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Mathematics — 2025, Undergraduate
This study modelled random phenomena using probability distributions and assessed goodness of fit. Observations from selected random processes were summarised and fitted to discrete and continuous distributions, and fitted models were compared. The findings revealed that distributional models captured central tendencies and variability effectively, while model adequacy varied with the underlying process. The study observed that choice of distribution improved inference. It recommends distribution fitting as a standard step in stochastic analysis.
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