Classification and Tabulation, Business Mathematics & Statistics Video Lecture | Business Mathematics and Statistics - B Com

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well conference in this module we
discuss classification and tabulation
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classification classification is the
arrangement of collected information in
two homogeneous classes or groups
classification of the data is made
according to the nature and purpose of
the data for example the data on
households can be classified according
to religion income education etc the
marks of some students can be classified
into distinction first class second
class etc objectives of classification
objectives of classification are one to
reduce the complexity of the data during
classification unbonded details are
eliminated and the data are arranged in
an ordered symbol and approachable
manner to to compare the collected
information classification helps to
compare the data collected for example
the data on the attack of a particular
disease in a state the district level
classification of the data helps health
department to compare the rate of attack
of the disease among districts and to
introduce more effective remedial
measures three to bring out the
relationship between the variables the
relation between the variables included
in the data can bring out by classifying
the data for example the characteristics
types of medicine and the days required
to cure a particular disease can be
related to extract their relationship
classification of data is needed for to
convene tabulation only classified data
can be tabled hence data classification
is essential for tabulation etc
properties of an ideal classification
1xo stiffness all the classes should be
clearly defined and each and every
observation must belong to one of the
classes two mutually exclusive Ness no
observation belongs to more than one
class otherwise classes must not overlap
if so it will make some ambiguity
three stability the classification once
made should be capable for an any
statistical inquiry which is having a
possibility to arise from the data for
homogeneity the classes created should
contain homogeneous items otherwise
subclasses also to be made for example
classification basis on employed and
unemployed groups may need F for the
classification according to education
level for further homogeneity six
flexibility no classification will
remain for over classification should be
flexible to accommodate the new and
changed situations and conditions types
of classification depending upon the
nature and purpose of the data collected
it can classify in various types
following are the common forms of data
classification one geographical
classification - chronological
classification three qualitative
classification and for quantitative
classification one geographical
classification this is based on the
geographical areas from where the data
is collected for example a data on the
sale of a particular commodity need to
be classified according to the areas of
sale for identifying the sale volume of
various geographical areas here the
classification of the sale data may be
classified according to state district
or village etc - chronological
classification here data are classified
according to the time of its occurrence
data regarding import and export of a
company or the data regarding the attack
of a particular disease may be
classified according to year to identify
the rate of the corresponding events
from year to year three qualitative
classification when the data are
classified according to characteristics
which are not possible to numerically
miserable like Beauty intelligence etc
the
if equation is called the qualitative
classification for quantitative
classification if the data are
classified according to some
quantitative measurements like height
weight marks obtained in an examination
etc the classification is quantitative
classification the quantitative
phenomenon under consideration is called
variable the variable may be discrete or
continuous
if the possible values of a variable are
finite or countable the variable is said
to be discrete otherwise if the variable
can assume any real number within
certain limits as its value the variable
is a continuous variable for example
variables denoting number of children in
a family number of attacks of asthma per
week are discrete and the variable such
as height which take any value within a
given range are continuous frequency
distribution frequency distribution is
the orderly arrangement of the data
classified according to the values of
the variable two kinds of frequency
distribution are one ungrouped frequency
distribution and two grouped frequency
distribution ungroup the frequency table
is a representation of the collected
data in the form of two columns where
one column contains values of the
variable and the next column contains
the number of times each value repeaters
which is called frequency of that value
in the set of collected data to create
an ungrouped frequency table using the
given data first we list the collected
values in ascending order of magnitude
and then reading the data one by one and
put tally marks against the listed
values in final count the tally mark of
each value which is recorded as the
frequency of that value for example
consider the following data on the
number of children in 20 families of at
town 0 1 2 1 0 3 1 2 3 3 2 2 1 1 0 3 2 1
2
and three an ungroup the frequency table
representation of the data is as follows
number of children zero one two and
three and then tally marks are entered
counting the Terra max frequency of each
values for zero it is three for one it
is six for two it is six and for three
it is five in common the values of a
discrete variable are represented in an
ungroup the frequency table and that of
continuous variable are presented in
group the frequency table the method is
as follows
consider the continuous variable height
of 100 students the data can be
classified into different classes or
groups of heights say 100 to 110
centimeters 110 to 120 centimeters etc
then the number of students with height
belonging to each of the classes are
counted and knotted against each class
which are called frequency of that class
various steps involved in constructing
frequency distribution table are as
follows one finding the least and
highest value of the variable identify
the largest and smallest observation in
the given data set and their difference
is called the range is to be found to
determine the number of classes normally
a frequency distribution not containing
more than 20 classes and not in less
than 6 classes even though there is no
hard and fast rule regarding the number
of classes EMA stages suggested a
formula to find the number of classes
for the data according to his suggestion
number of classes equal to 1 plus 3.2 to
log n to the base 10 where n is the
total frequency 3 deciding the class
interval magnitude or sizes of the class
interval are commonly kept uniform and
it is founded by dividing the range of
the data with the suggested number of
classes and round off
four counting values belonging to each
of the classes reading the data one by
one and put tally mark in the class
where the rent observation is coming in
final count the tally mark of each class
which is the frequency of that class the
two methods for forming class intervals
are one exclusive methods and two
inclusive method in exclusive method
class intervals are fixed in such a way
that the upper limit of a class is same
to the lower limit of the next class for
example
the classes are of the form 0 to 10 10
to 20 20 to 30 etc are coming under
