<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n**. Correlation is significant at the 0.05 level (2-tailed).<\/p>\n\n\n\n
For significant correlation, sig. (2-tailed) will be less than 0.05. From the above table 1, the Pearson\u2019s correlation coefficient for research question 1 being .047 is less than 0.05. This shows that the test is significant. Also, the strength of the relationship is given by the numeric value of the correlation coefficient. From 0.10 to 0.29 means small or weak correlation, from 0.30 to 0.49 means medium correlation, 0.50 to 0.99 means large or strong correlation while 1 means perfect correlation. <\/p>\n\n\n\n
The sig (2-tailed) is 0.773 which is equivalent to 77.3%. We can conclude that under research question one, there is strong significant, large and positive correlation between reward and teachers job performance. <\/p>\n\n\n\n
4.1.2 Research Question Two <\/strong><\/p>\n\n\n\nHow salary advancement correlates with teachers\u2019 job performance in secondary schools in Delta central Senatorial District? <\/strong><\/p>\n\n\n\nTable 4.2: Relationship between salary advancement and teachers\u2019 job performance<\/strong><\/p>\n\n\n\nCorrelations<\/strong><\/td><\/tr>SALARY ADVANCEMENTTEACHERS\u2019 JOB PERFORMANCE<\/td><\/tr> SALARY ADVANCEMENT Pearson Correlation1 .842**<\/td><\/tr> Sig. (2-tailed)<\/td> .027 NPearson Correlation 4280.842**<\/td><\/tr> Sig. (2-tailed).027<\/td> 4280<\/td><\/tr> N 4280<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n**. Correlation is significant at the 0.05 level (2-tailed).<\/p>\n\n\n\n
For significant correlation, sig. (2-tailed) will be less than 0.05. From the above table 1, the Pearson\u2019s correlation coefficient for research question 1 being .027 is less than 0.05. This shows that the test is significant. Also, the strength of the relationship is given by the numeric value of the correlation coefficient. From 0.10 to 0.29 means small or weak correlation, from 0.30 to 0.49 means medium correlation, 0.50 to 0.99 means large or strong correlation while 1 means perfect correlation. <\/p>\n\n\n\n
The sig (2-tailed) is .842 which is equivalent to 84.2%. We can conclude that under research question two, there is strong significant, large and positive correlation between salary advancement and teachers\u2019 job performance.<\/p>\n\n\n\n
4.1.3<\/strong> <\/strong>Research Question Three <\/strong><\/p>\n\n\n\nHow does award of teachers relates to their job performance in secondary schools in Delta central Senatorial District?<\/strong><\/p>\n\n\n\nTable 4.3: Relationship between awards and teachers\u2019 job performance<\/strong><\/p>\n\n\n\nCorrelations<\/strong><\/td><\/tr>AWARDSTEACHERS\u2019JOB PERFORMANCE<\/td><\/tr> AWARDS Pearson Correlation 1 .855**<\/td><\/tr> Sig. (2-tailed) .037<\/td><\/tr> N 4280 4280 <\/td><\/tr> <\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n**. Correlation is significant at the 0.05 level (2-tailed).<\/p>\n\n\n\n
For significant correlation, sig. (2-tailed) is than 0.05. From the above table 1, the Pearson\u2019s correlation coefficient for research question 1 being .037 is less than 0.05. This shows that the test is significant. Also, the strength of the relationship is given by the numeric value of the correlation coefficient. From 0.10 to 0.29 means small or weak correlation, from 0.30 to 0.49 means medium correlation, 0.50 to 0.99 means large or strong correlation while 1 means perfect correlation. <\/p>\n\n\n\n
The sig (2-tailed) is .855 which is equivalent to 85.5%. We can conclude that under research question three, there is strong significant, large and positive correlation between awards and teachers\u2019 job performance<\/p>\n\n\n\n
4.2<\/strong> <\/strong>Hypotheses Testing<\/strong><\/p>\n\n\n\nThe Hypotheses Testing for this study will be shown thus:<\/p>\n\n\n\n
