Transcript Presentation Tabulation

Tabulation
By
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Objectives of Data Tabulation
To carry out investigations
 To do comparisons
 To locate omissions and errors in the data
 To use space economically
 To study the trends
 To simplify data
 To use it as future references
Session 01

Session 01
Importance of Tabulation

Under tabulation, data is divided into various parts and for
each part there are totals and sub totals. Therefore,
relationship between different parts can be easily known.
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Since data are arranged in a table with a title and a number
so these can be easily identified and used for the required
purpose
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Tabulation makes the data brief. Therefore, it can be easily
presented in the form of graphs.

Tabulation presents the numerical figures in an attractive
form.
Session 01
Importance of Tabulation

Tabulation makes complex data simple
and as a result of this, it becomes easy to
understand the data.

This form of the presentation of data is
helpful in finding mistakes.

Tabulation is useful in condensing the
collected data.
Session 01
Importance of Tabulation

Tabulation makes it easy to analyze the data
from tables.

Tabulation is a very cheap mode to present
the data. It saves time as well as space.

Tabulation is a device to summaries the large
scattered data. So, the maximum information
may be collected from these tables.
Rules of Tabulation
Session 01
There are no hard and fast rules for the tabulation of
data but for constructing good table, following general
rules should be observed while tabulating statistical
data.

The table should suit the size of the paper and,
therefore, the width of the column should be decided
before hand.

Number of columns and rows should neither be too
large nor too small.

As far as possible figures should be approximated
before tabulation. This would reduce unnecessary
details.
Session 01
Rules of Tabulation

Items should be arranged either in alphabetical,
chronological or geographical order or according to
size.

The sub-total and total of the items of the table must
be written.

Percentages are given in the tables if necessary.

Ditto marks should not be used in a table because
sometimes it create confusion.

Table should be simple and attractive.
Session 01
Rules of Tabulation

A table should be logical, well-balanced in length and
breadth and the comparable columns should be placed
side by side.

Light/heavy/thick or double rulings may be used to
distinguish sub columns, main columns and totals.

For large data more than one table may be used.
Session 01
Parts of an Ideal Table

Table number:
A number must be allotted to the table for
identification, particularly when there are many tables in
a study.

Title:
The title should explain what is contained in the table. It
should be clear, brief and set in bold type on top of the
table. It should also indicate the time and place to which
the data refer.
Parts of an Ideal Table
Date:
The date of preparation of the table should be given.

Stubs or Row designations:
Each row of the table should be given a brief heading. Such
designations of rows are called “stubs”, or, “stub items” and
the entire column is called “stub column”.

Column headings or Captions:
Column designation is given on top of each column to
explain to what the figures in the column refer. It should be
clear and precise. This is called a “caption”, or, “heading”.
columns should be numbered if there are four, or, more
columns.
Session 01
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Session 01
Parts of an Ideal Table

Body of the table:
The data should be arranged in such a way that any figure
can be located easily. Various types of numerical variables
should be arranged in an ascending order, i.e., from left to
right in rows and from top to bottom in columns. Column
and row totals should be given.

Unit of measurement:
If the unit of measurement is uniform throughout the
table, it is stated at the top right-hand corner of the
table along with the title. If different rows and columns
contain figures in different units, the units may be stated
along with “stubs”, or, “captions”.Very large figures may
be rounded up but the method of rounding should be
explained.
Session 01
Parts of an Ideal Table

Source:
At the bottom of the table a note should be added
indicating the primary and secondary sources from
which data have been collected.

Footnotes and references:
If any item has not been explained properly, a separate
explanatory note should be added at the bottom of the
table.
Session 01
Limitation of Tabulation

Tables contain only numerical data. They do not contain
details.

qualitative expression is not possible through tables.

