What is Correlation?

Correlation is a statistical measure that describes the strength and direction of the relationship between two variables. It ranges from -1 to 1.

• Positive Correlation: Both variables move in the same direction. As one increases, the other increases.

• Negative Correlation: One variable increases while the other decreases.

• No Correlation: No relationship between the variables.

Interpreting Correlation Coefficients

• +1: Perfect positive correlation

• -1: Perfect negative correlation

• 0: No correlation

What is Regression?

Regression analysis is a statistical method used to examine the relationship between a dependent variable and one or more independent variables. It helps in predicting the value of the dependent variable based on the independent variable(s).

Types of Regression

• Simple Linear Regression: Examines the relationship between two variables, one dependent and one independent. The relationship is modeled using a straight line (y = mx + b).

• Multiple Linear Regression: Examines the relationship between one dependent variable and multiple independent variables. It helps in understanding how each independent variable impacts the dependent variable.

Example

A researcher studies the relationship between hours studied (independent variable) and exam scores (dependent variable). A positive correlation indicates that more hours studied are associated with higher exam scores. Using regression analysis, the researcher can predict the exam score based on the number of hours studied.

Activity

Find a dataset with two variables (e.g., height and weight). Calculate the correlation coefficient and create a scatter plot to visualize the relationship. Perform a simple linear regression analysis to predict one variable based on the other.

Quiz