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<speak> We use the corr method to find the correlation between two variables. <break strength="strong"/>For correlation,<break strength="weak"/> you require two variables. <break strength="strong"/>Here one is GRE Score, <break strength="weak"/>and another one is the chance of admit. Using corr method, <break strength="weak"/>you will find the correlation between the chance of admit and the GRE Score.<break strength="strong"/> The correlation value is 0.8,<break strength="weak"/> and it is positive. <break strength="strong"/>That means GRE score and the chance of admit are positively correlated.<break strength="strong"/> Similarly,<break strength="weak"/> we can see the correlation between TOEFL score and the chance of admit. <break strength="x-strong"/> It is also positively correlated<break strength="weak"/> and is having a correlation coefficient of 0.78.<break strength="strong"/> TOEFEL Score and the chance of admit are strongly correlated.<break strength="strong"/> That means when you are building a model,<break strength="weak"/> you should consider these variables. <break strength="strong"/>That means you should consider the GRE score and Toefl score. <break strength="strong"/>You must include these variables in building the model. <break strength="x-strong"/> For building a model to predict the chance of admit, <break strength="weak"/>you must include these variables. <break strength="strong"/>CGPA correlated with chance of admit.<break strength="strong"/> Hence we need to consider CGPA also.<break strength="strong"/> Sometimes the independent variables or input variables are correlated.<break strength="strong"/> For example, we are drawing the scatter plot of CGPA and the TOEFL score.<break strength="strong"/> CGPA and TOEFL scores are strongly related.<break strength="strong"/> There is a value of 0.8 correlation between these two. <break strength="strong"/>Similarly, CGPA and GRE Score are also correlated,<break strength="weak"/> and their correlation value is 0.8. <break strength="x-strong"/> With more CGPA, the student will get good scores in GRE and TOEFL.<break strength="strong"/> So you can draw this kind of insights from the exploratory data analysis. <break strength="strong"/>You did the univariate analysis with a single variable.<break strength="strong"/> And bivariate analysis between the two variables. <break strength="x-strong"/> EDA helps you to make wise decisions while building the model. <break strength="x-strong"/> What is the use of exploratory data analysis?<break strength="x-strong"/> EDA is useful for seeing what the data can tell us before the modeling task.<break strength="x-strong"/> </speak>