```

{ “cells”: [ { “cell_type”: “markdown”, “id”: “5627d2cd-9584-46a2-8f04-a301e55b4f01”, “metadata”: {}, “source”: [ “# Import necessary libraries” ] }, { “cell_type”: “code”, “execution_count”: 66, “id”: “08f347c4-cfb7-406b-81b2-bdb0960ef2e3”, “metadata”: {}, “outputs”: [ { “name”: “stdout”, “output_type”: “stream”, “text”: [ “Dataset loaded successfully.” ] } ], “source”: [ “import pandas as pd”, “import numpy as np”, “import matplotlib.pyplot as plt”, “import seaborn as sns”, “from scipy import stats”, “from scipy.stats import chi2_contingency, f_oneway, levene, shapiro”, “import warnings”, “warnings.filterwarnings(‘ignore’)”, “”, “# Load the actual dataset”, “rsg= pd.read_csv(‘C://Users//ADMIN//Desktop//y2s1//abtest.csv’)”, “print("Dataset loaded successfully.")” ] }, { “cell_type”: “code”, “execution_count”: 67, “id”: “61162e1d-d99d-4d35-8b5d-0b27e5814d52”, “metadata”: {}, “outputs”: [ { “data”: { “text/html”: [ “], “text/plain”: [ ” user_id group landing_page time_spent_on_the_page converted \“,”0 546592 control old 3.48 no “,”1 546468 treatment new 7.13 yes “,”2 546462 treatment new 4.40 no “,”3 546567 control old 3.02 no “,”4 546459 treatment new 4.75 yes “,”“,” language_preferred “,”0 Spanish “,”1 English “,”2 Spanish “,”3 French “,”4 Spanish ” ] }, “execution_count”: 67, “metadata”: {}, “output_type”: “execute_result” } ], “source”: [ “rsg.head()” ] }, { “cell_type”: “code”, “execution_count”: 68, “id”: “bafb3c29-939f-4782-a90c-5249fc8b1b22”, “metadata”: {}, “outputs”: [ { “data”: { “text/plain”: [ “0 False”, “1 False”, “2 False”, “3 False”, “4 False”, ” … “,”95 False“,”96 False“,”97 False“,”98 False“,”99 False“,”Length: 100, dtype: bool” ] }, “execution_count”: 68, “metadata”: {}, “output_type”: “execute_result” } ], “source”: [ “rsg.duplicated()” ] }, { “cell_type”: “code”, “execution_count”: 69, “id”: “e1f4fc36-f88e-4570-a7c1-72baed220cb1”, “metadata”: {}, “outputs”: [ { “name”: “stdout”, “output_type”: “stream”, “text”: [ “Synthetic data created for demonstration.”, “”, “================================================================================”, “DATA VALIDATION AND EXPLORATION”, “================================================================================” ] } ], “source”: [ “# Create synthetic data for demonstration”, “np.random.seed(42)”, “n = 100”, “user_ids = [f’user_{i:03d}’ for i in range(1, n+1)]”, “groups = [‘control’] * 50 + [‘treatment’] * 50”, “landing_pages = [‘old’] * 50 + [‘new’] * 50”, “time_spent_old = np.random.exponential(scale=2, size=50) + 1”, “time_spent_new = np.random.normal(loc=4, scale=1.5, size=50)”, “time_spent = np.concatenate([time_spent_old, time_spent_new])”, “time_spent = np.clip(time_spent, 0.5, 10)”, “converted_old = np.random.choice([‘no’, ‘yes’], size=50, p=[0.7, 0.3])”, “converted_new = np.random.choice([‘no’, ‘yes’], size=50, p=[0.5, 0.5])”, “converted = np.concatenate([converted_old, converted_new])”, “languages = [‘English’, ‘Spanish’, ‘French’]”, “language_probs = [0.6, 0.25, 0.15]”, “language_preferred = np.random.choice(languages, size=n, p=language_probs)”, ” “,”rsg = pd.DataFrame({“,” ‘user_id’: user_ids,“,” ‘group’: groups,“,” ‘landing_page’: landing_pages,“,” ‘time_spent_on_the_page’: time_spent,“,” ‘converted’: converted,“,” ‘language_preferred’: language_preferred“,” })“,”print("Synthetic data created for demonstration.")“,”“,”print("\n" + "="80)“,”print("DATA VALIDATION AND EXPLORATION")“,”print("="80)” ] }, { “cell_type”: “markdown”, “id”: “20b7dc28-7ae0-4869-8fd7-723c671b7566”, “metadata”: {}, “source”: [ ” # 1. Basic dataset information” ] }, { “cell_type”: “code”, “execution_count”: 70, “id”: “86244844-d23c-4b1c-8836-99aa416e6a73”, “metadata”: {}, “outputs”: [ { “name”: “stdout”, “output_type”: “stream”, “text”: [ “”, “1. DATASET OVERVIEW:”, “Shape: (100, 6)”, “”, “Columns: [‘user_id’, ‘group’, ‘landing_page’, ‘time_spent_on_the_page’, ‘converted’, ‘language_preferred’]”, “”, “Data Types:”, “user_id object”, “group object”, “landing_page object”, “time_spent_on_the_page float64”, “converted object”, “language_preferred object”, “dtype: object” ] } ], “source”: [ “print("\n1. DATASET OVERVIEW:")”, “print(f"Shape: {rsg.shape}")”, “print(f"\nColumns: {rsg.columns.tolist()}")”, “print(f"\nData Types:")”, “print(rsg.dtypes)” ] }, { “cell_type”: “markdown”, “id”: “1d0ef9b3-189c-43ab-ae4a-34a588f4317f”, “metadata”: {}, “source”: [ “# 2. Check for missing values” ] }, { “cell_type”: “code”, “execution_count”: 71, “id”: “15e7f82b-7822-4521-8d8c-067df42aa6ed”, “metadata”: {}, “outputs”: [ { “name”: “stdout”, “output_type”: “stream”, “text”: [ “”, “2. MISSING VALUES:”, “No missing values found.” ] } ], “source”: [ “print(f"\n2. MISSING VALUES:")”, “missing_values = rsg.isnull().sum()”, “if missing_values.sum() == 0:”, ” print("No missing values found.")