From 1076666b22aec3cf1afce28bf740b9595e029a29 Mon Sep 17 00:00:00 2001 From: Lena Ebner Date: Wed, 3 Jan 2024 20:15:43 +0100 Subject: [PATCH] feat: add mean score calculation --- evaluation/ux_evaluation.ipynb | 155 ++++++++++++++++++++++++++++----- 1 file changed, 135 insertions(+), 20 deletions(-) diff --git a/evaluation/ux_evaluation.ipynb b/evaluation/ux_evaluation.ipynb index 032f795..79aac51 100644 --- a/evaluation/ux_evaluation.ipynb +++ b/evaluation/ux_evaluation.ipynb @@ -821,12 +821,12 @@ }, { "cell_type": "code", - "execution_count": 132, + "execution_count": 165, "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ "
" ] @@ -873,11 +873,11 @@ "\n", " # Plot questions for A_data\n", " for i, category in enumerate(category_columns):\n", - " axs[i].bar(A_data[category].value_counts().index - 0.2, A_data[category].value_counts().values, alpha=0.7, width=0.4, label='A_data', color='blue')\n", + " axs[i].bar(A_data[category].value_counts().index - 0.2, A_data[category].value_counts().values, alpha=0.7, width=0.4, label='A', color='blue')\n", "\n", " # Plot questions for B_data\n", " for i, category in enumerate(category_columns):\n", - " axs[i].bar(B_data[category].value_counts().index + 0.2, B_data[category].value_counts().values, alpha=0.7, width=0.4, label='B_data', color='orange')\n", + " axs[i].bar(B_data[category].value_counts().index + 0.2, B_data[category].value_counts().values, alpha=0.7, width=0.4, label='B', color='orange')\n", "\n", " axs[i].set_title(category)\n", " axs[i].legend()\n", @@ -902,12 +902,12 @@ }, { "cell_type": "code", - "execution_count": 133, + "execution_count": 166, "metadata": {}, "outputs": [ { "data": { - "image/png": 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OCSeckEsuuWSJUdhX5FyLde/ePdtss029bZ/8vA9AZbj88svTtm3b7Lvvvkk+nolkn332yYMPPpgXXnihrt0uu+ySu+++O0ny8MMP57333svxxx+fddZZp240t7vvvjvbbrtt2rdv36z3UCgUlsjTK+LMM8/MP/7xj5x//vmNPua2225LmzZtljkry7Rp01JVVZUDDzywXmzdu3fP5ptv3mzTskK5UOQGzWz+/Pl566230rNnz6W2WX/99XP33Xena9euGTVqVNZff/2sv/76K5QU/9eHH36Y6667LptsskldJ8Fib731VhYsWJALLrgga6yxRr1ljz32SJL85z//Weq5Dz300HrH7LLLLp8qxlLfBwClt3jqr6X9oXbBggVZY401ltjepUuXeuvV1dVJPh4ivTEaO7T5m2++mb/85S9L5JkOHTqkUCgskWc+Gdfi2BbH9fbbb2fRokXp3r37Eu0a2taQ4447Li+88EJdB8BFF12UbbfdNltttdUyj9tll13q3UNjpjZt0aJFtt5663rLhhtuWK9NY57l4uHTBwwYsMSzvO6665Z4ju3atav3x/Lk4+f4wQcf1K2/9dZb6dat2xLXauxz/OpXv5o+ffrkoosuSpJMmjQp8+fPN1UpQBlr6veG2bNn54477si2226b7bbbboViW9413nrrrSQN56nG5K5P+zn8sssuy8EHH5wzzzyz3pfGGqM53msAaBpNnTOX9Vlscc5ryJtvvpmpU6cu8blwk002SfL/+nIfe+yxDBkyJMnHuexPf/pTpk+fnp/+9Kf14mlMn3pjz7W0Z7D4OTS2v+GTXn311SXu93+L+Zbmm9/8ZqZPn54ZM2bkueeey1tvvZWf/exnyzymsX0Yr7/+enbcccf885//zPnnn58HH3ww06dPr/t8vPheO3XqlPvvvz9bbLFFfvKTn2STTTZJz54984tf/CIfffTRCp1rsWI/XwBK48UXX8wDDzyQYcOGpVAo5J133sk777yTvffeO0lyxRVX1LUdPHhwXn/99bzwwgu5++67s+WWW6Zr1675yle+krvvvjvvv/9+Hn744QwePLjZ72Py5MlL5M0Vsd122+VrX/tazjjjjLz99tuNOubf//53evbsmRYtll628+abb6ZQKKRbt25LxPfoo4/6+zernValDgBWN7///e+zcOHCDBw4cJntdtxxx+y4445ZuHBhZsyYkQsuuCCjR49Ot27d6qrgG6u6ujr33ntvdttttwwePDi333571l577STJ2muvnZYtW+bb3/