H<\/strong>o<\/sub><\/strong> 1<\/strong>: There is no significant relationship between rewards and teachers\u2019 job performance in secondary schools in Delta central Senatorial District<\/p>\n\n\n\nTable 4.7: Linear Regression Result showing the relationship between rewards and teachers job performance in secondary schools <\/strong>in Delta central Senatorial District<\/strong>(n=4280)<\/strong><\/p>\n\n\n\nModel Summary<\/strong>b<\/sup><\/strong><\/td><\/tr>Model<\/td> R<\/td> R Square<\/td> Adjusted R Square<\/td> Std. Error of the Estimate<\/td> Durbin-Watson<\/td><\/tr> 1<\/td> .817a<\/sup><\/td>.803<\/td> .802<\/td> 2.1122<\/td> 1.931<\/td><\/tr> a. Predictors: (Constant), REWARDS<\/td><\/tr> b. Dependent Variable: TEACHERS JOB PERFORMANCE<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\nANOVA<\/strong>a<\/sup><\/strong><\/td><\/tr>Model<\/td> Sum of Squares<\/td> Df<\/td> Mean Square<\/td> F<\/td> Sig.<\/td><\/tr> 1<\/td> Regression<\/td> 15.329<\/td> 1<\/td> 15.329<\/td> 3.436<\/td> .046b<\/sup><\/td><\/tr>Residual<\/td> 499.662<\/td> 4279<\/td> 4.461<\/td> <\/td> <\/td><\/tr> Total<\/td> 514.991<\/td> 4280<\/td> <\/td> <\/td> <\/td><\/tr> a. Dependent Variable: TEACHERS JOB PERFORMANCE<\/td><\/tr> b. Predictors: (Constant), REWARDS<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\nCoefficients<\/strong>a<\/sup><\/strong><\/td><\/tr>Model<\/strong><\/td>Unstandardized Coefficients<\/strong><\/td>Standardized Coefficients<\/strong><\/td>T<\/strong><\/td>Sig.<\/strong><\/td>Collinearity Statistics<\/strong><\/td><\/tr>B<\/strong><\/td>Std. Error<\/strong><\/td>Beta<\/strong><\/td>Tolerance<\/strong><\/td>VIF<\/strong><\/td><\/tr>1<\/td> (Constant)<\/td> 20.3821<\/td> 2.3246<\/td> <\/td> 8.7681<\/td> 0.05<\/td> <\/td> <\/td><\/tr> REWARDS<\/td> 3.1869<\/td> 0.1008<\/td> 0.1725<\/td> 1.8537<\/td> 0.046<\/td> 1.000<\/td> 1.000<\/td><\/tr> a. Dependent Variable: TEACHERS JOB PERFORMANCE<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\nSource: Field Work, 2025<\/strong><\/p>\n\n\n\nBased on an analysis of the results in table 4.7, the R-squared value is .803. This indicates that approximately, 80.3% academic performance is explained by rewards. The Adjusted R-squared value is .802. This is slightly lower than the R-squared which is due to adjustments for the number of predators in the model. Remember that the value of Durbin Watson statistics lies between 0-4. From 0-1.49 shows presence of positive first order autocorrelation. From 1.5 to 2.5 shows absence of first order autocorrelation. The Durbin Watson statistic is 1.931. This is asymptotically 2 which show absence of first order autocorrelation. <\/p>\n\n\n\n
The F-Statistic is 3.436 with a p-value of 0.046 which is less than 0.05. This indicates that the overall regression model is highly statistically significant. The standard error of the estimate is 2.1122 representing the average deviation of the observed values from the regression line. The beta coefficient for rewards is 0.1725. This suggests a strong positive relationship between the rewards and teachers\u2019 job performance in secondary schools in Delta central Senatorial District. The t-value for the reward is 1.8537, with a very low p-value of 0.046. This indicates that the coefficient for reward is highly statistically significant. <\/p>\n\n\n\n
The tolerance and VIF values are both 1.00, indicating no issues with multi-collinearity in the model. The coefficient for teachers\u2019 quality is 3.1869. This suggests that for every unit increase in the reward, the teachers\u2019 job performance increases by approximately 3.1869 units. The regression analysis indicates that reward has a strong positive relationship with teacher job performance. However, the positive coefficient suggests that higher scores on rewards may paradoxically be associated with higher teachers\u2019 job performance<\/p>\n\n\n\n
