MATLAB Source Program for Determining if Random Data Follows Normal Distribution

This MATLAB program helps determine whether a set of random data follows a normal distribution, which is crucial for proper statistical analysis. The implementation typically utilizes statistical tests like the Kolmogorov-Smirnov test, Lilliefors test, or Shapiro-Wilk test to assess normality. Users can employ this program for data analysis and exploration to better understand their dataset characteristics. If your dataset follows a normal distribution, you can proceed with parametric statistical methods for more accurate analysis and predictions. Conversely, if the data violates normality assumptions, alternative distributions or non-parametric methods should be considered for valid conclusions. The program provides visualization capabilities through Q-Q plots and histograms with normal distribution overlays for intuitive assessment. Key MATLAB functions involved may include kstest, lillietest, swtest (if using custom Shapiro-Wilk implementation), and probability plotting functions. This tool enables quick and easy normality evaluation, facilitating informed decisions about subsequent analytical approaches.