Tables can be used by experts only to draw conclusions.
Common men do not understand them properly.
Methods of Tabulation
Session 02

Simple tabulation
Simple tabulation is when the data are
tabulated to one characteristic. For
example, the survey that determined the
frequency or number of employees of a
firm owning different brands of mobile
phones like Blackberry, Nokia, Iphone, etc.
Methods of Tabulation
Session 02

Double tabulation
Double tabulation is when two characteristics of data
are tabulated. For example, frequency or number of
male and female employees in the firm owning different
brand of mobile phones like Blackberry, Nokia, Iphone,
etc.
Methods of Tabulation
Session 02

Complex tabulation
Complex tabulation of data that includes more than
two characteristics. For example, frequency or number
of male, female and the total employees owning
different brand of mobile phones like Blackberry, Nokia,
Iphone, etc. Crosstabulations, is also a sub-type of
complex tabulation that includes cross-classifying
factors to build a contingency table of counts or
frequencies at each combination of factor levels. A
contingency table is a display format used to analyze and
record the possible relationship between two or more
categorical variables
Session 03
Frequency Tables

Simple frequency tables
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Grouped frequency tables
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Cumulative frequency tables
Session 03
Simple Frequency Tables

If the value of a variable, e.g., height, weight, etc.
(continuous), number of students in a class,

readings of a taxi-meter (discrete) etc., occurs twice or
more in a given series of observations,
then
the number of occurrence of the value is termed as the
“frequency” of that value.
Simple Frequency Tables
Session 03
Marks of 100 students of a class in economics
Simple Frequency Tables
Session 03
Simple frequency table for marks
Session 04
Grouped Frequency Tables
The tabulation of raw data by dividing the whole range
of observations into a number of classes and indicating
the corresponding class-frequencies against the classintervals,
is
called
“grouped
frequency
distribution”.
Thus the steps in preparing the grouped frequency distribution
are:
1. Determining the class intervals.
2. Recording the data using tally marks.
3. Finding frequency of each class by counting the tally arks.
Grouped Frequency Tables
Important Terms
Class-limits: The maximum and minimum values of a
class-interval are called upper class limit and lower
class-limit respectively

Class-mark, or, Mid-value: The class-mark, or, midvalue of the class-interval lies exactly at the middle of
the class-interval
Session 04
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Grouped Frequency Tables
Session 04
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Class boundaries: Class boundaries are the true-limits
of a class interval. It is associated with grouped
frequency distribution, where there is a gap between
the upper class-limit and the lower class-limit of the
next class.This can be determined by using the formula:
where d = common difference between the upper classlimit of a class-interval and the lower class limit
of the next higher class interval
Session 04
Grouped Frequency Tables

Width or Length (or size) of a Class-interval:
Width of a class-interval = Upper class boundary −
Lower class-boundary
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Relative frequency:
Session 04
Grouped Frequency Tables

Percentage frequency:

