TENAFLY HIGH SCHOOL ACADEMIC RESEARCH 1

2015­2016 New Jersey Public High Schools Academic Rankings

C. Bucca, M. Guo, M. Hill­Oliva, J. Laufer, D. Shin, Q. Wang, M. Weiss, J. Xing

Class of 2016, Tenafly High School ­ Tenafly, New Jersey

June 16, 2016

Abstract

The correlation between the AP indices and the average composite SAT scores—for the top 100

New Jersey public schools—was analyzed to determine how indicative the two factors are of

student performance. Since these two indices appeared to be highly correlated, according to the

calculated R squared value, they were the only factors considered in the novel ranking

methodology described in this paper. Using 2015­2016 school data, AP indices were averaged

with the SAT indices for the top 100 schools in order to generate a 2015­2016 ranking of those

schools. A chi­squared test proved that there was no statistically significant difference among the

top 25 schools’ data. These findings suggest that it would be more appropriate to devalue the

method of ranking these schools individually, and, instead, switch to a tier ranking system. This

paper also goes on to predict the 2015­2016 rankings for the top 30 New Jersey public

schools—based on average composite SAT scores—according to the New Jersey Monthly 2014

methodology. Lastly, the correlation between middle school PARCC and high school SAT

scores was analyzed. The results showed that they were weakly correlated, which implies that, in

general, academic performance of middle school students is loosely associated with that of high

school students.

TENAFLY HIGH SCHOOL ACADEMIC RESEARCH 2

I. High School Academic Ranking

Introduction and Methods

High school rankings can influence the popularity of school systems, the price of homes,

and even the college admissions process. Though high school rankings are so important, many of

the most popular rankings of New Jersey high schools used a variety of factors in their

methodologies that may not provide the best insight into school quality. These rankings often

involve many criteria that obscure actual school quality and create less accurate rankings. For

instance, the New Jersey Monthly Magazine High School Ranking weighs graduation rate and

college matriculation rate most heavily, even though these factors involve many inherent

problems. For instance, among lower performing schools, college matriculation and graduation

rates are often influenced by socioeconomic factors, and at higher performing schools such

factors are often altered dramatically by students attending university in foreign countries or

private universities that do not confirm matriculation. For these reasons, though graduation and

matriculation rates may reflect school quality to an extent, they also reflect many other factors

unrelated to school quality that make rankings less accurate. If a school provides a robust

academic environment, evident by high SAT and AP scores, it follows that students should have

the ability to succeed at a college or university; therefore, academic performance based on

standardized test scores is a more reliable and better criteria for determining school strength as it

does not involve the inherent problems that accompany measuring by matriculation or graduation

TENAFLY HIGH SCHOOL ACADEMIC RESEARCH 3

rates. Additionally, while socioeconomic factors certainly play a role in performance of districts,

rankings still do provide insight into the differences between districts of similar financial status.

For these reasons, in this analysis, only AP scores and SAT scores, based on data taken

from the NJ Department of Education (NJDOE) school performance database on 313 public,

non­magnet high schools, were used in determining school ranking. These two criteria are

especially promising due to their strong correlation, indicating that performance on these two

standardized tests are strongly associated and therefore together reveal an overall trend in student

performance as seen in the graphs below. While a correlation showing student performance is

evident between SAT scores and AP scores, there may be a weaker correlation between these

two criteria and PARCC scores, as the PARCC is a very new exam with less reliable data

available. Additionally, though the ACT may potentially be a good indicator of school strength,

it is less popular than the SAT in New Jersey and the the NJDOE database does not provide

sufficient ACT data for analysis.

Though SAT and AP scores are strongly correlated, it is important that both, not only

one, of the criteria are used. AP scores are extremely useful as they directly test material taught

in the curriculum of AP courses. While the SAT may not directly test a course curriculum, it

does test skills in english and mathematics taught in the classroom. Additionally, the SAT is

taken by many students, regardless of their strength in academics, it factors in the performance of

lower performing students, while examining AP scores provides a better understanding of higher

performing students. The importance of using both metrics together is evident in the final

rankings as many schools have a significant disparity between their SAT and AP ranking, such

as Northern Valley Regional High School which is ranked 9 by SAT but 58 by AP,

TENAFLY HIGH SCHOOL ACADEMIC RESEARCH 4

demonstrating that these two highly correlated, but also different metrics provide a more

comprehensive description of academic performance when examined together.

To determine rankings, schools were given two sub­rankings, one by average SAT score,

and the other by the product of percentage of Juniors and Seniors taking AP tests in english,

math, social studies, or science and the percentage of students earning scores of three or above

on those exams. Whereas some rankings such as the New Jersey Monthly Magazine annual

rankings sum the percentage of students taking AP tests with percentage of students receiving

scores over 3, this is a flawed methodology as it rewards schools who encourage students to take

AP tests regardless of how they will perform in order to increase participation scores. If the two

values are multiplied instead, encouraging weaker students to take AP tests in order to improve

participation will not improve rank as the participation value will be multiplied by a lower score

value. These two sub­rankings were then averaged, providing a final ranking.

