What are the Steps Involved in Conducting Multiple Linear Regression?
The process typically involves:
Data Collection: Gather data from reliable sources such as surveys, clinical trials, or epidemiological studies. Data Cleaning: Prepare the data by handling missing values, outliers, and ensuring accuracy. Model Specification: Choose the dependent variable and the relevant independent variables. Model Fitting: Use statistical software to fit the MLR model to the data. Model Validation: Check the assumptions and validate the model using techniques like cross-validation. Interpretation: Analyze the coefficients and p-values to draw meaningful conclusions.
