Wind turbines have been one of the dependable sources of renewable energy that due to its abundance, have witnessed constant innovations and quest for design and productivity optimization. The commonly used type is Horizontal Wind Turbine also known as Horizontal Axis Wind Turbine (HAWT). Understanding the imperative factors influencing the functionality of HAWT provides insight into its optimal design. This study therefore x-rays the numerical analysis of HAWT operation variables and their influence on its performance parameters. Research Likert questionnaires with identified operation variables with weighty factors that have influence on HAWT were developed and distributed to trained, knowledgeable and experienced wind turbine engineers/operators with respondents outcome. A data matrix were collated. With variables identified, iterations were computed. Ten (10) clusters (F1 to F2) were optimised, with each cluster consisting of computed influential variable(s) as input data and rated factors (output) computed as maximum value for each variable, being ranked by 13 judges in Sequential Merit Order (SMO) based on their influence on HAWT. Kendall’s Coefficient of Concordance (w) and Principal Component Analysis statistical models were employed. Respondents’ scores transposed into data matrix, fed into StatistiXL software; and eigenvalues, eigenvectors, factor loadings, descriptive statistics and case wise factor scores (correlation matrix) were computed. A value of w=0.56 (middling) obtained as the level of consistency. The level of coherence/agreement of data using chi-square model had , ( at ). Therefore, null hypothesis H0 rejected; alternative hypothesis H1 accepted, which implies strong agreement with the data at 95% confidence level.