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A correlation is the relationship between two variables.

Correlations are described as either weak or strong, and positive or negative, however there can be a perfect correlation between variables, or no correlation between variables.

It is important to determine the correlation between variables in order to know if and how strongly one variable affects another variable (if one variable changes, how will the other variable react). This is done by determining the coefficient of correlation (r), which describes the strength of the relationship between variables and the direction.

-1 is less than or equal to r, r is less than or equal to +1

- if r= +1 or -1, there is a perfect relationship
- if r= 0 there is no relationship between the variables, meaning that one variable does not affect the other variable and one variable could change without any change to the other variable.

- a value closer to + or - 1 demonstrates a strong relationship, while a value closer to 0 demonstrates a weak relationship.
- a + value demonstrates that when one variable increases the other variable increases, while a - value demonstrates that when one variable increases the other variable decreases.

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It is very important to understand that correlation is not the same as relationship. Consider the two variables, x and y such that y = x2 where x lies between -a and +a. There is a clear and well-defined relationship between x and y, but the correlation coefficient r is 0. This is true of any pair of variables whose graph is symmetric about one axis.

Conversely, a high correlation coefficient does not mean a strong relationship - at least, not a strong causal relationship. There is pretty strong correlation between my age and [the log of] the number of television sets in the world. That is not because TV makes me grow old nor that my ageing produces TVs. The reason is that both variables are related to the passage of time.

Q: What is correlation. What are the different types of correlation. Why is it important to determine correlation. What does it mean when it is said that two variables have no correlation?

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It mean that there is no correlation between the two variables. The variables are the same.

"If coefficient of correlation, "r" between two variables is zero, does it mean that there is no relationship between the variables? Justify your answer".

a zero correlation means that there is no relationship between the two or more variables.

If variables have zero correlation, they do not have a linear relationship. Zero correlation shows that two things were not found to be related.

If measurements are taken for two (or more) variable for a sample , then the correlation between the variables are the sample correlation. If the sample is representative then the sample correlation will be a good estimate of the true population correlation.

Related questions

that there is a correlation between the two variables. However, correlation does not imply causation, so it is important to further investigate to determine the nature of the relationship between the variables.

The three different types of correlation are positive correlation (both variables move in the same direction), negative correlation (variables move in opposite directions), and no correlation (variables show no relationship).

A correlation is the relationship between two or more variables. Correlations are described as either weak or strong, and positive or negative. There can be a perfect correlation between variables, or no correlation between variables. It is important to determine the correlation between variables in order to know if and how closely changes in one variable are reflected by changes in another variable. This is done by determining the coefficient of correlation (r), which describes the strength of the relationship between variables and the direction. -1 â‰¤ r â‰¤ +1 if r= +1 or -1, there is a perfect correlation if r= 0 there is no correlation between the variables. a value closer to + or - 1 demonstrates a strong correlation, while a value closer to 0 demonstrates a weak correlation. a + value demonstrates that when one variable increases the other variable increases, while a - value demonstrates that when one variable increases the other variable decreases. However, it is very important to understand that correlation is not the same as relationship. Consider the two variables, x and y such that y = x2 where x lies between -a and +a. There is a clear and well-defined relationship between x and y, but the correlation coefficient r is 0. This is true of any pair of variables whose graph is symmetric about one axis. Conversely, a high correlation coefficient does not mean a strong relationship - at least, not a strong causal relationship. There is pretty strong correlation between my age and [the log of] the number of television sets in the world. That is not because TV makes me grow old nor that my ageing produces TVs. The reason is that both variables are related to the passage of time.

Correlation is a statistical measure of the linear association between two variables. It is important to remember that correlation does not mean causation and also that the absence of correlation does not mean the two variables are unrelated.

You calculate a correlation coefficient and test to see if it is statistically different from 0.

A correlation research method is used to examine the relationship between two variables to see if they are related and how they may change together. It helps to determine if there is a pattern or connection between the variables, but it does not imply causation.

It mean that there is no correlation between the two variables. The variables are the same.

partial correlation is the relation between two variable after controlling for other variables and multiple correlation is correlation between dependent and group of independent variables.

A positive correlation between two variables means that there is a direct correlation between the variables. As one variable increases, the other variable will also increase.

We consider correlation as a several independent variables.

correlation

No. The units of the two variables in a correlation will not change the value of the correlation coefficient.