CORRELATION AND REGRESSION

CORRELATION AND REGRESSION

CORRELATION

🔹 DEFINITION
Correlation is a statistical method used to measure the strength and direction of the relationship between two variables.

🔹 TYPES OF CORRELATION

• Positive Correlation: As one variable increases, the other also increases.

• Negative Correlation: As one variable increases, the other decreases.

• Zero Correlation: No relationship between the variables.

🔹 CORRELATION COEFFICIENT (r)

• Ranges from -1 to +1

  • +1 = perfect positive correlation

  • -1 = perfect negative correlation

  • 0 = no correlation

🔹 TYPES OF TESTS USED

• Pearson’s Correlation – for normally distributed, continuous data

• Spearman’s Rank Correlation – for ordinal or non-normal data

🔹 LIMITATIONS

• Correlation does not imply causation

• Only shows association, not influence or cause

REGRESSION

🔹 DEFINITION
Regression is a statistical method used to predict the value of one variable based on the value of another variable.

🔹 PURPOSE

• To determine the cause-and-effect relationship

• Helps in forecasting and prediction

🔹 TYPES OF REGRESSION

• Simple Linear Regression: One independent and one dependent variable

• Multiple Regression: More than one independent variable

🔹 EQUATION OF SIMPLE LINEAR REGRESSION

$$Y = a + bX$$

Where:

• Y = Dependent variable (to be predicted)

• X = Independent variable

• a = Intercept

• b = Slope (regression coefficient)

🔹 USES

• Medical prediction (e.g., predicting blood pressure based on age)

• Disease outcome prediction

• Dose-response analysis

DIFFERENCE BETWEEN CORRELATION AND REGRESSION