Spss 15.0 version software

The relationship between the length (L) and weight (W) of the fish samples were expressed by the equation (Le Cren, 1951 ): Where;
W = Weight of fish in gram (g); L = Total Length (TL) of fish in centimeter (cm);
a = Constant (intercept).
b = Slope (i.e. change in weight per unit change in Length).
The parameters ‘a’ and ‘b’ were obtained from a least square linear regression (Zar, 1984 ) of the length and weight of Eq. (1), to obtain:
The Fulton's condition factors (K) of fish as expressed by Bagenal and Tesch (1978) were used to estimate the well-being of the fishes, that is, compare the health or fattening of the fishes. They were estimated using the relationship: $\text{K}=\frac{100\text{W}}{{\text{L}}^3}$ Where.
K = condition factor.
W = weight of fish (g).
L = length of fish (cm).
Apart from the meristic measurements, the data collected were analysed using mean, standard error of mean, frequency distribution and analysis of variance (ANOVA) at 5% level of significance. SPSS (15.0 version) software was used to analyze the condition factors while the LWRs were analyzed using FISAT II.
Ethical approval and consent to participate is not applicable to this work, as dead fish were collected from the local firshermen.

The database was collected on a Microsoft Excel (Microsoft Corporation, Redmond, WA) spreadsheet and evaluated using SPSS software 15.0 version (SPSS, Inc., Chicago, IL). The results were presented in percentages and mean (±SD). The categorical/dichotomous variables were compared using Chi-square/Fisher exact test and continuous variables were compared using unpaired t-test. The odds ratio (OR) with its 95% confidence interval (CI) was calculated to find out the risk factors for IFIS. The univariate and multivariate analyses were carried out using binary logistic regression analysis. The multivariate analysis was performed using factors from the univariate analysis that achieved significance at the 0.05 level. A P < 0.05 was considered significant.