1 – What is Correlation
2 – Types of Correlation
3 – Pearson’s Correlation
4 – Spearman Rank Correlation
1 – What is Correlation
correlation refers to a statistical relationship
between the two entities.
to which two variables are linearly
related.
for example
the increase in the height of the children
is accompanied often by the increase in weight.
the value of the correlation always
lies between minus one two plus one.
2 – Types of Correlation
There are mainly three categories of
correlation.
1 - Positive Correlation
and Negative Correlation
2 - Linear and Non-Linear
Correlation and
3 - Simple, Multiple
and Partial Correlation
1 - Positive Correlation and Negative Correlation
Positive correlation
A positive correlation means that a linear
relationship is positive and the two variables increases or decreases in the
same direction as you
for example
the calories you burn is directly proportional
to the amount of time you run on a treadmill.
Negative correlation
negative correlation is just the opposite
the relationship line has a negative slope and the variable changes in the opposite
direction that is one variable decreases while the other increases.
an example
can be a student who has many absence
has a decreasing grades.
2 - Linear and Non-Linear Correlation
Linear Correlation
when we change the value of a
variable which leads to a constant ratio change in other variable then that
relation is said to be linear.
for example
the factory doubles its output by doubling
the number of workers
Non-Linear Correlation
Correlation is said to be non-linear
when the amount of change in one variable is not in constant ratio to the
change in the other variable.
for example
the change in radius of the sphere
and the change in volume of the same sphere does not happen to be in the same
ratio.
3 - Simple, Multiple and Partial Correlation
Simple Correlation .
When studying the relationship
between the variables when only two variables are involved the correlation is
said to be simple.
Multiple Correlation .
the multiple correlation we measure the
degree of association between one variable on the one side and all the variables
together on the other side.
Partial Correlation .
The partial correlation we study the
relationship of one variable with one of the other variables presuming that all
the variables remains constant.
now that we know all the types of correlation
3 – Pearson’s Correlation (PSS
Correlation)
pss correlation coefficient is the
test statistics that measures the statistical relationship between the two
continuous variables.
the ps's correlation coefficient is
often denoted by r and the formula to calculate the psense relation coefficient
is sigma x i minus x bar into y i minus y bar divided by under root sigma x i
minus x bar whole square and y i minus y bar whole square.
but r is the coefficient of
correlation x y is the mean of x variable and y bar is the mean of y variable
and x i and yy denotes the samples of variable x and y respectively.
the psl's coefficient coefficient is
the best method to measure the association between two variables of interest
because,
it gives information about the
magnitude of the association or correlation as well as the direction of the relationship
between the two variables
4 – Spearman Rank Correlation (psn rank correlation)
This psn rank correlation is used to
discover the strength of a link between the two sets of data.
The formula to calculate this psn
rank correlation coefficient is rho is equal to 1 minus 6 sigma di whole square
divided by n bracket n square minus 1.
Where rho is this ps1 rank correlation coefficient di is the difference between the two ranks of each observations and n is the number of observations.
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