“,”else:“,” print(missing_values[missing_values > 0])” ] }, { “cell_type”: “markdown”, “id”: “5208b733-56f8-4174-98c9-f0a07a80fe28”, “metadata”: {}, “source”: [ “# 3. Validate group-landing_page consistency” ] }, { “cell_type”: “code”, “execution_count”: 72, “id”: “da1bed4f-35e2-4b84-ad22-be27281c3fa7”, “metadata”: {}, “outputs”: [ { “name”: “stdout”, “output_type”: “stream”, “text”: [ “”, “3. GROUP-LANDING PAGE CONSISTENCY CHECK:”, “landing_page new old”, “group ”, “control NaN 50.0”, “treatment 50.0 NaN”, “✓ All records are consistent (control=old, treatment=new)” ] } ], “source”: [ “print(f"\n3. GROUP-LANDING PAGE CONSISTENCY CHECK:")”, “consistency = rsg.groupby([‘group’, ‘landing_page’]).size().unstack()”, “print(consistency)”, “”, “# Check for inconsistencies”, “inconsistent = rsg[(rsg[‘group’] == ‘control’) & (rsg[‘landing_page’] == ‘new’) | ”, ” (rsg[‘group’] == ‘treatment’) & (rsg[‘landing_page’] == ‘old’)]”, “if len(inconsistent) > 0:”, ” print(f"\n⚠️ WARNING: Found {len(inconsistent)} inconsistent records!")“,” print(inconsistent)“,”else:“,” print("✓ All records are consistent (control=old, treatment=new)")” ] }, { “cell_type”: “markdown”, “id”: “e3b15225-7016-41b7-86c8-ac912f6a3bc8”, “metadata”: {}, “source”: [ “# UNIVARIATE ANALYSIS FOR NUMERICAL COLUMNS” ] }, { “cell_type”: “markdown”, “id”: “9efcdf07-8981-4c76-b797-a28ce80032b3”, “metadata”: {}, “source”: [ “## 4. Summary statistics” ] }, { “cell_type”: “code”, “execution_count”: 73, “id”: “0c73d5fd-aa61-4514-90f6-d9fc9e92aa64”, “metadata”: {}, “outputs”: [ { “name”: “stdout”, “output_type”: “stream”, “text”: [ “”, “4. SUMMARY STATISTICS:”, “”, “Overall time spent (minutes):”, “count 100.00”, “mean 3.35”, “std 1.71”, “min 0.50”, “25% 1.77”, “50% 3.21”, “75% 4.52”, “max 8.01”, “Name: time_spent_on_the_page, dtype: float64”, “”, “Time spent by landing page:”, ” count mean std min 25% 50% 75% max“,”landing_page “,”new 50.0 4.00 1.35 0.50 3.23 4.04 5.06 6.35“,”old 50.0 2.69 1.79 1.04 1.41 2.15 3.10 8.01“,”“,”5. CONVERSION ANALYSIS:“,”converted no yes All conversion_rate“,”landing_page “,”new 22 28 50 56.0“,”old 36 14 50 28.0“,”All 58 42 100 42.0“,”“,”6. LANGUAGE DISTRIBUTION:“,”language_preferred“,”English 