Data classification and tabulation-1.pdf

Data classification and tabulation

1. DATA CLASSIFICATION
AND TABULATION

Dr. S. Malini
Associate Professor
Department of Economics
Ethiraj College for Women

2. •Arranging data into homogenous groups or classes according to some
common characteristics present in the data
•Process of sorting and categorizing data into various types, forms or any
other distinct class


CLASSIFICATION
Quantitative
Weight , Scores,
Per Capita Income
Qualitative
Gender ,
Intelligence
Geographical
Regions, States,
Cities, Countries
Chronological
Years , Days,
Months
BASES OF CLASSIFICATION

3. •Simplification and Briefness: Classification presents data in a brief manner. Hence, it
becomes fairly easy to analyze the data.
•Utility: As classification highlights the similarity in the data, it brings out its utility.
•Distinctiveness: With the help of grouping data into different classes, classification
also brings out the distinctiveness in data.
•Comparability: it facilitates comparison of data.
•Scientific Arrangement: Classification arranges data on scientific lines. Thus it also
increases the reliability of data.
•Attractive and Effective: Lastly, through the process of classification, data becomes
effective and attractive.

USES OF CLASSIFICATION

4. Systematic & logical presentation of numeric data in rows and columns
It facilitates comparison by bringing related information close to each other and helps
in further statistical analysis and interpretation.
TABULATION
Simplify data
Essential features of data
Facilitate comparison and further analysis
Highlight the features of Data
Draw Inferences
Objectives of tabulation

5. PARTS OF A TABLE






Table Number easy reference and identification a table should be numbered.
written in the centre at the top of the table. Sometimes it is written just before the title of
the table.
Title clearly worded, brief and unambiguous title describing the nature of data contained in the
table. placed centrally on the top of a table, just below the table number (or just after table
number in the same line).
Captions brief and self-explanatory vertical columns. It may involve headings and sub-headings as
well. The units of data contained should also be given for each column
Stubs

brief and self-explanatory headings of horizontal rows. Also a variable with a large
number of classes is usually represented in rows.
Body numerical information or frequency of observations in the different cells. This arrangement
of data is according to the description of captions and stubs.
Footnotes foot of the table for explanation of any fact or information included in the table which
needs some explanation. meant for explaining or providing further details about the data,
that have not been covered in title, captions and stubs.
Sources of Data source of information from which data are taken. include the name of the author, volume,
page and year of publication.

6. RELATED CONCEPTS TO TABULATION
Frequency Distribution – the principle of classifying data into
groups
Class interval -the numerical width of any class in a particular
distribution difference between the upper-class limit and the
lower-class limit
Illustration – Age of 10 Persons 8, 19, 58, 35, 45, 12, 6, 13, 18, 47
Class limits- Lower and upper-class limits
Lower class limit - the smallest possible data value assigned to
the class
Upper-class limit – the largest possible data value assigned to
the class
Class midpoint - the value halfway between the lower and upper
limit of the class
Age 0-20 20-40 40-60
Frequency 6 1 3

7. Cumulative Frequency
The running total of frequencies. It is
the sum of all the previous frequencies
up to the current point









Tally Bar
Representation of the data in the form
of vertical lines



CI f C.f
5 2 2
8 6 8
10 8 16
12 10 26
Marks Tally bar Frequency
10 |||| 4
20 || 2
30 | 1

8. Diagrammatic data presentation allows us to
understand the data more easily.
Types of Diagrams
Bar Charts – It commonly used to compare
several categories of data. Each rectangular bar
has a length and height proportional to the
values it represents. One axis of the bar chart
presents the categories being compared. The
other axis shows a measured value
Pie Charts- displays data and statistics in an
easy-to-understand ‘pie-slice’ format and
illustrates numerical proportion. It is a circle
representing all the data given. The 360 degrees
about the centre of the circle is divided up
according to the proportions of the different
quantities shown
DIAGRAMMATIC REPRESENTATION
0
1
2
3
4
5
6
Category 1 Category 2 Category 3 Category 4
Bar Chart
Series 1 Series 2 Series 3
58% 23%
10%
9%
PIE CHART
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr

9. Line Chart –It graphically displays data that changes
continuously over time. It used to show trends, for comparison,
Make predictions
Histograms - Compares the distribution or frequency of different
values or ranges of values. Class intervals are usually of equal
width
Frequency Polygon- Histogram is another way of representing a
frequency distribution on a graph. You draw a frequency polygon
by joining the midpoints of the upper widths of the adjacent
rectangles of the histogram with straight lines.
Stem and Leaf diagrams -numerical representation of the data
where the most significant digit is highlighted.
Cumulative Frequency Curve – 0 gives are of two types – ‘less
than 0 give’ and ‘more than 0 give’.
Graphs - Use of graphs in interpreting data, trends and
forecasting, easier to understand
0
2
4
6
Line Chart
Series 1 Series 2
Series 3

10. MERITS AND DEMERITS OF DIAGRAMMATIC REPRESENTATION
Merits
Easy to Understand
Simplified Presentation
Quick to grasp
Reveals hidden facts
Easy to compare
Universally accepted
Demerits
Limited
information
Restricts further data analysis
Portrays limited characteristics
Fail to present a meaningful look
in certain situations
Possibility of misuse
Careful usage

11. THANK YOU