1. The document discusses the use of data tables and charts to summarize student performance data from three data sets: benchmark reading scores, student ethnicity, and student grades. 2. Tables 1-3 display the data sets using categories, frequencies, and relative frequencies. Table 4 combines the data sets and displays the percentages for each category. 3. The tables and charts provide easy to understand summaries of the data that can help administrators and teachers identify student performance trends and target areas for improvement.

1. Data Frequency
1
Data Frequency
Michael Adams
EDU 530
January 17, 2014
Dr. Elaine Omann

2. Data Frequency
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Data is an essential tool employed by nearly every worker within the educational arena.
As a school leader, data usage is paramount for daily operations. Administrators are constantly
processing information concerning “assessments, demographic data, dropout rates, graduation
rates, course-taking patterns, attendance data, survey data, and on and on” (DiRanna, Love,
Mundry, & Styles, 2008, p.16). Directors of schools are charged with not only understanding
and utilizing this invaluable tool, but are equally responsible for delegating this clarity and use to
others within the school. Improper usage of data can result in a range of problems, from simple
error in comprehension of information to catastrophic setbacks and data abuse associated with
poor application (DiRanna, Love, Mundry, & Styles, 2008). School leaders should recognize the
potential for data misuse and avoid such pitfalls by applying more time and energy in data
comprehension.
One way of simplifying data understanding is by breaking it down into subgroups, or
disaggregating the data. “Examining data by subgroups can show important trends and patterns”
(Data analysis for Instructional Leaders, 2013) in a simplified manner. The researcher can then
place this basic information into easy to grasp charts or tables. The tables in this paper will
display fundamental subcategories of data along with its corresponding frequency and data
percentages.
Table 1 viewed on the following page reveals Benchmark levels for one class of 8th grade
students in the following subcategory: 2013 NG=Reading Application Level. These benchmark
reading scores help administration and teachers track at risk students who are in need of
intensive reading classes. They also help target “bubble” students who “fall just a few points
short of a proficiency-level cut point” (DiRanna, Love, Mundry & Styles, 2008, p.155). The
scores are disaggregated into five levels, with one being the lowest (at risk students) and five

3. Data Frequency
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being the highest. Additionally, the simple frequency in which each level occurred is shown,
along with the relative frequency, or the percentage of the total.
Table 1 – 1st Period Benchmark Reading Scores: Reading Application Levels
Benchmark Reading Score
Reading Application Levels
2013
Level 1
Level 2
Level 3
Level 4
Level 5
Frequency
Relative Frequency
2
1
5
2
0
10
.2
.1
.5
.2
0
1
With a junior high school boasting over 1400 students, including over 600 8th graders, it’s
easy to see how an application of data such as this could accommodate such a large number of
students. This table provides administrators, guidance, and teachers an easy to understand data
set with extremely useful knowledge of student reading comprehension levels. While there is
more detailed data pertaining to reading scores, such as student scale scores, sometimes a
broader scope is needed to group larger categories.
The next chart below, table 2, shows the ethnicity of the same group of 8th graders.
Table 2 – 1st Period Student Ethnicity
1st Period Student Ethnicity
White, non-Hispanic
Black, non-Hispanic
Hispanic
Asian or Pacific Islander
Multi-Racial
Frequency
5
3
0
2
0
Cumulative Frequency
5
8 (5+3)
8 (8+0)
10 (8+2)
10 (10+0)
This table clearly exhibits the number of different races within one classroom. The cumulative
frequency that’s employed here provides the researcher with a way to ensure that all of the data

4. Data Frequency
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points are correct. It’s important for administrators to understand the disparity between different
ethnicities within the school. “One of the key policy accomplishments in the post–civil rights era
has been a reduction in the achievement gap between whites and blacks” (Taylor, 2006, pg.3).
Research has proven that information depicting ethnicities, genders, and demographics at school
is instrumental in closing achievement gaps. The children we are losing in the data gap tend to be
those “of color, English Language Learners, children living in poverty, and those with
exceptional needs” (DiRanna, Love, Mundry & Styles, p.16). Tables such as the one above
provide education professionals with the information on ethnicities in a clear and concise
manner. The audience for this data includes administration, guidance, and teachers.
Table 3 – 1st Period Student Percentage Grades (Before Rounding)
Student Percentage Grade
Semester Average
90-100
80-89
70-79
60-69
0-59
Frequency
Relative Frequency
4
3
3
0
0
10
.4
.3
.3
0
0
1
The above table 3 illustration plots 1st period student percentage grades. This simplistic
interval data is made even more user-friendly with the addition of the frequency information.
School leaders are repeatedly faced with limited time in the field. This particular classroom
achievement is easily summed up in this table. With school enrollment in excess of 1400
students, school leaders have to learn to use these informative tools. This information provides
the teachers and administrators with precise information on student averages. Audiences for this
information include teachers, administration, guidance, parents and students.

