knuckletouch/python/Step_41_R.ipynb

In [7]:

df = read.csv("./DataStudyEvaluation/R_TLX.csv")
df$ID <- factor(df$ID)
df$Task <- factor(df$Task)
friedman.test(Score ~ Task | ID, data = df)

	Friedman rank sum test

data:  Score and Task and ID
Friedman chi-squared = 12, df = 1, p-value = 0.000532

In [8]:

df = read.csv("./DataStudyEvaluation/R_SUS.csv")
df$ID <- factor(df$ID)
df$Task <- factor(df$Task)
friedman.test(Score ~ Task | ID, data = df)

	Friedman rank sum test

data:  Score and Task and ID
Friedman chi-squared = 8.3333, df = 1, p-value = 0.003892

In [6]:

df = read.csv("./DataStudyEvaluation/R_Quest.csv")
df$ID <- factor(df$ID)
df$Task <- factor(df$Task)
friedman.test(Easiness ~ Task | ID, data = df)
friedman.test(Speed ~ Task | ID, data = df)
friedman.test(Success ~ Task | ID, data = df)
friedman.test(Accuracy ~ Task | ID, data = df)
friedman.test(Comfort ~ Task | ID, data = df)

	Friedman rank sum test

data:  Easiness and Task and ID
Friedman chi-squared = 8.3333, df = 1, p-value = 0.003892

	Friedman rank sum test

data:  Speed and Task and ID
Friedman chi-squared = 12, df = 1, p-value = 0.000532

	Friedman rank sum test

data:  Success and Task and ID
Friedman chi-squared = 6.4, df = 1, p-value = 0.01141

	Friedman rank sum test

data:  Accuracy and Task and ID
Friedman chi-squared = 11, df = 1, p-value = 0.0009111

	Friedman rank sum test

data:  Comfort and Task and ID
Friedman chi-squared = 12, df = 1, p-value = 0.000532

In [ ]: