What is Correlation?
In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables or bivariate data. In the broadest sense correlation is any statistical association, though it commonly refers to the degree to which a pair of variables are linearly related. Familiar examples of dependent phenomena include the correlation between the height of parents and their offspring, and the correlation between the price of a good and the quantity the consumers are willing to purchase, as it is depicted in the so-called demand curve.
Correlations are useful because they can indicate a predictive relationship that can be exploited in practice. For example, an electrical utility may produce less power on a mild day based on the correlation between electricity demand and weather. In this example, there is a causal relationship, because extreme weather causes people to use more electricity for heating or cooling. However, in general, the presence of a correlation is not sufficient to infer the presence of a causal relationship (i.e., correlation does not imply causation).
Let learn by example or by doing some small project
We have taken three variables age, service, and target
now go to data then data analysis
fill value I'm not going so deep into it but if you are a beginner and need to learn how? follow this link
https://www.statology.org/correlation-matrix-excel/
we get this table
Now, what does this table mean?
Correlation coefficients are used to measure the strength of the linear relationship between two variables. learn more
- A correlation coefficient greater than zero indicates a positive relationship while a value less than zero signifies a negative relationship.
- A value of zero indicates no relationship between the two variables being compared.
- A negative correlation, or inverse correlation, is a key concept in the creation of diversified portfolios that can better withstand portfolio volatility.
- Calculating the correlation coefficient is time-consuming, so data are often plugged into a calculator, computer, or statistics program to find the coefficient
If you want easier
- -1 indicates a perfect negative linear correlation between two variables
- 0 indicates no linear correlation between two variables
- 1 indicates a perfect positive linear correlation between two variables
Let do it in easy way
Now related table try to use the example you like
like number hour study and manga we read or sleep we have
If you are from marketing, number of customer visite vs number of purchase
will dive deep soon with time
if you want to connect
