This document discusses different methods for organizing data in research. It describes data organization as the process of structuring collected factual information in a way that is accepted by the scientific community. Proper data organization is important for research because it allows facts to be represented in context and helps researchers answer questions and hypotheses. The document then explains three common ways to organize data: frequency distribution tables, stem-and-leaf diagrams, and different types of charts including bar charts, pie charts, line charts, and histograms. Guidelines are provided for constructing each of these data organization methods.

1. DATA ORGANIZATION
-ROWELL A. BALALA

2. WHAT IS DATA ORGANIZATION?
A process organizing collected factual material
commonly accepted in the scientific community as
necessary to validate research findings.
“Research data is data that is collected, observed,
or created, for purposes of analysis to produce
original research results”(Boston University
Libraries, n.d.a).

3. WHY IS DATA IMPORTANT IN RESEARCH?
 Data are intended to represent facts and without
proper preservation of the context of collection and
interpretation, may become meaningless (Boston
University Libraries, n.d.a).
 The collection of data and its analysis assists
researchers with discovering answers to their research
questions and hypotheses. In some cases, it even
predicts future outcomes (Office of Research Integrity,
n.d.a).

4. WAYS OF ORGANIZING DATA IN RESEARCH
1. Frequency Distribution Table
2. Stem and Leaf Diagram
3. Chart

5. 1. FREQUENCY DISTRIBUTION TABLE
To construct a frequency table, We use the following steps
1. Construct a table with three columns. Then in the first column,
write down all of the data values in ascending order.
2. To complete the second column, go through the list of data
values and place one tally mark at the appropriate place in the
second column for every data value. When the fifth tally is
reached for a mark, draw a diagonal line through the first four
tally marks. We continue this process until all data values in the
list are tallied.
3. Count the number of tally marks for each data value and write it
in the third column.

6. A. CATEGORICAL/ UNGROUP - Determine the order to
list the categories then total the number of occurrences
of each category.
Example:
The following data represents the scores of 10 students
8 6 4 5 8 8 9 10 10 6
TYPES OF FREQUENCY DISTRIBUTION

7.  Construct a table with three columns. The first column
shows what is being arranged in ascending order (i.e.
the scores). The lowest mark is 4. So, start from 4 in
the first column as shown below. The second column is
Tally, third is frequency.
Scores Tally Frequency
4 I 1
5 I 1
6 II 2
7 0 0
8 III 3
9 I 1
10 II 2

8. B. GROUP - It refers to data being organized into groups known as
classes.
GUIDELINES
1. Use between 5 – 20 classes
2. Classes are mutually exclusive
3. Include all classes even if the frequency is zero
4. Use the same width for all classes
5. Use convenient numbers for the class limit
6. The sum of the frequency must total the data set
7. Have enough classes for all the data
8. Remember to use 0 if the class has no data, don’t leave it blank.

9. The following data represents the ages of 20 respondents
21 26 18 45 32 41 42 22 28 26
33 20 26 44 46 21 24 36 39 30
1. Determine the highest and lowest value and then compute the
Range:
Range = Highest value- Lowest value, Range = 46 - 18 = 28.
2. Decide how many numbers of classes you want to have. Example:
5 Classes
3. Compute the Class width or class interval
i = Class Interval = Range/# of Classes = 28/5 = 5.6 or 6
Or in calculator, you may use the equation below:
Log # of observation/log2 or # of Observation

10. 4. Lower class limit (Smallest number of each class) and
upper class limit (largest number of each class) Example:
LCL = 18,24,30,36,42 UCL = 23,29,35,41,47
5. Class Boundaries – The number that separates the
classes from one another by Subtracting .5 to Lower limit
and add .5 to upper limit of each class.
Example: (LL) 18 - .5 = 17.5 (Class Boundary) and (UP) 23 +
.5 = 23.5 (Class Boundary)

11. we proceed as follows:
Age Tally Frequency
18-23 IIII 5
24-29 IIII - I 6
30-35 III 3
36-41 II 2
42-47 IIII 4

12. 2. STEM AND LEAF DIAGRAM
A method used to organize statistical data that
helps us to see values according to their size, so we
can order them accordingly. In a stem-and-leaf
diagram, each data value is split into a stem and a
leaf. The leaf is the last digit to the right. The stem
is the remaining digits to the left. For the number
243, the stem is 24 and the leaf is 3.

13. Example: The following data represents the science test
scores for the third grading period (out of 100%):
97 92 77 82 96 75 68 80 79 96
21 34 55 84 87 68 87 88 97 81
STEM LEAVES
2
3
5
6
7
8
9
1
4
5
8 8
5 7 9
0 1 2 4 7 7 8
2 6 6 7 7

14. 3. GRAPH OR CHART
Graphs or charts condense large amounts of information
into easy-to-understand formats that clearly and effectively
communicate important points.
TYPES OF CHART
a. Bar Chart
b. Pie Chart
c. Line Chart
d. Histogram

15. A. Bar chart is composed of discrete bars that represent
different categories of data. The length or height of the
bar is equal to the quantity within that category of data.
Bar graphs are best used to compare values across
categories.
Example: The following data represents Peters’ Grades in
Science subject for 1st – 4th quarter.
Quarter Grades
First 84
Second 90
Third 89
Fourth 93
HOW TO CREATE BAR CHART?

16. B. Pie chart is a circular chart used to compare parts of
the whole. It is divided into sectors that are equal in size
to the quantity represented.
Example: The following data represent the monthly
household expenses of Rich family.
Household
expenses
Amount
Internet 1,000
Electricity 2,000
Grocery 4,000
Other 3,000
HOW TO CREATE PIE CHART?

17. C. Line chart displays the relationship between two types
of information, such as number of school personnel
trained by year. They are useful in illustrating trends over
time.
Example: The following data shows daily temperature in
Luna, La Union, recorded for 5 days in Degrees Celsius
HOW TO CREATE LINE CHART?
DAYS °C
MONDAY 29
TUESDAY 33
WEDNESDAY 31
THURSDAY 36
FRIDAY 34

18. D. Histogram has connected bars that display the frequency
or proportion of cases that fall within defined intervals or
columns. The bars on the histogram can be of varying width
and typically display continuous data.
Example: The following data represents the number of
respondents aged 8-55 who are disabled.
Age (years) Frequency
8 - 15 10
16 - 23 14
24 - 31 19
32 - 39 12
40 - 47 14
48 - 55 25
HOW TO CREATE HISTOGRAM?

19. GUIDELINES FOR FORMATTING CHARTS
 Keep it simple and avoid flashy special effects. Present only essential
information. Avoid using gratuitous options in graphical software programs,
such as three-dimensional bars, that confuse the reader. If the graph or chart is
too complex, it will not clearly communicate the important points.
 Title your graph or chart clearly to convey the purpose. The title provides the
reader with the overall message you are conveying.
 Specify the units of measurement on the x and y-axis. Years, number of
participants trained, and type of school personnel are examples of labels for
units of measurement.
 Label each part of the chart or graph. You may need a legend if there is too
much information to label each part of the chart or graph. Use different colors
or variations in patterns to help the reader distinguish categories and
understand your graph or chart.