In [2]:
scores = read.csv("drp.csv")
In [3]:
head(scores)
Out[3]:
DRPGroup
110Control
217Control
319Control
420Control
526Control
628Control
In [9]:
t.test(scores$DRP~scores$Group,var.equal=T,conf.level=0.95)
Out[9]:
	Two Sample t-test

data:  scores$DRP by scores$Group
t = -2.2666, df = 42, p-value = 0.02863
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -18.817650  -1.091253
sample estimates:
  mean in group Control mean in group Treatment 
               41.52174                51.47619
In [10]:
# box-and-whisker plots make it easy to spot outliers.
boxplot(scores$DRP~scores$Group)
In [12]:
# The split command lets you split the values of one variable by another.  This is useful if you want QQ-plots or histograms of the separated data. 
groupscores = split(scores$DRP,scores$Group)
In [13]:
groupscores$Control
Out[13]:
  1. 10
  2. 17
  3. 19
  4. 20
  5. 26
  6. 28
  7. 33
  8. 37
  9. 37
  10. 41
  11. 42
  12. 42
  13. 42
  14. 43
  15. 46
  16. 48
  17. 53
  18. 54
  19. 55
  20. 55
  21. 60
  22. 62
  23. 85
In [14]:
qqnorm(groupscores$Control)
In [ ]:
















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