The document defines and provides examples for mode, median, and mean - three common measures of central tendency used in statistics. Mode is defined as the most frequently occurring value, median is defined as the middle value when values are ordered from lowest to highest, and mean is defined as the arithmetic average calculated by summing all values and dividing by the total number of values. Special considerations are discussed for calculating the median when the number of values is even versus odd. The document encourages the viewer to subscribe to the Quantitative Specialists YouTube channel for more statistics content and courses.
quantitative aptitude, maths
applicable to
Common Aptitude Test (CAT)
Bank Competitive Exam
UPSC Competitive Exams
SSC Competitive Exams
Defence Competitive Exams
L.I.C/ G. I.C Competitive Exams
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Career Aptitude Test (IT Companies) and etc.
quantitative aptitude, maths
applicable to
Common Aptitude Test (CAT)
Bank Competitive Exam
UPSC Competitive Exams
SSC Competitive Exams
Defence Competitive Exams
L.I.C/ G. I.C Competitive Exams
Railway Competitive Exam
University Grants Commission (UGC)
Career Aptitude Test (IT Companies) and etc.
Measures of Central Tendency
Requirements of good measures of central tendency
mean, median, mode
skewness of distribution
relation between mean, median,mode
Measures of Central Tendency
Requirements of good measures of central tendency
mean, median, mode
skewness of distribution
relation between mean, median,mode
This tutorial explain the measure of central tendency (Mean, Median and Mode in detail with suitable working examples pictures. The tutorial also teach the excel commands for calculation of Mean, Median and Mode.
Measures of Central Tendency-Mean, Median , Mode- Dr. Vikramjit SinghVikramjit Singh
This presentation discusses in details about different measures of central tendency like- mean, median, mode, Geometric Mean, Harmonic Mean and Weighted Mean.
A measure of central tendency (also referred to as measures of centre or central location) is a summary measure that attempts to describe a whole set of data with a single value that represents the middle or centre of its distribution.
Measure of central tendency provides a very convenient way of describing a set of scores with a single number that describes the PERFORMANCE of the group.
It is also defined as a single value that is used to describe the “center” of the data.
Lecture 3 Measures of Central Tendency and Dispersion.pptxshakirRahman10
Objectives:
Define measures of central tendency (mean, median, and mode)
Define measures of dispersion (variance and standard deviation).
Compute the measures of central tendency and Dispersion.
Learn the application of mean and standard deviation using Empirical rule and Tchebyshev’s theorem.
Measures of Central Tendency:
A measure of the central tendency is a value about which the observations tend to cluster.
In other words it is a value around which a data set is centered.
The three most common measures of central tendency are mean, median and mode.
A measure of the central tendency is a value about which the observations tend to cluster.
In other words it is a value around which a data set is centered.
The three most common measures of central tendency are mean, median and mode.
A measure of the central tendency is a value about which the observations tend to cluster.
In other words it is a value around which a data set is centered.
The three most common measures of central tendency are mean, median and mode.
A measure of the central tendency is a value about which the observations tend to cluster.
In other words it is a value around which a data set is centered.
The three most common measures of central tendency are mean, median and mode.
Why is it needed?
To summarize the data.
It provides with a typical value that gives the picture of the entire data set
Mean:
It is the arithmetic average of a set of numbers, It is the most common measure of central tendency.
Computed by summing all values in the data set and dividing the sum by the number of values in the data set Properties:
Applicable for interval and ratio data
Not applicable for nominal or ordinal data
Affected by each value in the data set, including extreme values.
Formula:
Mean is calculated by adding all values in the data set and dividing the sum by the number of values in the data set.
Median:
Mid-point or Middle value of the data when the measurements are arranged in ascending order.
A point that divides the data into two equal parts.
Computational Procedure:
Arrange the observations in an ascending order.
If there is an odd number of terms, the median is the middle value and If there is an even number of terms, the median is the average of the middle two terms.
Mode:
The mode is the observation that occurs most frequently in the data set.
There can be more than one mode for a data set OR there maybe no mode in a data set.
Is also applicable to the nominal data.
Comparison of Measures of Central Tendency in Positively Skewed Distributions:
Majority of the data values fall to the left of the mean and cluster at the lower end of the distribution: the tail is to the right Mean, median & mode are different When a distribution has a few extremely high scores, the mean will have a greater value than the median = positively skewed.
Majority of the data values fall to
the right of the mean and cluster at the upper end of the distribution= Negatively Skewed
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http://sandymillin.wordpress.com/iateflwebinar2024
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7. Example: 1, 2, 3, 4, 5, 6
Two middle scores: 3, 4
To find the median, take the average
of the two middle scores: (3+4)/2 =
3.5
Median = 3.5
Quantitative
Specialists
8. Odd N: When there are an odd number of
values, the median is the middle
score
(1, 2, 3, 4, 5; N=5) median = 3
Even N: When there are an even number
of values, the median is equal to the
average of the two middle scores
(1, 2, 3, 4, 5, 6; N=6) median = 3.5
Quantitative
Specialists
9. Prior to calculating the median, be
sure that the numbers are ordered
from smallest to largest (don’t
pick the middle number of a set of
numbers if they are not first
ordered)
Example: 2, 3, 1, 3, 1, 6
Reordered: 1, 1, 2, 3, 3, 6
Median = 2.5
Quantitative
Specialists
10. Mean = the arithmetic average
Mean:
Where µ = the population mean, ΣX is
the sum of the variable X (add the
values of X together), and N is the
total number of values
N
X
Quantitative
Specialists
11. Example
X = 1, 2, 3, 4, 5
N = 5
Mean = 3
3
5
15
5
54321
N
X
Quantitative
Specialists
12. YouTube Channel: Quantitative Specialists
Subscribe to our channel at:
https://www.youtube.com/statisticsinstructor
(typing “quantitative specialists” in the search box will also find
us). New videos uploaded regularly.
Comprehensive statistics courses available on
Udemy.com. Search for Quantitative Specialists (use
offer SS50 for a discount on any of our Statistics/SPSS
courses with our thanks for viewing us on slideshare)
Statistical consultation questions? Contact us at:
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