Correlation vs causation all you need to know about

1
(No Transcript)
2
(No Transcript)
3
A correlation is a statistical measure that we
use to describe the linear relationship between
two continuous variables. For example, height and
weight. Generally, the correlation is used when
there is no identified response variable. It
estimates the strength or direction between two
or more variables that have a linear
relationship.         The Pearson correlation
measures the linear relationship between two
variables. We can estimate the the population
correlation by using it.
CORRELATION
4
TYPES OF CORRELATION
5
If the capacity of one variable to influence
others, then it comes under causation or
causality. The first variable is the reason to
bring the second one into existence. The second
variable can fluctuate because of the first
variable.Causation is also known as
causality.From the above explanation, you can get
clarity on both. Now we understand the difference
between Correlation vs Causation.Correlation vs
Causation help in telling something is a
coincidence or causalityThe main difference is
that if two variables are correlated. That does
not mean that one causes the reason for happening.
CAUSATION
6
The basic example to demonstrate the difference
between correlation and causation is ice cream
and car thefts.  Ice cream sales or stolen cars
have a highly positive correlation. When the sale
of ice cream rises, then the number of cars
stolen also rises.  It is not the valid reason
that ice cream eating behind the reason to steal
cars. This is not a casual relationship between
cars stolen and ice cream. Behind it, there is a
third reason that explains the correlation
between sales of ice cream and car thefts. The
third reason is the weather.  In the summer, both
are increasing that is ice cream sales get an
increase. Or cars get stolen in the more
numbers. Therefore, ice cream and car thefts do
not have a casual relationship. But they are
correlated.One of the examples of a causal
relationship is the link between smoking and
cancer. There are higher chances of correlation
between people who smoke and people who contract
disease.Further explanation is that the data has
shown the conclusion that there is a causal
relationship between smoking and contracting
diseases (cancer).    To conclude, correlation
does not imply causation.
EXAMPLE
7
FINAL WORDS
From the above discussion, you can get the
knowledge of both correlation and causation.
Theoretically, it is easy to identify the
distinction between both. Dont conclude too
quickly. After studying the correlation, take
time to understand the causation. Find the hidden
factor behind both and then conclude. The above
explanation explains the difference between both.
If you are facing difficulty in understanding the
difference or looking for the best math
assignment help. Then we are here to provide you
the best help with math assignment.
8
Follow us on Social Media
9
(No Transcript)