H<\/strong>o 2:<\/strong> There is no significant relationship between salary advancement and teachers\u2019 job performance in secondary schools in Delta central Senatorial District<\/p>\n\n\n\nTable 4.8: Linear Regression Result showing the relationship between salary advancement and teachers\u2019 job performance (n=4280)<\/strong><\/p>\n\n\n\nModel Summary<\/strong>b<\/sup><\/strong><\/td><\/tr>Model<\/td> R<\/td> R Square<\/td> Adjusted R Square<\/td> Std. Error of the Estimate<\/td> Durbin-Watson<\/td><\/tr> 1<\/td> .842a<\/sup><\/td>.802<\/td> .797<\/td> 2.14243<\/td> 1.959<\/td><\/tr> a. Predictors: (Constant), SALARY ADVANCEMENT<\/td><\/tr> b. Dependent Variable: TEACHERS\u2019 JOB PERFORMANCE<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\nANOVA<\/strong>a<\/sup><\/strong><\/td><\/tr>Model<\/td> Sum of Squares<\/td> Df<\/td> Mean Square<\/td> F<\/td> Sig.<\/td><\/tr> 1<\/td> Regression<\/td> .911<\/td> 1<\/td> .911<\/td> 2.199<\/td> 0.006b<\/sup><\/td><\/tr>Residual<\/td> 514.080<\/td> 4279<\/td> 4.590<\/td> <\/td> <\/td><\/tr> Total<\/td> 514.991<\/td> 4280<\/td> <\/td> <\/td> <\/td><\/tr> a. Dependent Variable: SALARY ADVANCEMENT<\/td><\/tr> b. Predictors: (Constant), TEACHERS\u2019 JOB PERFORMANCE<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\nCoefficients<\/strong>a<\/sup><\/strong><\/td><\/tr>Model<\/strong><\/td>Unstandardized Coefficients<\/strong><\/td>Standardized Coefficients<\/strong><\/td>T<\/strong><\/td>Sig.<\/strong><\/td>Collinearity Statistics<\/strong><\/td><\/tr>B<\/strong><\/td>Std. Error<\/strong><\/td>Beta<\/strong><\/td>Tolerance<\/strong><\/td>VIF<\/strong><\/td><\/tr>1<\/td> (Constant)<\/td> 25.8587<\/td> 2.6633<\/td> <\/td> 9.7093<\/td> 0.05<\/td> <\/td> <\/td><\/tr> SALARY ADVANCEMENT<\/td> 3.0408<\/td> 0.0916<\/td> 0.0421<\/td> 0.446<\/td> 0.006<\/td> 1.000<\/td> 1.000<\/td><\/tr> a. Dependent Variable: TEACHERS\u2019 JOB PERFORMANCE<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\nSource: Field Work, 2025<\/strong><\/p>\n\n\n\nBased on an analysis of the results in table 4.8, the R-squared value is .802. This indicates that approximately, 80.2% teachers\u2019 job performance is explained by salary advancement. The Adjusted R-squared value is .797. This is slightly lower than the R-squared which is due to adjustments for the number of predators in the model. Remember that the value of Durbin Watson statistics lies between 0-4. From 0-1.49 shows presence of positive first order autocorrelation. From 1.5 to 2.5 shows absence of first order autocorrelation. The Durbin Watson statistic is 1.959. This is asymptotically 2 which show absence of first order autocorrelation. <\/p>\n\n\n\n
The F-Statistic is 2.199 with a p-value of 0.006 which is less than 0.05. This indicates that the overall regression model is highly statistically significant. The standard error of the estimate is 2.1424 representing the average deviation of the observed values from the regression line. The beta coefficient for salary advancement is 0.0421. This suggests a strong positive relationship between the salary advancement and teachers\u2019 job performance in secondary schools in Delta central Senatorial District. The t-value for the salary advancement is 1.8537, with a very low p-value of 0.046. This indicates that the coefficient for salary advancement is highly statistically significant. <\/p>\n\n\n\n
The tolerance and VIF values are both 1.00, indicating no issues with multi-collinearity in the model. The coefficient for salary advancement is 3.0408. This suggests that for every unit increase in the 3.0408, the academic performance increases by approximately 3.0408 units. The regression analysis indicates that salary advancement has a strong positive relationship with teachers\u2019 job performance. However, the positive coefficient suggests that higher scores on salary advancement may paradoxically be associated with higher teachers\u2019 job performance.<\/p>\n\n\n\n
H<\/strong>o <\/sub><\/strong>3:<\/strong> <\/strong>There is no significant relationship between awards of teachers and job performance in secondary schools in Delta central Senatorial District<\/p>\n\n\n\nTable 4.9: Linear Regression Result showing the relationship between awards of teachers and job performance in secondary schools in Delta central Senatorial District (n=4280)<\/strong><\/p>\n\n\n\n