TENAFLY HIGH SCHOOL ACADEMIC RESEARCH 5

Figure 1­ The scatterplot above shows the correlation between the SAT indices and the AP

indices. The R­squared value of 0.796 for the dataset which indicates there is a strong positive

correlation between the SAT performance and the AP performance for the public, non­magnet

high schools in New Jersey. Data was obtained from the New Jersey Department of Education

using SQL. Plots were obtained using the software R.

Figure 2­ The Q­Q plot above demonstrates that the residual plot is random,

showing the accuracy of this model.

TENAFLY HIGH SCHOOL ACADEMIC RESEARCH 6

New Jersey High School Rankings based on SAT­AP Composite Methodology

Rank Rank by AP Rank by SAT

School Name

1 2 1 PRINCETON HIGH SCHOOL

2 3 5 DR RONALD MCNAIR HIGH SCHOOL

2 5 3 MILLBURN HIGH SCHOOL

4 7 4 WEST WINDSOR­PLAINSBORO HIGH SCHOOL SOUTH

4 9 2 WEST WINDSOR­PLAINSBORO HIGH SCHOOL NORTH

6 1 12 CHATHAM HIGH SCHOOL

7 6 11 MOUNTAIN LAKES HIGH SCHOOL

8 10 8 JOHN P. STEVENS HIGH SCHOOL

9 4 18 SUMMIT HIGH SCHOOL

10 19 6 MONTGOMERY HIGH SCHOOL

11 16 10 RIDGE HIGH SCHOOL

12 14 13 LIVINGSTON HIGH SCHOOL

13 8 21 RUMSON­FAIR HAVEN REGIONAL HIGH SCHOOL

13 22 7 TENAFLY HIGH SCHOOL

15 11 20 GLEN ROCK HIGH SCHOOL

16 17 16 NORTHERN HIGHLANDS REGIONAL HIGH SCHOOL

17 23 14 HADDONFIELD MEMORIAL HIGH SCHOOL

18 15 24 NORTH HUNTERDON HIGH SCHOOL

TENAFLY HIGH SCHOOL ACADEMIC RESEARCH 7

19 21 19 CRESSKILL HIGH SCHOOL

20 20 22 BERNARDS HIGH SCHOOL

21 18 27 GLEN RIDGE HIGH SCHOOL

22 13 36 WEST MORRIS MENDHAM HIGH SCHOOL

23 25 26 MADISON HIGH SCHOOL

24 29 25 HOPEWELL VALLEY CENTRAL HIGH SCHOOL

25 40 15 RIDGEWOOD HIGH SCHOOL

26 26 30 SOUTH BRUNSWICK HIGH SCHOOL

26 27 29 WESTFIELD SENIOR HIGH SCHOOL

28 37 23 HOLMDEL HIGH SCHOOL

29 58 9 NORTHERN VALLEY REG HIGH SCHOOL AT DEMAREST

30 24 44 WEST MORRIS CENTRAL HIGH SCHOOL

31 30 39 KINNELON HIGH SCHOOL

32 33 37 MARLBORO HIGH SCHOOL

33 41 33 MOORESTOWN HIGH SCHOOL

34 34 41 NEW PROVIDENCE HIGH SCHOOL

35 38 42 HUNTERDON CENTRAL REGIONAL HIGH SCHOOL

36 28 53 VOORHEES HIGH SCHOOL

37 12 70 CRANFORD HIGH SCHOOL

38 54 34 BRIDGEWATER­RARITAN REGIONAL HIGH SCHOOL

39 35 54 RAMAPO HIGH SCHOOL

TENAFLY HIGH SCHOOL ACADEMIC RESEARCH 8

39 42 47 GOVERNOR LIVINGSTON HIGH SCHOOL

41 59 32 EAST BRUNSWICK HIGH SCHOOL

42 55 40 METUCHEN HIGH SCHOOL

43 48 48 PASCACK HILLS HIGH SCHOOL

44 65 31 WATCHUNG HILLS REGIONAL HIGH SCHOOL

44 79 17 NORTHERN VALLEY REG OLD TAPPEN HIGH SCHOOL

46 31 66 HANOVER PARK HIGH SCHOOL

47 43 55 WHIPPANY PARK HIGH SCHOOL

48 62 38 RANDOLPH HIGH SCHOOL

49 52 51 FORT LEE HIGH SCHOOL

50 49 58 PARK RIDGE HIGH SCHOOL

51 44 64 LEONIA HIGH SCHOOL

51 80 28 CHERRY HILL HIGH SCHOOL EAST

53 60 52 COLTS NECK HIGH SCHOOL

54 70 43 INDIAN HILLS HIGH SCHOOL

55 81 35 HILLSBOROUGH HIGH SCHOOL

56 39 79 COLUMBIA HIGH SCHOOL

57 74 45 RIVER DELL REGIONAL HIGH SCHOOL

58 61 59 MAHWAH HIGH SCHOOL

59 45 77 MIDLAND PARK JR./SR. HIGH SCHOOL

60 66 57 PARAMUS HIGH SCHOOL

61 75 49 MONTVILLE TOWNSHIP HIGH SCHOOL

62 63 63 RAMSEY HIGH SCHOOL

TENAFLY HIGH SCHOOL ACADEMIC RESEARCH 9

63 71 56 PARSIPPANY HIGH SCHOOL

64 56 76 SCOTCH PLAINS­FANWOOD HIGH SCHOOL

64 64 68 FREEHOLD BOROUGH HIGH SCHOOL

66 32 101 RED BANK REGIONAL HIGH SCHOOL

