Chapter II: Frequency Distributions and Graphs
Outline
1.
Introduction
2.
Organizing data
3.
Histograms, frequency polygons and ogives
4.
Other types of graphs
5.
Summary
Objectives
1.
Organize data using frequency distributions
21.
Introduction
When conducting a statistical study, the researcher must gather data fort he particular
variable under study. For example, if a researcher wishes to study the number of people who
were bitten by poisonous snakes in a specific geographic area over the past several years, he
or she would have to gather the data from various doctors, hospitals, or health departments.
In order to describe situations, draw conclusions, or make inferences about events, the
researcher must organize the data in some meaningful way. The most convenient method of
the organizing data is to construct a frequency distribution.
After organizing the data, the researcher must present them so they can be understood by
those who will benefit from reading the study. The most useful method of presenting the data
is by constructing statistical charts and graphs. There are many different types of charts and
graphs, and each one has a specific purpose.
This chapter explains how to organize data by constructing frequency distributions and
how to present the data by constructing charts and graphs. The charts and graphs illustrated
here are histograms, frequency polygons, ogives, pie graphs, Pareto charts, and time series
graphs.
22.
Organizing Data
There are several ways to collect and organize data.
The lesson on
measures of central
tendency
shows an example of using a tally/frequency table.
Other ways to organize and
collect data are:
1. Circle graphs
2. Broken line graphs
3. Frequency histograms
4. Cumulative frequency
histograms
5. Box and whisker plots
6. Scatter plots, and
7. Stem and leaf plots.
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View Full DocumentSometimes when dealing with large sets of data, it is more convenient to observe patterns
by grouping the data in intervals called classes and making a frequency distribution.
A
frequency distribution
is a table that shows
classes or intervals
of data entries with a
count of the number of entries in each class.
The frequency
ƒ
of a class is the number of data
entries in the class.
Each class has a
lower class limit
which is the least number that can
belong to the class and an
upper class limit
that is the largest number that can belong to a
class.
For example:
in the class of data 1225, 12 would be the smallest number in the set
and 25 would be the largest and the ƒ would be the number of data entries that fall between 12
and 25 inclusive.
The
class width
is the distance between the lower and upper class limits.
The difference between the minimum and maximum data entries is called the
range
.
Guidelines to Constructing a Frequency Distribution from a Data Set
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 Spring '10
 Frequency, Bar chart, Histogram, Statistical charts and diagrams

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