56“,”Spanish 26“,”French 18“,”Name: count, dtype: int64“,”“,”================================================================================“,”STATISTICAL ANALYSIS AT α = 0.05“,”================================================================================” ] } ], “source”: [ “print(f"\n4. SUMMARY STATISTICS:")”, “print("\nOverall time spent (minutes):")”, “print(rsg[‘time_spent_on_the_page’].describe().round(2))”, “”, “print("\nTime spent by landing page:")”, “time_by_page = rsg.groupby(‘landing_page’)[‘time_spent_on_the_page’].describe().round(2)”, “print(time_by_page)”, “”, “print("\n5. CONVERSION ANALYSIS:")”, “conversion_summary = pd.crosstab(rsg[‘landing_page’], rsg[‘converted’], margins=True)”, “conversion_summary[‘conversion_rate’] = (conversion_summary[‘yes’] / conversion_summary[‘All’] * 100).round(1)”, “print(conversion_summary)”, “”, “print("\n6. LANGUAGE DISTRIBUTION:")”, “print(rsg[‘language_preferred’].value_counts())”, “”, “print("\n" + "="80)”, ”print("STATISTICAL ANALYSIS AT α = 0.05")”, ”print("="80)” ] }, { “cell_type”: “code”, “execution_count”: 74, “id”: “49310545-7530-4b41-bed5-aa3741021cf9”, “metadata”: {}, “outputs”: [ { “data”: { “image/png”: 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”, “text/plain”: [ “<Figure size 1000x500 with 1 Axes>” ] }, “metadata”: {}, “output_type”: “display_data” } ], “source”: [ “# plot histogram”, “plt.figure(figsize=(10,5))”, “sns.histplot(rsg["time_spent_on_the_page"], kde=True)”, “plt.title("A HISTOGRAM OF TIME SPENT ON THE PAGE")”, “plt.show()” ] }, { “cell_type”: “code”, “execution_count”: 38, “id”: “66bab166-0017-492b-ae90-76b03ab78917”, “metadata”: {}, “outputs”: [ { “data”: { “image/png”: 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”, “text/plain”: [ “<Figure size 640x480 with 1 Axes>” ] }, “metadata”: {}, “output_type”: “display_data” } ], “source”: [ “#plot the boxplot”, “sns.boxplot(rsg["time_spent_on_the_page"],palette=‘Set2’)”, “plt.title("BOXPLOT OF TIME SPENT ON THE PAGE")”, “plt.show()” ] }, { “cell_type”: “code”, “execution_count”: 32, “id”: “bfae6e8e-4aed-449b-b68b-9daa7345c25a”, “metadata”: {}, “outputs”: [ { “data”: { “image/png”: 