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Measures of Central Tendency
Dr. Suresh Kumar Murugesan Ph.D
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About the Presenter
● Dr.Suresh Kumar Murugesan is a Passionate Professor,Researcher
and Positive Mental Health and Wellness Practitioner from Madurai,
Tamil Nadu,India
● At present he is Heading the PG Department of Psychology,The
American College,Madurai and Adjunct Professor of School of
Behavioural Sciences and Education at Texila American University
● He is very keen in learning new research studies in behavioural
Sciences and open to learn.
● His ultimate aim is to make impression in the field of Knowledge
● His area of specializations are Psychometry,Counselling &
Psychotherapy
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Disclaimer
● This presentation is prepared
for learning purpose only and
all the images and pictures
used in this presentation are
taken from google image
search.
● Due recognition was given to all
the material collected from the
various sources.
● Any name or reference is
missed kindly bring it to the
notice of the presenter for
inclusion.
● Email -
sureshkumar800@yahoo.com
Thank you
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Measures of Central
Tendency
A measure of central tendency is a single value that
attempts to describe a set of data by identifying the central
position within that set of data.
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Measures of Central
Tendency
Measures of central tendency are
sometimes called measures of central
location
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Summary of when to use the mean, median and mode
Type of Variable Best measure of central tendency
Nominal Mode
Ordinal Median
Interval/Ratio (not skewed) Mean
Interval/Ratio (skewed) Median
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Exclusive Method
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Inclusive Method
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Open Ended Classes
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Problem
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Solution
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Problem
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Frequency Table
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Cumulative Frequency
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Mean
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Definition: Average
● “A measure of central tendency is a typical value around which other figures
congregate.”
● “An average stands for the whole group of which it forms a part yet
represents the whole.”
● “One of the most widely used set of summary figures is known as measures
of location.”
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Characteristics for a good or an ideal average
The following properties should possess for an ideal average.
1. It should be rigidly defined.
2. It should be easy to understand and compute.
3. It should be based on all items in the data.
4. Its definition shall be in the form of a mathematical formula.
5. It should be capable of further algebraic treatment.
6. It should have sampling stability.
7. It should be capable of being used in further statistical computations or
processing.
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Arithmetic Mean
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Arithmetic Mean -
Shortcut method
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Solution
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Solution
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Properties of Arithmetic
Mean
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Merits of Arithmetic Mean
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Merits of Arithmetic mean
1. It is rigidly defined.
2. It is easy to understand and easy to calculate.
3. If the number of items is sufficiently large, it is more accurate and more
reliable.
4. It is a calculated value and is not based on its position in the series.
5. It is possible to calculate even if some of the details of the data are lacking.
6. Of all averages, it is affected least by fluctuations of sampling.
7. It provides a good basis for comparison.
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Demerits of Arithmetic Mean
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Demerits of Arithmetic mean
1. It cannot be obtained by inspection nor located through a frequency graph.
2. It cannot be in the study of qualitative phenomena not capable of numerical
measurement i.e. Intelligence, beauty, honesty etc.,
3. It can ignore any single item only at the risk of losing its accuracy.
4. It is affected very much by extreme values.
5. It cannot be calculated for open-end classes.
6. It may lead to fallacious conclusions, if the details of the data from which it is
computed are not given.
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Median
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Solution
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Solution
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Solution
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Solution
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Merits of Arithmetic Median
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Merits of Median
1. Median is not influenced by extreme values because it is a positional
average.
2. Median can be calculated in case of distribution with open-end intervals.
3. Median can be located even if the data are incomplete.
4. Median can be located even for qualitative factors such as ability, honesty
etc.
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Demerits of Arithmetic Median
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Demerits of Median
1. A slight change in the series may bring drastic change in median value.
2. In case of even number of items or continuous series, median is an estimated
value
other than any value in the series.
3. It is not suitable for further mathematical treatment except its use in mean
deviation.
4. It is not taken into account all the observations.
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Mode
Mode
● The mode refers to that value in a distribution, which occur most frequently. It
is an actual value, which has the highest concentration of items in and
around it.
● According to Croxton and Cowden “ The mode of a distribution is the value at
the point around which the items tend to be most heavily concentrated. It
may be regarded at the most typical of a series of values”.
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Remarks :
1. If (2f1-f0-f2) comes out to be zero, then mode is obtained by the following
formula taking absolute differences within vertical lines.
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Mean, Median and Mode
● In a symmetrical distribution the three simple averages mean = median =
mode.
● For a moderately asymmetrical distribution, the relationship between them
are brought by Prof. Karl Pearson as
○ mode = 3 median - 2 mean.
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Mode
Example :
If the mean and median of a moderately asymmetrical series are 26.8 and 27.9
respectively, what would be its most probable mode?
Solution:
Using the empirical formula
Mode = 3 median – 2 mean
= 3 × 27.9 – 2 × 26.8
= 30.1
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Merits of Arithmetic Mode
Merits of Mode
1. It is easy to calculate and in some cases it can be located mere inspection
2. Mode is not at all affected by extreme values.
3. It can be calculated for open-end classes.
4. It is usually an actual value of an important part of the series.
5. In some circumstances it is the best representative of data.
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Demerits of Arithmetic Mode
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Demerits of mode
1. It is not based on all observations.
2. It is not capable of further mathematical treatment.
3. Mode is ill-defined generally, it is not possible to find mode in some cases.
4. As compared with mean, mode is affected to a great extent,by sampling
fluctuations.
5. It is unsuitable in cases where relative importance of items has to be
considered.
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