5. Data Frequency
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Table 4 below takes the three charts introduced in this paper and offers a combined view
of them with percentages for each data set. It is interesting to view the disaggregated data
lumped together in one compact table.
Table 4 – Data Set/Percentages
Data Set
Student Ethnicity
1st Period
Benchmark Reading Scores
Reading Application Levels
2013 – 1st Period
1st Period Student Percentage Grades
(Before Rounding)
1.
2.
3.
4.
5.
1.
2.
3.
4.
5.
1.
2.
3.
4.
5.
Categories
White, non-Hispanic
Black, non-Hispanic
Hispanic
Asian or Pacific Islander
Multi-Racial
Level 1
Level 2
Level 3
Level 4
Level 5
90-100
80-89
70-79
60-69
50-59
Percentages
1. 50%
2. 30%
3. 0%
4. 20%
5. 0%
1. 20%
2. 10%
3. 50%
4. 20%
5. 0%
1. 40%
2. 30%
3. 30%
4. 0%
5. 0%
There is a wealth of information complied on the data table above. We have Student Percentage
Grades, Benchmark Reading Scores, and Ethnicity tables for one particular 8th grade class.
Viewers of such research can quickly surmise areas of needed attention based on crossreferencing this disaggregated information at hand and creating a plan of action on where any
focus should occur. This mass of invaluable data can aid classroom teacher performance by
exposing areas of concern. It can also be used by data coaches who have been assigned the task
of educating the faculty on the multi-application of data at school. Additionally, this information
can be used by administration willing to go the extra mile and change the culture of one’s school
from an over-grown data “jungle” to a clean, well run, data-driven workplace.
Saint Leo University has already impressed this dedicated future school leader with the
way in which the data is learned. When future administrators get chills from reflecting on what

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has been learned so far concerning data sets, frequencies, and percentages, Saint Leo must know
they are doing something right. The university’s commitment to excellence is seen in every
lesson tackled, every assignment graded, and every bit of well-written feedback received from
the instructor. It is obvious that Saint Leo takes pride in their college on so many levels.

7. Data Frequency
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Tables and Charts
Table 1 – 1st Period Benchmark Reading Scores: Reading Application Levels
Benchmark Reading Score
Reading Application Levels
2013
Level 1
Level 2
Level 3
Level 4
Level 5
Frequency
Relative Frequency
2
1
5
2
0
10
.2
.1
.5
.2
0
1
Frequency
5
3
0
2
0
Cumulative Frequency
5
8 (5+3)
8 (8+0)
10 (8+2)
10 (10+0)
Table 2 – 1st Period Student Ethnicity
1st Period Student Ethnicity
White, non-Hispanic
Black, non-Hispanic
Hispanic
Asian or Pacific Islander
Multi-Racial
Table 3 – 1st Period Student Percentage Grades (Before Rounding)
Student Percentage Grade
Semester Average
90-100
80-89
70-79
60-69
0-59
Frequency
Relative Frequency
4
3
3
0
0
10
.4
.3
.3
0
0
1

8. Data Frequency
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Table 4 – Data Set/Percentages
Data Set
Student Ethnicity
1st Period
Benchmark Reading Scores
Reading Application Levels
2013 – 1st Period
1st Period Student Percentage Grades
(Before Rounding)
1.
2.
3.
4.
5.
1.
2.
3.
4.
5.
1.
2.
3.
4.
5.
Categories
White, non-Hispanic
Black, non-Hispanic
Hispanic
Asian or Pacific Islander
Multi-Racial
Level 1
Level 2
Level 3
Level 4
Level 5
90-100
80-89
70-79
60-69
50-59
Percentages
1. 50%
2. 30%
3. 0%
4. 20%
5. 0%
1. 20%
2. 10%
3. 50%
4. 20%
5. 0%
1. 40%
2. 30%
3. 30%
4. 0%
5. 0%

9. Data Frequency
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References
Florida School Leaders (2013). Data analysis for instructional leaders. Retrieved from
https://www.floridaschoolleaders.org/general/content/NEFEC/dafil/lesson2-2.htm
DiRanna, K., Love, N., Mundry, S., & Stiles, K. (2008). The data coach’s guide to
improving learning for all students. Thousand Oaks, California: Corwin Press
Taylor, R. (2006). Addressing the achievement gap: Findings and applications.
Greenwich, Connecticut: IAP-Information Age Publications. Retrieved from
http://saintleo.worldcat.org/title/addressing-the-achievement-gap-findings-andapplications/oclc/795566275&referer=brief_results

10. Data Frequency
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Frequency Data
(48 points)
Week 2
For your three data sets, determine the categories and the percentages for each of the categories.
Construct frequency charts for your three sets of data and then complete the chart. Expand the sections
on the chart to reflect the number of categories in each data set. Provide a rationale for the type of
frequency chart you developed for each data set. Use scholarly sources to support your ideas. In an APA
formatted paper include the complete data set, the frequency charts, the completed chart and any
interesting observations the percentages provided. Support your ideas with scholarly sources.
Rating:
Exceptional corresponds to an A (95-100%). Performance is outstanding; significantly above the usual
expectations.
Proficient corresponds to a grade of B to A- (83-94%). Skills and standards are at the level of expectation.
Basic corresponds to a C to B- (75-82%). Skills and standards are acceptable but improvements are needed to
meet expectations well.
Novice corresponds to an F (< 74%). Performance is weak; the skills or standards are not sufficiently
demonstrated at this time.
0 This criterion is missing or not in evidence.
Criteria
Ratings
0
Data Set
Complete data sets included
Categories identified
Frequency charts and rationale for type provided
supported by scholarly sources.
Characteri Percentages calculated correctly
Novice
Basic
Proficient
Exceptional
1
2
2.5
3
2-3
4-5
6-7
8-8.5
2-3
4-5
6-7
8-8.5
2-3
4-5
6-7
8-8.5
2-3
4-5
6-7
8-8.5
stics
Observations made about the data sets

11. Data Frequency
Narrative
11
Text satisfies all aspects of the written conventions
(cohesion, grammar etc.) as expected for a graduate
course including APA.
3-4
5-6
7-8
9-10
2
3
4
5
Core value of Excellence is specifically addressed.
Total Points:
Comments:
_____________48