus                   \_0.75      \_2.97      50.28\par
}{\plain  84 Commerce                   \_0.49       3.33      48.42\par
}{\plain   7 Connally                   13.13      10.01      67.23\par
}{\plain  69 Copperas Cove               1.35       1.93      55.60\par
}{\plain  66 Corrigan\_Camden             1.74      \_7.38      46.92\par
}{\plain 131 Corsicana                  \_5.22      \_4.28      40.42\par
}{\plain 125 Crockett                   \_4.51      \_8.87      38.45\par
}{\plain  64 Crosby                      2.02      \_2.35      56.38\par
}{\plain  46 Crowley                     4.15       6.65      64.85\par
}{\plain  95 Cureo                      \_1.15      \_1.46      46.08\par
}{\plain  17 Daingerfield\_Lone St        8.75      10.26      59.50\par
}{\plain 108 Dallas                     \_2.65      \_5.06      45.55\par
}{\plain  83 Dayton                     \_0.45      \_0.98      45.78\par
}{\plain   6 Del Valle                  13.64      15.73      57.63\par
}{\plain  47 Denison                     4.11       0.55      54.47\par
}{\plain  74 Denton                      0.64       1.46      52.03\par
}{\plain 100 DeSoto                     \_1.61       0.61      57.97\par
}{\plain  67 Diboll                      1.56      \_0.96      46.58\par
}{\plain 139 Dickinson                  \_5.92      \_6.12      37.55\par
}{\plain 114 Duncanville                \_3.17      \_1.43      53.60\par
}{\plain 103 East Central               \_2.30       0.05      53.28\par
}{\plain  29 Edna                        5.90       4.66      54.08\par
}{\plain  53 El Campo                    3.21       9.29      51.35\par
}{\plain 129 Elgin                      \_4.93      \_6.16      41.42\par
}{\plain 118 Ennis                      \_3.49      \_4.14      45.83\par
}{\plain  89 Everman                    \_0.71      \_2.43      51.70\par
}{\plain 117 Fairfield                  \_3.33      \_9.86      48.30\par
}{\plain   1 Ferris                     21.60      20.11      68.93\par
}{\plain  81 Fort Bend                  \_0.15       2.26      56.47\par
}{\plain 127 Fort Worth                 \_4.70      \_6.20      41.47\par
}{\plain 144 Ft Sam Houston             \_6.58      \_5.96      61.50\par
}{\plain  72 Gainesville                 0.98       0.17      55.05\par
}{\plain  37 Galena Park                 5.03       5.87      57.53\par
}{\plain  73 Galveston                   0.75       3.47      42.45\par
}{\plain  21 Garland                     8.02       4.42      62.22\par
}{\plain  63 Giddings                    2.05     \_11.50      50.80\par
}{\plain 123 Gilmer                     \_4.33      \_4.47      45.42\par
}{\plain  62 Gladewater                  2.24      \_0.65      49.85\par
}{\plain 147 Gonzales                   \_6.98     \_10.10      38.80\par
}{\plain  22 Goose Creek                 7.95       7.26      55.20\par
}{\plain  23 Grand Prairie               7.76       5.72      62.13\par
}{\plain 156 Greenville                 \_9.44     \_14.64      35.65\par
}{\plain 134 Groesbeck                  \_5.42      \_6.78      43.33\par
}{\plain  43 Hallettsville               4.17       3.97      54.78\par
}{\plain  49 Hardin\_Jefferson            3.73      \_0.69      51.17\par
}{\plain  65 Hearne                      1.96      \_2.49      45.42\par
}{\plain 169 Hempstead                 \_16.05     \_18.63      32.90\par
}{\plain 136 Henderson                  \_5.64      \_5.35      42.58\par
}{\plain  77 Hillsboro                   0.34       1.27      44.70\par
}{\plain 167 Hitchcock                 \_14.56     \_18.33      34.97\par
}{\plain   3 Hooks                      17.76      22.73      66.10\par
}{\plain  25 Houston                     7.05       7.36      54.83\par
}{\plain 150 Huntsville                 \_7.81      \_7.44      41.63\par
}{\plain  58 Irving                      2.84      \_1.42      59.30\par
}{\plain 146 Jacksonville               \_6.78      \_2.79      37.20\par
}{\plain  42 Jasper                      4.33       0.13      51.40\par
}{\plain  38 Jefferson                   4.95       5.28      52.05\par
}{\plain  71 Judson                      1.27       2.32      60.08\par
}{\plain  80 Kaufman                    \_0.06      \_0.18      48.15\par
}{\plain  99 Kilgore                    \_1.50       2.31      46.03\par
}{\plain  93 Killeen                    \_1.07       1.84      55.35\par
}{\plain  31 Kirbyville                  5.72       4.11      51.67\par
}{\plain  70 Klein                       1.33      \_3.87      60.65\par
}{\plain  15 Kountze                    10.07      16.06      55.17\par
}{\plain  45 La Grange                   4.15      14.11      56.22\par
}{\plain  96 La Marque                  \_1.17       3.06      46.95\par
}{\plain 102 La Vega                    \_2.22       1.55      46.38\par
}{\plain  57 Lamar Consolidated          2.90       5.04      52.00\par
}{\plain 128 Lancaster                  \_4.73     \_12.51      48.95\par
}{\plain  16 Liberty\_Eylau               9.63      10.22      59.47\par
}{\plain 106 Liberty                    \_2.47       0.43      47.40\par
}{\plain   4 Linden\_Kildare             15.11      23.95      66.75\par
