4. INTRODUCTION
Definition of Mean :
Mean in statistics refers to the average of a collection
of values. The collection of values can be two or
more. It is a measure of central tendency and output
typical value in a collection or set of data.
Mean refers to the average of values or items in a
given set. In its simplest form, it is derived by adding
the values given in a set and dividing it by the
number of values in the set.
5. Mean Formula
The basic formula to calculate the mean is calculated
based on the given data set. Each term in the data set is
considered while evaluating the mean. The general
formula for mean is given by the ratio of the sum of all the
terms and the total number of terms. Hence, we can say;
Mean = Sum of the Given Data/Total number of Data
7. Arithmetic Mean
When you add up all the values and divide by the number of
values it is called Arithmetic Mean. To calculate, just add up
all the given numbers then divide by how many numbers are
given.
Example: What is the mean of 3, 5, 9, 5, 7, 2?
Now add up all the given numbers:
3 + 5 + 9 + 5 + 7 + 2 = 31
Now divide by how many numbers are provided in the
sequence:
31/6= 5.16
Answer:-5.16.
8. Geometric Mean
The geometric mean of two numbers x and y is xy. If
you have three numbers x, y, and z, their geometric
mean is 3xyz.
9. Harmonic Mean
The harmonic mean is used to average ratios. For two
numbers x and y, the harmonic mean is 2xy(x+y).
For, three numbers x, y, and z, the harmonic mean is
3xyz(xy+xz+yz)
10. Applications of mean
It is used in integral experiments, statistics, and data analysis.
Traders and investors derive meaningful information by
calculating average returns based on proper context, forming
an important input to investment decisions.
It is used in the calculation of dispersion and skewness.
It can be applied to complete a simple time-series data if any
one of the data points is missing.
11. In conclusion, the mean is a fundamental concept in
statistics that provides valuable insights into a
dataset's central tendency.
Understanding the different types of mean, their
calculation, and interpretation is crucial for effective
data analysis.
Conclusion