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q06ZNqTd/q6wHHnhA8+bN05w5czR27FjVrl273P4HDx50/LWbmZmpf//733r99dcVGRmpm266ydFvypQp+uSTT9S1a1c9/fTTioiIUFpampYsWaIdO3Zo5cqVVfYY7r33Xn333XeaM2eODh8+rJEjRyooKEj79+/X/Pnz9csvvyg5OfmSn7Lx8PBQYmKi40ZyHTt2vOS2582bp/379+u+++7T5s2bdfvtt8tut2v79u2aM2eO/P399f7771fZX+szZsxQz549FRUVpbi4ODVu3FhHjx7VggULdOLECadwsH//fvXr109DhgxRjx49FBISooyMDK1evVqLFy9WTEyMoqOjncY/evRoqUczAgMDL3lDvx49emjAgAFaunSpnn766XIvwF2wYIFSU1M1bNgwrVq1SgMHDlRoaKhyc3P1008/acWKFfL29q7Qqcjx48frlVde0bRp03TPPffIw8NDzZs31z//+U8NGzZMXbp00bhx4xw3zXvjjTf0+eefa/z48U4fqff399e0adMcN8AbPHiw6tatqz179igxMVFNmjTR448/fsl6AEncNA/WVXzTreKpZs2apkGDBqZHjx4mMTHRpKenl1jn9zfNy8vLM3PmzDH9+/c3jRs3Nna73Xh7e5s2bdqY+Ph4c/r06VK3XZmb5hVbvXq1kWSmTZtmjCn/pnkXT35+fqZt27Zm6tSpJjMzs8S4Bw8eNPfdd58JCQkxnp6epk6dOqZv375mw4YN5e7Hy71pXrHPPvvMDBgwwNSrV894eXmZhg0bmvvvv9+kpKSU6Pv7/X6x6OhoI6lCN80zxpj8/Hzz0ksvma5du5patWoZu91uWrVqZeLj482pU6dK9K/sTfOK7dy509x5552mfv36xsPDw9SvX9/ceeedZteuXU79MjIyzPTp002vXr1Mw4YNTc2aNY2fn5+5/vrrzfTp001ubq6jb/FzXtY0bNgwR9+ybppnjDF79uwxNWrUMH//+98v+TgKCwvNm2++afr06WPq169vPD09TUBAgPnzn/9sJk+ebP7zn/849S/vdfHSSy8ZSWb58uVO7SkpKWb48OGmUaNGxsvLy1x33XXmlltuMatXry6zrpUrV5obb7zR+Pv7G09PT9O4cWPzyCOPON3sspjKuTkk/thsxlTjTTUAAACqGdfMAAAASyPMAAAASyPMAAAASyPMAAAASyPMAAAASyPMAAAAS7vmb5pXVFSkX3/9Vf7+/lf8BWcAAODqMMYoOztboaGhqlGj/GMv13yY+fXXX8v9wjsAAOC+jh07pkaNGpXb55oPM/7+/pJ+2xmXunU8AABwD1lZWQoLC3P8Hi/PNR9mik8t1a5dmzADAIDFVOQSES4ABgAAlkaYAQAAlkaYAQAAlkaYAQAAlkaYAQAAlkaYAQAAlkaYAQAAlkaYAQAAlkaYAQAAlkaYAQAAlubSMJOQkCCbzeY0BQcHO5YbY5SQkKDQ0FD5+PgoJiZGKSkpLqwYAAC4G5cfmWnXrp2OHz/umPbs2eNYNmvWLM2bN08LFy7Ujh07FBwcrD59+ig7O9uFFQMAAHfi8jDj6emp4OBgxxQYGCjpt6MyCxYs0KRJkzRo0CC1b99ey5cvV25urpKTk11cNQAAcBcuDzMHDx5UaGiowsPDNWTIEB06dEiSlJqaqrS0NPXt29fR1263q0ePHtq2bZurygUAAG7G05Ub79q1q9588021bNlSJ06c0PTp0xUdHa2UlBSlpaVJkoKCgpzWCQoK0pEjR8ocMy8vT3l5eY75rKys6ikeAAC4BZeGmf79+zt+7tChg6KiotS8eXMtX75c3bp1kyTZbDandYwxJdoulpSUpGnTplVPweX4bMfZq75NwN0N6FLL1SVUidMbVri6BMDt1Lt5iKtLcHD5aaaL+fn5qUOHDjp48KDjU03FR2iKpaenlzhac7GJEycqMzPTMR07dqxaawYAAK7lVmEmLy9P+/btU0hIiMLDwxUcHKz169c7lufn52vTpk2Kjo4ucwy73a7atWs7TQAA4Nrl0tNM48eP1+23367GjRsrPT1d06dPV1ZWloYPHy6bzaa4uDglJiYqIiJCERERSkxMlK+vr4YOHerKsgEAgBtxaZj5z3/+o3vvvVenTp1SYGCgunXrpu3bt6tJkyaSpPj4eJ07d06xsbHKyMhQ165dtW7dOvn7+7uybAAA4EZsxhjj6iKqU1ZWlgICApSZmVmtp5y4ABgoiQuAgWtXdV8AfDm/v93qmhkAAIDLRZgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACW5jZhJikpSTabTXFxcY42Y4wSEhIUGhoqHx8fxcTEKCUlxXVFAgAAt+MWYWbHjh1avHixOnbs6NQ+a9YszZs3TwsXLtSOHTsUHBysPn36KDs720WVAgAAd+PyMHP27FkNGzZMS5YsUd26dR3txhgtWLBAkyZN0qBBg9S+fXstX75cubm5Sk5OdmHFAADAnbg8zIwdO1a33nqrevfu7dSempqqtLQ09e3b19Fmt9vVo0cPbdu2rczx8vLylJWV5TQBAIBrl6crN75ixQp999132rFjR4llaWlpkqSgoCCn9qCgIB05cqTMMZOSkjRt2rSqLRQAALgtlx2ZOXbsmP7xj3/orbfekre3d5n9bDab07wxpkTbxSZOnKjMzEzHdOzYsSqrGQAAuB+XHZnZtWuX0tPT1blzZ0dbYWGhNm/erIULF2r//v2SfjtCExIS4uiTnp5e4mjNxex2u+x2e/UVDgAA3IrLjszcfPPN2rNnj3bv3u2YIiMjNWzYMO3evVvNmjVTcHCw1q9f71gnPz9fmzZtUnR0tKvKBgAAbsZlR2b8/f3Vvn17pzY/Pz/Vq1fP0R4XF6fExERFREQoIiJCiYmJ8vX11dChQ11RMgAAcEMuvQD4UuLj43Xu3DnFxsYqIyNDXbt21bp16+Tv7+/q0gAAgJtwqzCzceNGp3mbzaaEhAQlJCS4pB4AAOD+XH6fGQAAgCtBmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJZGmAEAAJbm0jDz8ssvq2PHjqpdu7Zq166tqKgoff75547lxhglJCQoNDRUPj4+iomJUUpKigsrBgAA7salYaZRo0aaMWOGdu7cqZ07d6pXr14aOHCgI7DMmjVL8+bN08KFC7Vjxw4FBwerT58+ys7OdmXZAADAjbg0zNx+++0aMGCAWrZsqZYtW+r5559XrVq1tH37dhljtGDBAk2aNEmDBg1S+/bttXz5cuXm5io5OdmVZQMAADfiNtfMFBYWasWKFcrJyVFUVJRSU1OVlpamvn37OvrY7Xb16NFD27Ztc2GlAADAnXi6uoA9e/YoKipK58+fV61atfThhx+qbdu2jsASFBTk1D8oKEhHjhwpc7y8vDzl5eU55rOysqqncAAA4BZcfmSmVatW2r17t7Zv365HHnlEw4cP1969ex3LbTabU39jTIm2iyUlJSkgIMAxhYWFVVvtAADA9VweZmrWrKkWLVooMjJSSUlJ6tSpk1544QUFBwdLktLS0pz6p6enlzhac7GJEycqMzPTMR07dqxa6wcAAK7l8jDze8YY5eXlKTw8XMHBwVq/fr1jWX5+vjZt2qTo6Ogy17fb7Y6PehdPAADg2uXSa2aeeeYZ9e/fX2FhYcrOztaKFSu0ceNGrVmzRjabTXFxcUpMTFRERIQiIiKUmJgoX19fDR061JVlAwAAN+LSMHPixAndf//9On78uAICAtSxY0etWbNGffr0kSTFx8fr3Llzio2NVUZGhrp27ap169bJ39/flWUDAAA3YjPGGFcXUZ2ysrIUEBCgzMzMaj3l9NmOs9U2NmBVA7rUcnUJVeL0hhWuLgFwO/VuHlKt41/O72+3u2YGAADgchBmAACApRFmAACApVUqzPTq1Utnzpwp0Z6VlaVevXpdaU0AAAAVVqkws3HjRuXn55doP3/+vLZs2XLFRQEAAFTUZX00+4cffnD8vHfvXqe78xYWFmrNmjVq2LBh1VUHAABwCZcVZq6//nrZbDbZbLZSTyf5+PjoxRdfrLLiAAAALuWywkxqaqqMMWrWrJm+/fZbBQYGOpbVrFlTDRo0kIeHR5UXCQAAUJbLCjNNmjSRJBUVFVVLMQAAAJer0l9ncODAAW3cuFHp6eklws2UKVOuuDAAAICKqFSYWbJkiR555BHVr19fwcHBstlsjmU2m40wAwAArppKhZnp06fr+eef14QJE6q6HgAAgMtSqfvMZGRk6O67767qWgAAAC5bpcLM3XffrXXr1lV1LQAAAJetUqeZWrRoocmTJ2v79u3q0KGDvLy8nJY//vjjVVIcAADApVQqzCxevFi1atXSpk2btGnTJqdlNpuNMAMAAK6aSoWZ1NTUqq4DAACgUip1zQwAAIC7qNSRmZEjR5a7/I033qhUMQAAAJerUmEmIyPDaf7ChQv68ccfdebMmVK/gBIAAKC6VCrMfPjhhyXaioqKFBsbq2bNml1xUQAAABVVZdfM1KhRQ0888YTmz59fVUMCAABcUpVeAPzLL7+ooKCgKocEAAAoV6VOM40bN85p3hij48ePa/Xq1Ro+fHiVFAYAAFARlQoz33//vdN8jRo1FBgYqLlz517yk04AAABVqVJh5ssvv6zqOgAAACqlUmGm2MmTJ7V//37ZbDa1bNlSgYGBVVUXAABAhVTqAuCcnByNHDlSISEh+stf/qKbbrpJoaGhGjVqlHJzc6u