Question

One of the major misconceptions about correlation is that a relationship between two variables means causation; that is, one variable causes changes in the other variable. There is a particular tendency to make this causal error, when the two variables seem to be related to each other.

What is one instance where you have seen correlation misinterpreted as causation? Please describe.

an orginal post please

Answer #1

EXAMPLE WHERE WE HAVE SEEN CORRELATION MISINTERPRESTED AS CAUSATION:

Scenerio:

Children who watch a lot of TV are the most violent. The conclusion is: TV makes children more violent.

Here, there is a strong correlation observed between :

Watching a lot of TV

and

becoming violent.

So, we conclude:

Watching alot of TV is the cause

and

Children becoming violent is the effect.

FALLACY IN THE ABOVE CAUSE & EFFECT ARGUMENT:

If the above scenerio is carefully analysed, we will find out the actual interpretation as follows:

The children, who are by nature of violent character like watching more TV, as compared to those children who are by nature very mild.

Thus wesee correlation cannot mean causation in all cases.

One of the major misconceptions about correlation is that a
relationship between two variables means causation; that is, one
variable causes changes in the other variable. There is a
particular tendency to make this causal error, when the two
variables seem to be related to each other.
What is one instance where you have seen correlation
misinterpreted as causation? Please describe
Can you help me understand how to answer this question

A Correlation Coefficient is a measurement of
the relationship between two variables. A positive correlation
means that as one variable increases, the second variable increases
too. A negative correlation means that as one variable increases,
the second variable decreases, or as one variable decreases, the
second variable increases. Positive and negative correlations
exists in nature, science, business, as well as a variety of other
fields. Please watch the following video for a graphical
explanation of the correlation coefficient:
For Discussion...

A) Two variables have a high covariance. This means the two
variables have a strong relationship. T/F
B) For a variable x, the sample mean is 8 and the sample
standard deviation is 2. One of the observations is 15. Is this
observation an outlier?
Group of answer choices
Yes, the z-score is greater than 3
No, the z-score is between -3 and 3
Yes, the z-score is between -3 and 3
No, the z-score is less than -3
C)...

One can infer causation from statistical correlation: if
variables are highly correlated then one of the variables must be
causally related to the other. True or False.

Suppose the correlation coefficient between two variables is
found to be 0.83. Which of the following statements are true?
small values of one variable are associated with large values of
the other variable
the relationship between the variables is weak
a scatter plot of the points would show an upward trend
low values of one variable tend to be paired with low values of
the other variable
there is a strong positive curvilinear relationship between the
variables
there is a...

Does correlation mean the same thing as causation? In other
words, if there exists a strong correlation between two variables,
does that necessarily mean that one variable causes the other?
Support your answer with examples.

One hears versions of the expression "correlation does not mean
causation" so often - especially as a graduate student - that it
can be easy to accept the statement as true without giving the
matter some careful consideration.
Is it ALWAYS true that correlation does not imply (or suggest)
causation? Does correlation NEVER imply (or suggest) causation? Are
there any conditions under which we might have good reason to think
that a causal relationship does exist on the basis of...

How might squaring a correlation coefficient be useful to
understanding the relationship between two variables?
Why is it important to remember “association, not causation”
when discussing correlations? Please provide an example.

Correlation =/= Causation
A lot of data is correlated. In some cases, this is because one
variable causes another. In other cases, things are correlated and
neither thing cause the other. I would like for you to think of one
such example. 2 variables must be (believably) correlated, but one
clearly doesn't cause the other. Thus, your response should have 4
parts to it...
~Thing 1
~Thing 2
~Ridiculous claim- thing 1 causes thing 2 or thing 2 causes
thing...

correlation measures the degree to which two variables are
related to one another.
Here are the definitions of the three possibilities:
Positive correlations: In this type of
correlation, both variables increase or decrease at the same time.
A correlation coefficient close to +1.00 indicates a strong
positive correlation.
Negative correlations: This type of
correlation indicates that as the amount of one variable increases,
the other decreases (and vice versa). A correlation coefficient
close to -1.00 indicates a strong negative correlation....

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