Statistics is essential in biological and ecological scientific research. However, the
default Frequentist statistics based on p-value and null hypothesis testing is often
misused and misinterpreted, hence causing reproducible crises. The p-value concept
deserved further examination because it has been irretrievably lost. Therefore, there
is dire need for reform in the default Frequentist statistics as practiced by researchers
because of the perils of p-values. Bayesian statistics, using the tools of Bayes Factors
and posterior distributions derived from priors and likelihood function; rooted in
Bayes’ Theorem is one of the suggested alternatives. Frequentist (least square) and
Bayesian (specifying uniform Jeffreys-Zellner-Siow prior, r-scale =0.35) regression
models, a standard statistical protocol in fisheries were applied to determine the
allometric growth coefficient based on length (mm) and weight (g) measurements of
juvenile African mud catfish, Clarias gariepinus from Epe Lagoon. The growth
coefficient, b=3.20, 95% Confidence Interval [3.07, 3.34], t(96)=47.55, p<0.001 was
significant with 96% explanatory power (R2=0.96).While Bayesian method, with
96% explanatory power (R₂=0.96), also estimated, b=3.20, (with Credible Interval
between 3.06 and 3.32). The Bayes Factor (>100) suggested the data is more
plausible under the alternative model than the null model, but p-value cannot
quantify evidence in support of alternative hypothesis, since p-value can only reject
or fail to reject a null hypothesis. These findings suggested that juvenile C.
gariepinus thrived in Epe Lagoon. Therefore, Bayesian inference is a robust
substitute for Frequentist regression model in fisheries.