Research on water quality has received much attention in both developing and developed countries. This is because of the fact that, the effects of poor quality of water are detrimental to human beings, animals and the environment. This study is about a computational model for water quality analysis and assessment in Tanzania. Water quality can be understood as the measure of suitability of water based on physical, chemical and biological attributes. Water quality analysis and assessment face several challenges due to population growth, urban land use, agricultural activities, and industrialization. Besides, attempts have been made by the scholars to address the challenges. However, the tools used like titrimetric, electrometric, pH-meter, thermometer and turbidity meter are yet to come up with effective solutions. Because of these, the researcher was compelled to adopt computational model which uses Statistical Analysis System (SAS) software in order to come up with effective solutions concerning water quality analysis and assessment. In this study therefore, the secondary data were collected from Lake Victoria littoral stations under the auspices of the Ministry of Water in Tanzania with the objective to get sufficient information concerning water quality analysis and assessment. Additionally, the collected data were coded in SAS software to analyse independent and dependent variables. SAS software therefore, was employed to obtain central tendency and dispersion as benchmarks in determining quality of water. Also, the Multivariate Linear Regression Model was run to obtain coefficients of estimation, 95% confident limits and p-value. Statistical findings from central tendency and dispersion indicate that, the mean for potential of Hydrogen (pH) was 8.165; for total suspended solids was 3.065 mg/l; chloride displayed a mean of 6.494 mg/l; calcium displayed a mean of 6.421 mg/l; iron had a mean of 0.188 mg/l; magnesium displayed a mean of 3.331 mg/l and sulphate had mean of 2.326 mg/l. Looking closely at all of the above-mentioned water quality parameters, they all align with a Tanzania Bureau of Standards (TBS) and World Health Organization (WHO) as shown on table 1. Findings from the Multivariate linear regression model shows that: First, iron had a p-value of 0.0153, magnesium 0.0347 and total hardness had a p-value of 0.001. All of these were statistically significant in the analysis and assessment of water quality as shown on table 2. The study concludes that, the water quality in Lake Victoria complies with both TBS and WHO standards as explained above.
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