Model Std. Change Statistics Error of R Adjusted the R Square F Sig. F R Square R Square Estimate Change Change df1 df2 Change dimension0 1 .131a .017 .013 .74965 .017 4.391 1 251 .037 a. Predictors: (Constant), Days of the month Source: Research data The coefficient of determination (R2) in unexplained. The P- value of 0.037 implies table equals 0.017. This shows that that the model of Daily return of stock days of the month explain 1.7 percent of index is not significant at the 5 percent the total variation of Daily return of stock significance level. index leaving only 98.3 percent Table 7: ANOVA Model Sum of Squares Df Mean Square F Sig. 1 Regression 2.468 1 2.468 4.391 .037a Residual 141.057 251 .562 Total 143.525 252 a. Predictors: (Constant), Days of the month b. Dependent Variable: Daily return of stock index The P- value of 0.37 implies that there is days of the month and the Daily return of no linear regression relationship between stock index at 5 percent significance level. Table 8: Year 2005 Model summary Model Std. Change Statistics Error of R Adjusted the R Square F Sig. F R Square R Square Estimate Change Change df1 df2 Change dimension0 1 .015a .000 -.004 .54664 .000 .057 1 246 .811 a. Predictors: (Constant), Days of the month The coefficient of determination (R2) by other factors. The P- value of 0.811 equals 0.000. This shows that days of the implies that the model of Daily return of month do not explain any variation of stock index is not significant at the 5 Daily return of stock index but determined percent significance level. Table 9: ANOVA Model Sum of Squares df Mean Square F Sig. 1 Regression .017 1 .017 .057 .811a Residual 73.507 246 .299
Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df1 df2 Sig. F Change dimension0 1 .131a .017 .013 .74965 .017 4.391 1 251 .037 a. Predictors: (Constant), Days of the month Source: Research data The coefficient of determination (R2) in table equals 0.017. This shows that days of the month explain 1.7 percent of the total variation of Daily return of stock index leaving only 98.3 percent unexplained. The P- value of 0.037 implies that the model of Daily return of stock index is not significant at the 5 percent significance level. Table 7: ANOVA Model Sum of Squares Df Mean Square F Sig. 1 Regression 2.468 1 2.468 4.391 .037a Residual 141.057 251 .562 Total 143.525 252 a. Predictors: (Constant), Days of the month b. Dependent Variable: Daily return of stock index The P- value of 0.37 implies that there is no linear regression relationship between days of the month and the Daily return of stock index at 5 percent significance level. Table 8: Year 2005 Model summary Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df1 df2 Sig. F Change dimension0 1 .015a .000 -.004 .54664 .000 .057 1 246 .811 a. Predictors: (Constant), Days of the month The coefficient of determination (R2) equals 0.000. This shows that days of the month do not explain any variation of Daily return of stock index but determined by other factors. The P- value of 0.811 implies that the model of Daily return of stock index is not significant at the 5 percent significance level. Table 9: ANOVA Model Sum of Squares df Mean Square F Sig. 1 Regression .017 1 .017 .057 .811a Residual 73.507 246 .299
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