What is Correlation | Data Science Interview Questions and Answers | Thinking Neuron

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Correlations are mathematical relationships between two continuous variables.
You can identify correlations on a scatter diagram by the distinct patterns they form. The correlation is said to be linear if the scatter diagram shows the points lying in an approximately straight line.
Let’s take a look at a few common types of correlation between two variables:
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Positive linear correlation (r=0 to 1)
Positive linear correlation is when low values on the x-axis
correspond to low values on the y-axis, and higher values of x
correspond to higher values of y. In other words, y tends to
increase as x increases.
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Negative linear correlation(r= -1 to 0)
Negative linear correlation is when low values on the x-axis
correspond to high values on the y-axis, and higher values of x
correspond to lower values of y. In other words, y tends to
decrease as x increases.
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No correlation(r=0)
If the values of x and y form a random pattern, then we say there is no correlation.

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