exclusive classes in such a
classification the observation 20 is
included in the class 20 to 30 and this
observation is excluded from the class
10 to 20 in inclusive method of classes
the lower limits of a class is the next
value of the upper limit of the
preceding class following are the
classes coming under inclusive method 0
to 9 10 to 19 20 to 29 etc in some
situations classification is done with
first class not lost at the beginning
and the last class not lost at the end
for example the classes in such
classification may be as below 10 10 to
20 20 to 30 etc 50 and above this type
of classification is the classification
with the open-ended classes frequency
density of air class is the class
frequency per unit magnitude of the
class it is obtained as class frequency
divided by class width the relative
frequency of a class is the ratio of
class frequency to the total frequency
and the person rates frequency is the
expression of class frequency as a
percentage of the total frequency which
is expressed as class frequency divided
by total frequency in 200
cumulative frequency distribution
cumulative frequency distribution gives
successively added or subtracted
frequencies up to each of the classes in
a less than cumulative frequency
distribution the total frequency of all
classes less than and equal to the each
of the class is listed in a greater than
cumulative frequency distribution the
total frequency of all classes greater
than and equal to the each of the
classes is listed as an illustration
consider the following frequency
distribution class 0 to 10 10 to 20 20
to 30 30 to 40 40 to 50 and 50 to 60
corresponding frequencies 5 8 13 10 9
and 5 in a less than cumulative
frequency distribution the cumulative
frequencies are as given as follows
classes 0 to 10 10 to 20 20 to 30 30 to
40 40 to 50 and 50 to 60 corresponding
less than frequencies 5 13 26 36 45 and
50 and in a greater than cumulative
frequency distribution the cumulative
frequencies are as given as follows
classes 0 to 10 10 to 20 20 to 30 30 to
40 40 to 50 and 50 to 60 the
corresponding greater than frequencies
50 45
37:24 14 and 5 tabulation tabulation may
be defined as the logical and systematic
organization of statistical data in rows
and columns it facilitates the analysis
of the data tabulation is an
intermediate process between collection
and statistical analysis of the data
main objectives of the tabulation
includes one to clarify the object of
Investigation two to simplify combats
data three to depict trench for this
save space and file to facilitate
comparison of the data etc an ideal
table should contain as information as
possible in a specified space with no
loss of clarity main parts of a
statistical table include one table
number to enable easy reference of a
table it should be properly numbered to
title an appropriate clear and precise
title which explains where the data are
what the data are when the data occurred
and how the data are classified is to be
given for every table 3 caption captions
are column headings which indicate what
the column represents each column should
have captions for steps steps are row
headings which indicate what the row
represents each row should have steps
file bori bori is the main part of a
table contains the collected numerical
information 6 prefatory notes and
footnotes refer trainers are a given
just below the main heading this is for
explaining those which are not cleared
by main title for example prefer tree
nodes can be included to indicate the
units in which the data are expressed in
the table footnotes are added below the
body of the table to clarify or to give
explanation for any item included in the
table if necessary 7 source data source
data refers to the source from which the
data has been collected format of a
table with the suggested parts is as
follows types of tables different types
of tabular representations of data
according to the natural aim objective
and scope of the survey are one symbol
and complex table to general and special
purpose table 3 or
and derivative table one symbol and
complex table when the data represents
according to only one characteristic the
table is called a simple table for
example in a Health Survey the heights
of people participated are listed in a
symbol table as follows
height distribution of people heights in
centimeters less than 100 100 to 120 120
to 140 140 to 160 160 to 180 and more
than 180 number of people to thirteen
twenty to thirty eight seventeen and six
if the table is made considering two or
more characteristics simultaneously then
it is called a complex or many fault
table for example in a Health Survey if
we record the height age and sex of
people simultaneously in a table the
table is a complex table let us make
such a table as follows general and
special purpose table general purpose
table which also called repository table
represents the raw data in great detail
covers a variety of information on the
same subject and represent the data
without any special analytical purposes
special-purpose tables are summary
tables they are also known as analytical
tables these tables are used to indicate
the relationship which is of special
significance three original and
derivative table original tables
consists of the original data initially
collected from the original source
derivative table consists of the
descriptive measures like average
coefficients etcetera for example a
table formed out of time series data is
an original table while the table of
trend values is a derivative table while
constructing a table the following
points should be kept in mind one table
should be attractive neat compact and
self explanatory two table should not be
overloaded three use of abbreviations
should be minimized
for use of detour marks are to be
avoided five arranged data in a table so
as it makes the comparison ec6 as far as
possible around off the figures in a
table now let us summarize the session
this module introduces the idea of
classification and tabulation of
collected data at first objectives
properties and various types of
classification are considered concept of
frequency distribution and construction
of frequency distribution are discussed
the idea of tabulation along with
objectives components and various types
of tabulation techniques are also
narrated before we move to the next
session please try to answer the
following questions
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Kusum are the following data shows the
duration of slept in house of 25
patients following administration of a
certain and aesthetic represent the data
in a frequency distribution 2 3 4 3 4 5
6 1 2 1 1 3 5 7 5 4 3 4 4 3 2 3 2 4 3 3
2 1 2 3
question 2 for the following data given
in a group the frequency distribution
construct one relative frequency
distribution to cumulative frequency
distribution classes 0 to 10 10 to 20 20
to 30 30 to 40 40 to 50 and 50 to 60
corresponding frequencies 5 8 13 24 12
and 8 question 3 collect the age serum
cholesterol and blood pressure of
patients admitted in cardiology
department of a hospital and tabulate
the data considering the sex of the
patients also the books for your
reference are 1 Marcelo Pagano and
Kimberly Goryeo principles of
biostatistics sin age learning to mehdi
j statistical methods and introductory
text new age international Private
Limited 3 but B are three venkatramana T
and mother ah who cares statistics a
beginners test new age international
private limited for gupta SC and VK
Kapoor fundamentals of mathematical
statistics Sultan jump and sons while
Danielle w/w biostatistics
John Wiley sons hope you enjoyed the
session see you next time until then
good bye
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