67 85 50 EASTERN REGIONAL HIGH SCHOOL

68 90 46 ROBBINSVILLE HIGH SCHOOL

69 57 80 WEST ESSEX HIGH SCHOOL

70 50 91 VERONA HIGH SCHOOL

71 67 75 SOUTH HUNTERDON HIGH SCHOOL

72 76 69 WAYNE VALLEY HIGH SCHOOL

73 68 78 SPARTA HIGH SCHOOL

74 77 71 JAMES CALDWELL HIGH SCHOOL

75 86 65 MONTCLAIR HIGH SCHOOL

76 36 118 MORRIS HILLS HIGH SCHOOL

76 82 72 WAYNE HILLS HIGH SCHOOL

78 69 86 MAINLAND REGIONAL HIGH SCHOOL

79 97 60 PEQUANNOCK TOWNSHIP HIGH SCHOOL

80 51 108 SHORE REGIONAL HIGH SCHOOL

81 87 73 FAIR LAWN HIGH SCHOOL

82 88 74 PASCACK VALLEY HIGH SCHOOL

83 46 117 JONATHAN DAYTON HIGH SCHOOL

83 102 61 SOMERVILLE HIGH SCHOOL

85 109 62 PARSIPPANY HILLS HIGH SCHOOL

86 91 81 ALLENTOWN HIGH SCHOOL

TENAFLY HIGH SCHOOL ACADEMIC RESEARCH 10

87 92 82 MORRIS KNOLLS HIGH SCHOOL

88 83 95 HENRY HUDSON REGIONAL SCHOOL

89 93 96 MORRISTOWN HIGH SCHOOL

90 89 102 DUMONT HIGH SCHOOL

91 72 123 EDISON HIGH SCHOOL

91 110 85 FREEHOLD TOWNSHIP HIGH SCHOOL

93 103 93 MONROE TOWNSHIP HIGH SCHOOL

94 73 125 OCEAN CITY HIGH SCHOOL

95 94 105 POINT PLEASANT BOROUGH HIGH SCHOOL

96 113 87 WALL HIGH SCHOOL

97 95 106 RUTHERFORD HIGH SCHOOL

98 78 124 ELIZABETH HIGH SCHOOL

98 114 88 MANASQUAN HIGH SCHOOL

100 98 110 WALDWICK HIGH SCHOOL

Discussion

A chi­squared test was executed to determine the similarity between the top 30 schools’

data. A two­way data table was created with the high schools’ AP Indices and average composite

SAT scores (based on 2015­2016 data) as the columns; the rows were the top 30 schools,

according to the above ranking. The expected value of each item reflected the proportion of that

value to the entire sum of all the values in the data table.

TENAFLY HIGH SCHOOL ACADEMIC RESEARCH 11

The test was first performed on the top 30 schools, then on the top 25, top 15, top 10, and

finally, on the top 5. The resulting P values for each test were then recorded in a data table.

The null hypothesis was that the top schools are homogenous. This would mean that

differences among the schools’ data are so statistically insignificant, that the data for all of the

schools can essentially be considered the same. If the P value was below the chosen significance

level of .05, then the null hypothesis must be rejected; however, with a P value greater than the

chosen significance level of .05, then the null hypothesis must fail to be rejected.

According to the P values listed below in Figure 3, the null hypothesis must be rejected

for the top 30 schools, since there is a P value less than .05. This means that when comparing the

AP Indices and average composite SAT scores among the schools, there is a statistically

significant difference. Thus, such notable discrepancies among the schools’ data confirmed that

it is necessary to individually rank the top 30 schools. Nonetheless, the P values in Figure 3 for

the top 25 schools, up to the smallest grouping of just the top 5 schools, are all larger than .05, so

the null hypothesis must fail to be rejected, revealing that the top 25 schools are, in fact,

homogenous. The differences in the schools’ data are so statistically insignificant that the schools

cannot, and should not, be ranked individually. They must be grouped into a single unit, a tier.