Frequency density:
Grouped Frequency Tables
Types of Grouped tables
Exclusive type
Session 04
Upper limit excluded
X
f
10 – 15
XX
15 – 20
XX
20 – 25
XX
25 – 30
XX
Grouped Frequency Tables
Exclusive type
Session 04
Lower limit excluded
X
f
Above 10 but no more than 15
XX
Above 15 but no more than 20
XX
Above 20 but no more than 25
XX
Above 25 but no more than 35
XX
Grouped Frequency Tables
Exclusive types
Session 04
Upper limit excluded
X
f
30 -
XX
40 -
XX
50 -
XX
60 -70
XX
Grouped Frequency Tables
Session 04
Inclusive type
X
f
30 – 39
XX
40 – 49
XX
50 – 59
XX
60 – 69
XX
Grouped Frequency Tables
Session 04
Open – End Type
X
f
0 – 10
XX
10 – 20
XX
20 – 30
XX
30 – over
XX
X
f
Below 30
XX
30 – 40
XX
40 – 50
XX
50 and over
XX
Grouped Frequency Tables
Session 04
Unequal class intervals
X
f
10 – 30
XX
30 – 35
XX
35 – 40
XX
40 – 60
XX
60 – 70
XX
70 – 100
XX
Multivariate Frequency Tables
Session 05
The multivariate frequency table is a statistic method to
organize and simplify a large set of data of two or more
variables in a single table.
Example:
Multivariate Frequency Tables
Session 05
Example: Multivariate frequency table
Multivariate Frequency Tables
Session 05
Example: Marginal frequency tables for X and Y
Multivariate Frequency Tables
Session 05
Example: Conditional Distribution X when Y Lies Between 300 and 400
Session 06
Cumulative Frequency Tables
The cumulative frequency table of a set of data is a table
which indicates the sum of the frequencies of the data
up to a required level. It can be used to determine the
number of items that have values below a particular
level.
Example: Construct the cumulative frequency distribution (both
“less than” and “more than” types) from the following data:
Cumulative Frequency Tables
Session 06
Example: Cumulative frequency table
Session 07 & 8
Cross Tabulation
Cross-tabs or cross tabulation is a quantitative research
method appropriate for analyzing the relationship between
two or more variables. Data about variables is recorded in
a table or matrix. A sample is used to gather information
about the variable.
Cross Tabulation gives you the ability to compare two
questions to each other and evaluate relationships between
the responses of those questions. You can review the
frequency and assess the statistical significance in that
relationship. Cross tabulation is particularly useful when you
want to assess whether there is a relationship between how
your entire respondent base, or a specific subset of
respondents, answered two questions.
Cross Tabulation
Session 07 & 8
General Hints When Constructing Tables
1. Make sure that all the categories of the variables presented in the
tables have been specified and that they are mutually exclusive (i.e.
no overlaps and no gaps) and exhaustive.
2. When making cross-tabulations, check that the column and row
counts correspond to the frequency counts for each variable.
3. Check that the grand total in the table corresponds to the number of
subjects in the sample. If not, an explanation is required. This could
be presented as a footnote. (Missing data, for example.)
4. Think of a clear title for each table. Also be sure that the headings of
rows and columns leave no room for misinterpretation.
5. Number your tables and keep them together with the objectives to
which they are related. This will assist in organizing your report and
ensure that work is not duplicated.
Session 07 & 8
Cross Tabulation - Descriptive Cross Tabulation
Example 1:
A study was carried out on the degree of job satisfaction among doctors
and nurses in rural and urban areas. To describe the sample a crosstabulation was constructed which included the sex and the residence
(rural or urban) of the doctors and nurses interviewed. This was useful
because in the analysis the opinions of male and female staff had to be
compared separately for rural and urban areas.
Type of health worker by residence
Cross Tabulation - Descriptive Cross Tabulation
Session 07 & 8
Residence and sex of doctors and nurses
Session 07 & 8
Cross Tabulation - Descriptive Cross Tabulation
Example 2:
We want to know the ages at which teenage pregnancies occur and
whether they are more frequent among schoolgirls than among girls who
are not attending school. In order to answer these questions we may
construct the following cross-tabulation.
Number of teenage pregnancies at different ages among girls
attending school and not attending school (Province X, 2000 - 2010)
Session 07 & 8
Cross Tabulation - Descriptive Cross Tabulation
Example 3:
A study was done to examine the factors contributing to the high
proportion of stillbirths in a hospital. The following cross-tabulation
describes how many of the fresh and macerated (wasted) stillbirths
weighed less than 2500 grams and how many weighed 2500 grams or
more.
Weight of foetus by condition at birth
Session 07 & 8
Cross Tabulation - Descriptive Cross Tabulation
Example 4:
In a cross-sectional survey on malnutrition, for example, relationships
could be tested between the duration of breastfeeding and the mothers’
age, or the mothers’ working status (answering previously formulated
research questions, but sometimes new questions that crop up during
analysis of the material).
Note that in such tables it is allowed to calculate your percentages both horizontally and vertically as all
variables have a similar chance of appearing in the survey. However, we will usually put the variable that is
assumed to influence the other one in rows, while the ‘dependent’ variable will be put in columns
Cross Tabulation - Descriptive Cross Tabulation
Session 07 & 8
Duration of breastfeeding by mothers’ age
Working status of mothers in relation to duration of breastfeeding
Session 07 & 8
Cross Tabulation - Analytic cross-tabulations
Example 5:
One of the possible contributing factors to malnutrition of under 5’s is
knowledge of the mothers of appropriate weaning foods. The crosssectional comparative study on malnutrition based on the survey gave
the following results
Mothers’ level of knowledge and nutritional status of their children