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a guest Jun 18th, 2019 60 Never
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  1. >T
  2.         Role Salary
  3. 1  Developer 139750
  4. 2  Developer 173200
  5. 3  Developer  79750
  6. 4  Developer 115000
  7. 5  Developer     NA
  8. 6   Analyst   97000
  9. 7       <NA> 175000
  10. 8   Analyst  147765
  11. 9   Analyst  119250
  12. 10  Analyst      NA
  13. 11        QA  79800
  14. 12        QA  77700
  15. 13      <NA>  78000
  16. 14        QA 104800
  17. 15        QA 117150
  18. 16        QA 101000
  19. 17        QA     NA
  20. 18        QA 124750
  21. 19        QA 137000
  22. 20 Developer     NA
  23. 21 Developer 106294
  24.      
  25. > tgroup <- data.frame(cbind(T$Role,T$Salary))
  26. > sGroups <- stack(tgroup)
  27. > areslt <- aov(values~ind,data=sGroups)
  28. > summary(areslt)
  29.  
  30.             Df    Sum Sq   Mean Sq F value Pr(>F)    
  31. ind          1 1.209e+11 1.209e+11   270.4 <2e-16 ***
  32. Residuals   34 1.520e+10 4.470e+08                  
  33. ---
  34. Signif. codes:  0 β€˜***’ 0.001 β€˜**’ 0.01 β€˜*’ 0.05 β€˜.’ 0.1 β€˜ ’ 1
  35. 6 observations deleted due to missingness
  36.      
  37. > taov <- aov(Salary~Role,data=T)
  38. > summary(taov)
  39.             Df    Sum Sq   Mean Sq F value Pr(>F)
  40. Role         2 9.865e+08 493252642   0.639  0.545
  41. Residuals   12 9.260e+09 771648886              
  42. 6 observations deleted due to missingness
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