Global Journal of Management and Business Research, A: Administration and Management, Volume 21 Issue 12

The significance value 0.000 establishes that H1 is rejected and therefore, it can be inferred that there is significant difference between salary and performance appraisal. F value is 2.680. Null hypothesis: There is no difference between gender and opinion about performance appraisal Table 2 Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 32.276 a 21 .055 Likelihood Ratio 37.286 21 .016 Linear-by-Linear Association 2.273 1 .132 N of Valid Cases 200 The above table shows that the chi square value (Gender and performance appraisal) is 32.276 and the p value is .055 and the degree of freedom is 21. Here the p value is more than 0.05. so, accept H0 and conclude that there is no significance difference between gender and performance appraisal. Null hypothesis: There is no significance impact of performance appraisal and productivity of Advinar Technologies Pvt.ltd. Table 3: Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .965(a) .932 .932 .22787 a. Predictors: (Constant), Performance appraisal Analysis The Multiple R for the relationship between the set of independent variables and the dependent variable is 0.965, which would be characterized as very strong using the rule of thumb that a correlation less than or equal to 0.20 is characterized as very weak; greater than 0.20 and less than or equal to 0.40 is weak; greater than 0.40 and less than or equal to 0.60 is moderate; greater than 0.60 and less than or equal to 0.80 is strong; and greater than 0.80 is very strong. Table shows the output for model fitness. The R coefficient of 0.965 indicates that the predictors of the model (Performance appraisal) which has a correlation of 96.5% with the dependent variable of productivity that means there is a very strong relationship between the set of independent variables and dependent variable. The R square also called coefficient of determination of 0.932 indicates that the model can explain 93.2% of the variations in the Performance appraisal and there are other factors which can explain 6.8% of the variations in Performance appraisal. This shows that the independent variables productivity of this study are significant predictors of the Performance appraisal. Table 4: ANOVA Model Sum of Squares df Mean Square F Sig. 1 Regression 140.649 1 140.649 2708.769 .000(a) Residual 10.281 198 .052 Total 150.930 199 a. Predictors: (Constant), Performance appraisal b. Dependent Variable: Productivity Analysis Table shows that variations in the productivity can be explained by the model to the extent of 2708.769. The F value of the model produces a p-value of 0.000. A p-value of 0.000 is lower than the set level of significance of 0.05 for a normally distributed data. This means that the model is significant in explaining Performance appraisal. 44 Global Journal of Management and Business Research Volume XXI Issue XII Version I Year 2021 ( ) A © 2021 Global Journals A Study on the Performance Appraisal by Advinar Technology Pvt. Ltd. in Thiruvananthapuram District