}{\plain  51 Littlefield                 3.35       0.13      53.80\par
}{\plain 126 Livingston                 \_4.66      \_6.90      41.25\par
}{\plain  32 Longview                    5.51       8.39      53.25\par
}{\plain 111 Lubbock                    \_2.94      \_3.53      46.60\par
}{\plain 113 Lufkin                     \_3.01      \_0.14      45.20\par
}{\plain  78 Luling                      0.26      \_0.20      50.00\par
}{\plain 142 Madisonville               \_6.16      \_7.18      38.13\par
}{\plain  48 Malakoff                    4.00      12.78      46.97\par
}{\plain  28 Manor                       6.16       0.81      52.40\par
}{\plain 130 Marlin                     \_5.00      \_8.68      39.67\par
}{\plain 112 Marshall                   \_2.98      \_4.49      43.97\par
}{\plain   8 McGregor                   12.58      20.08      66.78\par
}{\plain 115 McKinney                   \_3.26      \_1.61      32.75\par
}{\plain  87 Mesquite                   \_0.63      \_0.71      54.15\par
}{\plain  33 Mexia                       5.49       4.51      54.05\par
}{\plain  85 Midland                    \_0.54      \_0.63      43.00\par
}{\plain 170 Mineola                   \_16.49     \_31.55      36.63\par
}{\plain  76 Montgomery                  0.38       0.41      54.35\par
}{\plain  60 Mount Pleasant              2.51      \_3.50      51.20\par
}{\plain 132 Nacognoches                \_5.23      \_5.19      43.20\par
}{\plain 140 Navasota                   \_6.06      \_1.05      38.53\par
}{\plain  20 New Boston                  8.34       9.15      61.83\par
}{\plain  39 Newton                      4.69      14.25      48.92\par
}{\plain  19 North Forest                8.36       3.97      56.85\par
}{\plain 152 Palestine                  \_8.12      \_7.25      40.13\par
}{\plain  61 Paris                       2.35      \_2.65      51.78\par
}{\plain  56 Pflugerville                3.04      \_2.35      61.45\par
}{\plain   2 Pittsburg                  21.14      25.74      67.93\par
}{\plain  97 Port Arthur                \_1.41      \_1.48      41.00\par
}{\plain  54 Queen City                  3.13      10.01      51.03\par
}{\plain  94 Randolph Field             \_1.13      \_1.95      68.30\par
}{\plain  75 Rice Consolidated           0.57       0.11      44.30\par
}{\plain 137 Richardson                 \_5.73      \_9.24      53.20\par
}{\plain  59 Rockdale                    2.64      14.67      52.15\par
}{\plain 158 Royal                      \_9.61     \_10.10      32.08\par
}{\plain 135 Rusk                       \_5.44      \_0.47      41.28\par
}{\plain  50 Sabine                      3.49      11.37      56.92\par
}{\plain 162 San Augustine             \_10.93     \_13.73      38.80\par
}{\plain 161 San Antonio               \_10.50      \_1.36      36.08\par
}{\plain 154 Sealy                      \_9.06      \_8.37      43.92\par
}{\plain 119 Sheldon                    \_3.85      \_3.01      50.22\par
}{\plain 109 Shepherd                   \_2.69       1.17      43.58\par
}{\plain 116 Sherman                    \_3.27      \_2.03      48.08\par
}{\plain 124 Silsbee                    \_4.42      \_1.31      43.13\par
}{\plain  90 Slaton                     \_0.74      \_1.60      33.10\par
}{\plain 168 Smithville                \_15.65     \_18.24      35.10\par
}{\plain 141 Spring                     \_6.11      \_4.86      54.10\par
}{\plain  11 Stafford MSD               11.38       7.19      69.18\par
}{\plain  12 Sulpher Springs            10.87       9.39      62.75\par
}{\plain   5 Sweeny                     14.32      11.47      66.45\par
}{\plain  10 Tatum                      11.65      13.96      61.17\par
}{\plain  98 Taylor                     \_1.44      \_1.21      45.55\par
}{\plain 107 Teague                     \_2.60      \_5.05      50.60\par
}{\plain 157 Temple                     \_9.60      \_9.33      41.40\par
}{\plain  40 Terrell                     4.46       9.87      55.53\par
}{\plain 121 Texarkana                  \_4.07      \_8.21      41.78\par
}{\plain   9 Texas City                 11.93      10.27      59.38\par
}{\plain 133 Tyler                      \_5.35      \_5.56      45.90\par
}{\plain 104 Van Vleck                  \_2.31      \_3.80      49.20\par
}{\plain  44 Vernon                      4.17       7.13      52.60\par
}{\plain 101 Waco                       \_1.86       3.60      39.20\par
}{\plain 160 Waller                    \_10.47     \_12.66      41.55\par
}{\plain 138 Waxahachie                 \_5.73      \_6.62      44.88\par
}{\plain  88 West Orange\_Cove           \_0.69      \_0.31      46.63\par
}{\plain  55 West Oso                    3.11       6.97      46.78\par
}{\plain  82 Westwood                   \_0.30      \_4.14      51.20\par
}{\plain  35 Wharton                     5.20      10.29      51.33\par
}{\plain  24 Wichita Falls               7.17       5.34      57.72\par
}{\plain  86 Willis                     \_0.60      \_0.52      43.13\par
}{\plain  14 Wilmer\_Hutchins            10.28      11.24      54.70\par
}{\plain 110 Yoakum                     \_2.93      \_5.01      43.38\par
}}