Would these appear correct.

Figure l Scatterpiot of Age Predicting Sig/1 with a Line ofBest F it man 0 60.00 . . . . I O O O O . I I O ' I 50.00 0 O O O . . o o 3 o ' 42.410061 40.00 . \\f O O . I I O O O O I o o a 30.00 c O I I O O O U I 2mm 0 5.00 1000 15.00 20 .00 25.00 mm 3500 slgA R2 Linear = 01:01 In Figure 1 above, the assumptions of normality, linearity and homoscedasticity and appear to be tenable. The residuals display no evidence of clustering above or below the zero line, no curvilinear bends, or fanning of residuals to either side. Here, Age being the dependent variable, and $3.133\" being the independent variable, these variables negatively correlated as value of x goes up the value of y goes down, displaying a very weak negative linear relationship as the data has an R2 of 0.001. What is the most associated variable with sigA. Conduct a regression QUESTION 6 Regression of OC, EFFORT and REWARD Predicting Concentration of SIga Coefficients Unstandardized Standardized Collinearity Coefficients Coefficients Correlations Statistics Std. Zero- Model B Error Beta Sig. order Partial Part Tolerance VIF 1 (Constant) 21.785 4.160 5.237 .000 OC .357 .207 -.201 .090 -.222 -.214 921 1.085 1.721 193 EFFORT -.428 . 179 -.278 - .020 -.355 -.290 928 1.077 2.385 267 REWARD .235 .097 .277 2.412 .019 .280 .293 .270 .956 1.046 a. Dependent Variable: sigA Table 1 The Individual Contributions of OC, EFFORT and REWARD ST B p OC -,222 -.193 -0.201 -1.721 .090 EFFORT .355 .267 -0.278 -2.385 .020 REWARD .280 .270 0.277 2.412 .019 REWARD was the best, and most statistically significant, predictor of sigA, sr = .27, (3, 62) = 2.412, p = .019.|