knuckletouch/python/Step_41_R.ipynb

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2019-08-07 23:57:12 +02:00
{
"cells": [
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\n",
"\tFriedman rank sum test\n",
"\n",
"data: Score and Task and ID\n",
"Friedman chi-squared = 12, df = 1, p-value = 0.000532\n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df = read.csv(\"./DataStudyEvaluation/R_TLX.csv\")\n",
"df$ID <- factor(df$ID)\n",
"df$Task <- factor(df$Task)\n",
"friedman.test(Score ~ Task | ID, data = df)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\n",
"\tFriedman rank sum test\n",
"\n",
"data: Score and Task and ID\n",
"Friedman chi-squared = 8.3333, df = 1, p-value = 0.003892\n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df = read.csv(\"./DataStudyEvaluation/R_SUS.csv\")\n",
"df$ID <- factor(df$ID)\n",
"df$Task <- factor(df$Task)\n",
"friedman.test(Score ~ Task | ID, data = df)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\n",
"\tFriedman rank sum test\n",
"\n",
"data: Easiness and Task and ID\n",
"Friedman chi-squared = 8.3333, df = 1, p-value = 0.003892\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"\n",
"\tFriedman rank sum test\n",
"\n",
"data: Speed and Task and ID\n",
"Friedman chi-squared = 12, df = 1, p-value = 0.000532\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"\n",
"\tFriedman rank sum test\n",
"\n",
"data: Success and Task and ID\n",
"Friedman chi-squared = 6.4, df = 1, p-value = 0.01141\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"\n",
"\tFriedman rank sum test\n",
"\n",
"data: Accuracy and Task and ID\n",
"Friedman chi-squared = 11, df = 1, p-value = 0.0009111\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"\n",
"\tFriedman rank sum test\n",
"\n",
"data: Comfort and Task and ID\n",
"Friedman chi-squared = 12, df = 1, p-value = 0.000532\n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df = read.csv(\"./DataStudyEvaluation/R_Quest.csv\")\n",
"df$ID <- factor(df$ID)\n",
"df$Task <- factor(df$Task)\n",
"friedman.test(Easiness ~ Task | ID, data = df)\n",
"friedman.test(Speed ~ Task | ID, data = df)\n",
"friedman.test(Success ~ Task | ID, data = df)\n",
"friedman.test(Accuracy ~ Task | ID, data = df)\n",
"friedman.test(Comfort ~ Task | ID, data = df)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "R",
"language": "R",
"name": "ir"
},
"language_info": {
"codemirror_mode": "r",
"file_extension": ".r",
"mimetype": "text/x-r-source",
"name": "R",
"pygments_lexer": "r",
"version": "3.5.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}