These top 25 schools should simply be viewed as the ‘top tier.’

TENAFLY HIGH SCHOOL ACADEMIC RESEARCH 12

Number of Top High Schools Included

P value for Chi­Squared Test run

30 0.004156

25 0.07599

20 0.3213

15 0.229

10 0.1968

5 0.4217

Figure 3­ This figure shows the P value for each grouping of top high schools.

II. Prediction of New Jersey Monthly High School Ranking

Prediction of the New Jersey Monthly 2015­2016 High School Ranking

The top 30 New Jersey public schools were selected based solely on their 2014­2015

SAT rankings. Then, the New Jersey Monthly methodology for ranking high schools was used to

rank these 30 schools based on the 2014­2015 School Performance Reports for each school

(these can be accessed on the State of New Jersey Department of Education website).

The New Jersey Monthly divides data into three categories, each with a different

weight­­­School Environment (weight of 1), Student Performance (weight of 1.5), and Student

TENAFLY HIGH SCHOOL ACADEMIC RESEARCH 13

Outcomes (weight of 2.1)­­­and each with a number of subcategories. For further detail

regarding the magazine’s strategy, please reference their article entitled “Top Schools 2014:

Methodology.”

For this paper, the same methodology was utilized, and the data for each category was

pulled from the 2014­2015 School Performance Reports. After compiling the data into the

categories and subcategories outlined by the New Jersey Monthly, the schools were ranked

within each subcategory. The number each school was ranked was then multiplied by the weight

assigned to the umbrella category that the subcategory was a part of. For each school, the

weighted rankings for every subcategory were added together.

The sum of lowest numerical value corresponds to the best overall ranking (a ranking of

number one), because schools are ranked within each subcategory with a ranking of one

indicating the top school. Thus, when adding the weighted rankings, a final sum of low

numerical value would mean a school ranked close to the top in many subcategories. The results

show that Tenafly would be ranked at 24.

III. Comparison of Middle Schools and High Schools

While high school rankings can be evaluated based on criteria such as SAT and AP

scores, middle schools are far more difficult to rank as middle school students typically do not

take many standardized tests. When considering the strength of middle schools, parents often

look at the strength of the district’s high school, assuming that strong a high school should reflect

TENAFLY HIGH SCHOOL ACADEMIC RESEARCH 14

a strong middle school. To determine whether this assumption is correct, PARCC math scores

were compared with high school SAT math scores to test for a correlation between middle and

high school strength.

This analysis was performed by comparing the average math section SAT I score in each

of New Jersey’s top 100 high schools with the percent of students earning scores of 4 or 5 on the

math section of the PARCC in those districts’ respective middle schools. A linear model and

power model were both tested for goodness of fit, revealing that though the linear model is most

accurate, it shows only a relatively weak correlation with an R­squared value of 0.339. These

results suggest that middle school quality and high school quality are not strongly associated.

Alternatively, these results could reflect that the PARCC score is not an accurate measurement of

middle school strength.

Figure 4­ Above shows the linear model of the relationship between high school math SAT

scores and middle school PARCC math scores, with R­squared value of 0.339.

TENAFLY HIGH SCHOOL ACADEMIC RESEARCH 15

Figure 5­ Above is a Q­Q plot for the residuals of the linear model.

Figure 6­ Above shows the power model of the relationship between high school math SAT

scores and middle school PARCC math scores, with R­squared value of 0.2279.

TENAFLY HIGH SCHOOL ACADEMIC RESEARCH 16

Figure 7­ Above is a Q­Q plot for the residuals of the power model.

IV. Conclusion

Findings in this paper have shown that AP and SAT scores are the most valuable indicators of

student performance in high schools; for this reason, they were the only two components

factored into the novel ranking method described in part I. However, in the future, after the

PARCC exam has been in practice for a longer period of time, it is possible that the

aforementioned ranking methodology would have to be amended to include the PARCC scores,

because such scores may eventually better reflect student performance if schools and students

place more focus on the assessment. Additionally, as the ACT rises in popularity, it might also

need to be included in the part I ranking methodology, for it could represent a large sector of the

student population. With standardized tests playing such a key role in ranking high schools,

TENAFLY HIGH SCHOOL ACADEMIC RESEARCH 17

modifying schools’ curriculums to become more aligned with these assessments could be

beneficial for school districts. Aside from potentially boosting some schools’ rankings, this shift

could also help students excel academically, for it would ensure that students would be learning

material that is widely deemed advantageous.

References

[1] http://njmonthly.com/articles/towns­schools/top­schools­alphabetical­list/

[2] https://education.state.nj.us/pr/