Search for notes by fellow students, in your own course and all over the country.
Browse our notes for titles which look like what you need, you can preview any of the notes via a sample of the contents. After you're happy these are the notes you're after simply pop them into your shopping cart.
Document Preview
Extracts from the notes are below, to see the PDF you'll receive please use the links above
STA 114 STA 114 - GENERAL STATISTICS
Module Two - Presentation of Data
DR A
...
OGUNDE AND VICTORIA E
...
, 2025
An Overview of Lecture
⇒ Tabular presentation
⇒ Classification
⇒ Guidelines for the construction of tables
⇒ Definition of some terms under classification and tabulation
⇒ Steps for constructing a frequency distribution table from raw data
⇒ Diagram presentations (Bar Chart, Histogram, Frequency
Polygon, Stem & Leaf)
Tabular Presentation
q This is an orderly and precise arrangement of numerical information in columns and
rows
...
Classification
This is a process of arranging observations into logical, meaningful, useful categories in
accordance with the nature of property under-study
...
Classification Cont’d
Ideally, a group or class must be homogenous, that is, it should include all items and only
those items with definite characteristic of data
...
Each item must belong to
only one class (Exclusive)
Example of Classisfication
Guidelines For Consturuction of a Table
• We have seen from the Tables above most of the desirable features of a good
table
...
• All that is necessary is to pay attention to the more obvious and simple points
...
• It should present the data clearly, highlighting important details
...
It must be easily interpreted
...
This is because, quite often, a text table could be used by some other person as a
reference material
...
Approximation and
omission should be explained in footnote
...
Frequency Distribution Table
• Frequency distribution is a tabular arrangement of data by classes together with the
corresponding class frequencies
...
• However we need not use exact values as the classes
...
• The frequency distribution tables are of fundamental importance in statistics
...
A class that does not have either an upper and lower limit is
called an open- ended class
...
The class
limits can be defined in either of the following methods:
Ø Exclusive Method: In this method, the upper limit of a class is taken to be equal to
the lower limit of the following class
...
Frequency Table Classification Terms Cont’d
• Inclusive Method:- In this method, all the observations with magnitude greater
than or equal to the lower limit but less than or equal to the upper limit of a class is
included in it
...
It is a point where the lower class ends
and the higher class begins
...
It is sometimes
described as the arithmetic average of the two class limits (that is, the lower limit
and the upper limit)
...
����� ���������� + ����� ����������
����� ���� =
Frequency Table Classification Terms Cont’d
• Class size: - is the difference between the upper and lower class boundaries
...
• Class frequency: - is the number of observations that fall in a class
...
• Cumulative frequency: - is the total frequency of all values less than or equal to
the upper class boundary of a given class interval
...
5
40
...
5
51 - 60
51
60
10
55
...
5
60
...
5
60
...
5
71 - 80
71
80
10
75
...
5
80
...
050
5
...
175
17
...
500
50
...
075
7
...
100
10
PhD
4
0
...
• Determine the number of classes by dividing the range into a convenient number of
class intervals having the same size
...
• The length of a class or class interval is determined by the number of classes and the
range of the data, that is, we divide the range by the number of classes chosen in (2)
...
g
...
Steps for constructing a frequency distribution table from raw data
• Class intervals are also chosen so that the classmarks or midpoints coincide with actual
observed data
...
• Determine the number of observations falling into each class interval, that is, find the
class frequencies
...
• Classes should not overlap and there should be no gap
...
Diagram Presentation
• Diagrams prove nothing, but bring outstanding features readily to the
eye; they are therefore no substitute for such critical tests as may be
applied to the data, but are valuable in suggesting such tests, and in
explaining the conclusions founded upon them