statistics Linear Correlation and Linear Regression Analysis

• The primary purpose of linear correlation analysis is to measure the strength of a linear relationship between two variables.
• A sketch of data on two variables is called a scatter plot
• the correlation is positive when as X increases also Y

  tends to increase
• the correlation is negative when as X increases Y tends

  to decrease
• if the values of X and Y tend to follow a straight line path,

  there is a linear correlation
• Pearson coefficient shows the sign and the strength of linear correlation

  between variables X and Y
• Pearson coefficient: It takes the values between -1 and +1: