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Begin by calculating the Pearson’s correlation coefficient for each pair of variables. This can be done using a statistical software package or by hand.

Create a matrix of correlation coefficients by pairing each variable with all other variables in the dataset.

Visualize the data by graphing the correlation coefficients in a heatmap. This will help you to identify any strong correlations between the variables.

Interpret the correlations and identify any possible relationships between the variables. You can also use this matrix to identify any multicollinearity issues, which can be a problem when building predictive models.