72Uv+Q27dv36Wee+zYsfVGi/nfb3YXW1PeBwClt7hj/J///OcSneSFQiH/+te/svXWWxf9ulVVVY1qt84666Rt27b1PpR/cv+KWHvttVNVVZVZs2Ytsa+hbQ35yle+kv79++fCCy/MmmuumSeeeCJXXXXVco/71a9+lXnz5tWtr2jsS9OYZ7n4Wr/97W8bNVpNY3Tp0iWPPfbYEtsb+xxbtGiRUaNG5Sc/+UnOOeecXHzxxdlll12WKOIDoHw09XtD7969c+655+brX/969tprr9xwww1LFF1/Wov/oLu0d4A+ffos8/hP+zm8RYsWufzyy1NVVZWzzz47ixYtyi9/+cvGB74MxXivAaBpNHXOXPxFpv+1+Hd/Q0VMi62zzjrZbLPNctpppzW4f/GXxK+99tqsscYamTZtWr1cfPPNNy9xzPL61FfkXE2hZ8+emT59er1tjfnc+ZnPfGaF/x81tg/j5ptvzvz583PjjTfW+4z+1FNPLXHMpptummuvvTaFQiF/+ctfMmnSpJx88slp27ZtTjzxxBU6FwCrjiuuuCKFQiG//e1v89vf/naJ/ZMnT86pp56ali1b1n1J6+67785dd92VXXfdNcnHX8o+6aST8sADD6S2trZRRW6Lc3ltbW297Z+26GvEiBFL5OkVVVNTk/79++f0009vVPvPfOYzeeihh7Jo0aKlFrqts846qaqqyoMPPlj3pYP/1dA2WJUpcoNm9Prrr+eHP/xhOnXqlCOOOKJRx7Rs2TJf+tKXstFGG+Xqq6/OE088scJFbkmy5ZZb5v7778/gwYMzcODA3HXXXenatWvatWuXQYMG5cknn8xmm22W1q1br9B5+/Tps9wO+GJqqvsAoPS+8pWvpKqqKtddd90SI5HdfvvtmTt3bkm+wbXY8OHDc/rpp6dLly5FKZxu3759ttlmm9x44405++yz6z6Uz5s3L1OnTm30eY499th873vfy5w5c9KtW7fss88+yz2mlMVbu+22W1q1apWXXnqpUdObNsagQYNy/fXX59Zbb603Tc6UKVMafY7DDz88Y8eOzQEHHJDnnnsuZ555ZlFiA6BpNMd7w5AhQ3LHHXdk2LBhGT58eG655ZaiTJfy5S9/OW3atMnVV19dLxc+/PDDee2115b7GXtlPocvLnRr2bJlzjnnnCxatCjnnnvupzrX/yrWew0AxdfUOXPevHkNfhZr0aJFdtppp6UeN3z48PzhD3/I+uuvX/dF5oZUVVWlVatWadmyZd22999/P7/5zW+WeszS+tQ/zbmWZ0VGk2/dunWTfHmvIY3tw1j8ZbX//QN5oVDIZZddtsxjNt9885x33nmZNGlSnnjiiU99ruVZ0dH6AWheCxcuzOTJk7P++uvn17/+9RL7p02blnPOOSe33XZbhg8fnh49emTjjTfO7373uzz++ON1xWC77rprjjjiiJx77rnp2LFjBgwYsNxrL/5c/Je//KVef/ett976qe6lS5cuyyzQb4yNNtoohx56aC644IJGjQo/dOjQXHPNNZk0adJSZ1sZPnx4zjjjjPzzn//MN7/5zZWKD1YFitygiTzzzDN1c2LPnj07Dz74YCZOnJiWLVvmpptuymc+85mlHnvJJZfkj3/8Y4YNG5bevXvngw8+qPvG1cp0OPTr1y8PPvhgBg8enJ122il333131l133Zx//vnZYYcdsuOOO+bII49Mnz59Mm/evLz44ouZOnVq/vjHP37qay7N1KlTG/y2+eKhayvlPgAonvXXXz9HH310zj777LzzzjvZY4890rZt20yfPj1nnHFGtt566+y///4li2/06NH53e9+l5122inf//73s9lmm2XRokV5/fXXc+edd+YHP/hBvvSlL63QOU855ZTsvvvu2XXXXfODH/wgCxcuzJlnnpn27dvnv//9b6POceCBB2bMmDF54IEHctJJJ5V9oXefPn1y8skn56c//Wlefvnl7L777ll77bXz5ptv5rHHHkv79u0zbty4FTrnQQcdlPPOOy8HHXRQTjvttGywwQb5wx/+kDvuuKPR51hrrbVy0EEHZcKECVlvvfUyYsSIFb01AJpRc7037LDDDrnnnnuy++67Z8iQIfnDH/6QTp06rdQ511577fzwhz/MqaeemsMPPzz77LNPZs6cmbFjxzbL1J5VVVW59NJLU1VVlfPOOy+FQiHnnXfeSp+3GO81ABRfU+fMLl265Mgjj8zrr7+eL3zhC/nDH/6Qyy67LEceeWR69+691ONOPvnk3HXXXdluu+1y7LHHZsMNN8wHH3yQV199NX/4wx9yySWXZN11182wYcNy7rnnZv/99893v/vdvPXWW/nlL3+5xKgljelTb+y5VkT//v2TJJdeemk6dOiQNm3apG/fviv9R/KV1dg+jF133TWtW7fOfvvtlx//+Mf54IMPMmHChCWmWZs2bVouvvjifO1rX8vnPve5FAqF3HjjjXnnnXfqRuFp7LlWxPrrr5+2bdvm6quvTr9+/bLmmmumZ8+edSP9AVBat912W954442ceeaZDc5itngWkssvvzzDhw9P8vGobRdccEHatm2b7bffPsnHs3H17ds3d955Z/bcc8+66daXZcCAAdlwww3zwx/+MAsWLMjaa6+dm266KQ899FBR73FFjR07NldffXXuvffe5X5Rbr/99svEiRPzve99L88991wGDRqURYsW5c9//nP69euXfffdN9tvv32++93v5pBDDsmMGTOy0047pX379vnXv/6Vhx56KJtuummOPPLIZro7KD1FbtBEDjnkkCQffztrrbXWSr9+/XLCCSfk8MMPX2aBW5JsscUWufPOO/OLX/wis2bNypprrpn+/fvn1ltvzZAhQ1Yqrs997nN1BWI77rhj7rnnnmy88cZ54okncsopp+Skk07K7Nmzs9Zaa2WDDTbIHnvssVLXW5qlVaMXCoVGHV8u9wFAcZ1//vnZeOONc/nll+eqq67KggULst5662XUqFElL+Bq3759HnzwwZxxxhm59NJL88orr6Rt27bp3bt3Bg8e/KlGVNl1111z880356STTsq3vvWtdO/ePUcddVTef//9Rhd6tW3bNiNGjMhVV12V733veyscQymMGTMmG2+8cc4///xcc801qa2tTffu3TNgwIBPdQ/t2rXLH//4xxx33HE58cQTU1VVlSFDhuTaa69t1DfmFvvWt76VCRMm5Mgjj1zq8PAAlI/mem/Yeuut60YU/8pXvpI77rhjpaf6Pvnkk9O+fftcfPHF+c1vfpONNtool1xySdGmD12eqqqq/OpXv0rLli0zfvz4LFq0KOeff/5KnbMY7zUANI2mzJndu3fPRRddlB/+8If561//ms6dO+cnP/nJcn/39+jRIzNmzMgpp5ySs88+O//4xz/SoUOH9O3bt+7LUMnHI9FdccUVOfPMMzNixIh89rOfzXe+85107do1hx12WN35GtOn3thzrYi+fftm/PjxOf/88zNw4MAsXLgwEydOzMEHH/ypzlcsje3D2GijjfK73/0uJ510Uvbaa6906dIl+++/f44//vgMHTq07nwbbLBB1lprrZx11ll544030rp162y44YaZNGlSRo4cuULnWhHt2rXLFVdckXHjxmXIkCH56KOP8otf/CJjx45d2UcEQBFcfvnlad26dd3fxT9pnXXWyde//vX89re/zZtvvplu3bp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"text/plain": [ "
" ] @@ -954,11 +954,11 @@ "\n", " # Plot questions for A_data\n", " for i, category in enumerate(category_columns):\n", - " axs[i].bar(A_data[category].value_counts().index, A_data[category].value_counts().values, alpha=0.7, label='A_data', color='blue')\n", + " axs[i].bar(A_data[category].value_counts().index, A_data[category].value_counts().values, alpha=0.7, label='A', color='blue')\n", "\n", " # Plot questions for B_data\n", " for i, category in enumerate(category_columns):\n", - " axs[i].bar(B_data[category].value_counts().index, B_data[category].value_counts().values, alpha=0.7, label='B_data', color='orange')\n", + " axs[i].bar(B_data[category].value_counts().index, B_data[category].value_counts().values, alpha=0.7, label='B', color='orange')\n", "\n", " axs[i].set_title(category)\n", " axs[i].legend()\n", @@ -1041,16 +1041,16 @@ " comparison_results.loc[question_label, 'Significant'] = 'Yes' if p_value < 0.05 else 'No'\n", "\n", "# Display the comparison results\n", - "print(comparison_results)\n" + "print(comparison_results)\n", + "\n", + "# no question has a significant difference between the two groups\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Cronbach's Alpha\n", - "\n", - "\n" + "### Cronbach's Alpha Reliability\n" ] }, { @@ -1077,6 +1077,8 @@ } ], "source": [ + "# evaluate the reliability of the questionnaire\n", + "\n", "import pingouin as pg\n", "\n", "# Define your category labels\n", @@ -1106,6 +1108,119 @@ "# except for the perceived safety category, all categories have a Cronbach's Alpha of > 0.7, which is good - acceptable" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Calculate Mean Scores" + ] + }, + { + "cell_type": "code", + "execution_count": 155, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Overall Mean Score for Animacy - A: 2.6491\n", + "Overall Mean Score for Animacy - B: 2.6491\n", + "\n", + "Overall Mean Score for Likeability - A: 3.6632\n", + "Overall Mean Score for Likeability - B: 3.5684\n", + "\n", + "Overall Mean Score for Perceived Intelligence - A: 2.8526\n", + "Overall Mean Score for Perceived Intelligence - B: 2.5474\n", + "\n", + "Overall Mean Score for Perceived Safety - A: 3.6667\n", + "Overall Mean Score for Perceived Safety - B: 3.7544\n", + "\n" + ] + } + ], + "source": [ + "# calucalte mean score for comparision as suggested in https://www.bartneck.de/publications/2009/measurementInstrumentsRobots/\n", + "categories = {\n", + " 'Animacy': animacy_labels,\n", + " 'Likeability': likeability_labels,\n", + " 'Perceived Intelligence': percived_intelligence_labels,\n", + " 'Perceived Safety': percived_safety_labels\n", + "}\n", + "\n", + "# Loop through each category and calculate mean scores\n", + "for category, labels in categories.items():\n", + " # Select the relevant columns for the current category\n", + " category_data_A = A_data[labels]\n", + " category_data_B = B_data[labels]\n", + "\n", + " # Calculate mean scores for each respondent\n", + " mean_scores_A = category_data_A.mean(axis=1)\n", + " mean_scores_B = category_data_B.mean(axis=1)\n", + "\n", + " # Calculate overall mean score for each group\n", + " overall_mean_A = mean_scores_A.mean()\n", + " overall_mean_B = mean_scores_B.mean()\n", + "\n", + " print(f\"Overall Mean Score for {category} - A: {overall_mean_A:.4f}\")\n", + " print(f\"Overall Mean Score for {category} - B: {overall_mean_B:.4f}\\n\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 160, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# visualize mean scores\n", + "\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "\n", + "# Assuming 'A_data' and 'B_data' are your DataFrames with Likert scale responses\n", + "categories = {\n", + " 'Animacy': animacy_labels,\n", + " 'Likeability': likeability_labels,\n", + " 'Perceived Intelligence': percived_intelligence_labels,\n", + " 'Perceived Safety': percived_safety_labels\n", + "}\n", + "\n", + "# Initialize an empty DataFrame to store mean scores\n", + "mean_scores_df = pd.DataFrame(index=categories.keys(), columns=['With Recommender', 'Without Recommender'])\n", + "\n", + "# Loop through each category and calculate mean scores\n", + "for category, labels in categories.items():\n", + " # Select the relevant columns for the current category\n", + " category_data_A = A_data[labels]\n", + " category_data_B = B_data[labels]\n", + "\n", + " # Calculate mean scores for each respondent\n", + " mean_scores_A = category_data_A.mean(axis=1).mean()\n", + " mean_scores_B = category_data_B.mean(axis=1).mean()\n", + "\n", + " # Store mean scores in the DataFrame\n", + " mean_scores_df.loc[category, 'With Recommender'] = mean_scores_A\n", + " mean_scores_df.loc[category, 'Without Recommender'] = mean_scores_B\n", + "\n", + "# Plot the mean scores\n", + "ax = mean_scores_df.plot(kind='bar', rot=0, figsize=(10, 6))\n", + "ax.set_ylabel('Mean Score')\n", + "ax.set_title('Mean Scores for Different Categories of GodSpeed Questionnaire')\n", + "\n", + "plt.show()\n" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -1115,7 +1230,7 @@ }, { "cell_type": "code", - "execution_count": 127, + "execution_count": 156, "metadata": {}, "outputs": [ { @@ -1124,7 +1239,7 @@ "" ] }, - "execution_count": 127, + "execution_count": 156, "metadata": {}, "output_type": "execute_result" },