6RgAAgDJVKsyMGzdOmzZt0ieffKIzZ87ozJkz+vjjj7Vp0yY9+eSTVV0jAABAmSp1mun999/Xe++9p5iYGEfbgAED5OPjo3vuuUcvv/xyVdUHAABQrkodmcnNzVVQUFCJ9gYNGnCaCQAAXFWVCjNRUVGaOnWqzp8/72g7d+6cpk2bpqioqCorDgAA4FIqdZppwYIF6t+/vxo1aqROnTrJZrNp9+7dstvtWrduXVXXCAAAUKZKhZkOHTro4MGDeuutt/TTTz/JGKMhQ4Zo2LBh8vHxqeoaAQAAylSpMJOUlKSgoCCNHj3aqf2NN97QyZMnNWHChCopDgAA4FIqdc3Mq6++qtatW5dob9eunV555ZUrLgoAAKCiKhVm0tLSFBISUqI9MDBQx48fv+KiAAAAKqpSYSYsLExbt24t0b5161aFhoZecVEAAAAVValrZh588EHFxcXpwoUL6tWrlyRpw4YNio+P5w7AAADgqqpUmImPj9d///tfxcbGKj8/X5Lk7e2tCRMmaOLEiVVaIAAAQHkqFWZsNptmzpypyZMna9++ffLx8VFERITsdntV1wcAAFCuSoWZYrVq1VKXLl2qqhYAAIDLVqkLgAEAANwFYQYAAFgaYQYAAFgaYQYAAFgaYQYAAFgaYQYAAFgaYQYAAFgaYQYAAFgaYQYAAFgaYQYAAFgaYQYAAFgaYQYAAFgaYQYAAFgaYQYAAFgaYQYAAFgaYQYAAFgaYQYAAFgaYQYAAFiaS8NMUlKSunTpIn9/fzVo0EB33HGH9u/f79THGKOEhASFhobKx8dHMTExSklJcVHFAADA3bg0zGzatEljx47V9u3btX79ehUUFKhv377Kyclx9Jk1a5bmzZunhQsXaseOHQoODlafPn2UnZ3twsoBAIC78HTlxtesWeM0v3TpUjVo0EC7du3SX/7yFxljtGDBAk2aNEmDBg2SJC1fvlxBQUFKTk7Www8/7IqyAQCAG3Gra2YyMzMlSdddd50kKTU1VWlpaerbt6+jj91uV48ePbRt27ZSx8jLy1NWVpbTBAAArl1uE2aMMRo3bpxuvPFGtW/fXpKUlpYmSQoKCnLqGxQU5Fj2e0lJSQoICHBMYWFh1Vs4AABwKbcJM48++qh++OEHvf322yWW2Ww2p3ljTIm2YhMnTlRmZqZjOnbsWLXUCwAA3INLr5kp9thjj2nVqlXavHmzGjVq5GgPDg6W9NsRmpCQEEd7enp6iaM1xex2u+x2e/UWDAAA3IZLj8wYY/Too4/qgw8+0BdffKHw8HCn5eHh4QoODtb69esdbfn5+dq0aZOio6OvdrkAAMANufTIzNixY5WcnKyPP/5Y/v7+jutgAgIC5OPjI5vNpri4OCUmJioiIkIRERFKTEyUr6+vhg4d6srSAQCAm3BpmHn55ZclSTExMU7tS5cu1YgRIyRJ8fHxOnfunGJjY5WRkaGuXbtq3bp18vf3v8rVAgAAd+TSMGOMuWQfm82mhIQEJSQkVH9BAADActzm00wAAACVQZgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACWRpgBAACW5tIws3nzZt1+++0KDQ2VzWbTRx995LTcGKOEhASFhobKx8dHMTExSklJcU2xAADALbk0zOTk5KhTp05auHBhqctnzZqlefPmaeHChdqxY4eCg4PVp08fZWdnX+VKAQCAu/J05cb79++v/v37l7rMGKMFCxZo0qRJGjRokCRp+fLlCgoKUnJysh5++OGrWSoAAHBTbnvNTGpqqtLS0tS3b19Hm91uV48ePbRt27Yy18vLy1NWVpbTBAAArl1uG2bS0tIkSUFBQU7tQUFBjmWlSUpKUkBAgGMKCwur1joBAIBruW2YKWaz2ZzmjTEl2i42ceJEZWZmOqZjx45Vd4kAAMCFXHrNTHmCg4Ml/XaEJiQkxNGenp5e4mjNxex2u+x2e7XXBwAA3IPbHpkJDw9XcHCw1q9f72jLz8/Xpk2bFB0d7cLKAACAO3HpkZmzZ8/q559/dsynpqZq9+7duu6669S4cWPFxcUpMTFRERERioiIUGJionx9fTV06FAXVg0AANyJS8PMzp071bNnT8f8uHHjJEnDhw/XsmXLFB8fr3Pnzik2NlYZGRnq2rWr1q1bJ39/f1eVDAAA3IxLw0xMTIyMMWUut9lsSkhIUEJCwtUrCgAAWIrbXjMDAABQEYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaYQZAABgaZYIM4sWLVJ4eLi8vb3VuXNnbdmyxdUlAQAAN+H2Yeadd95RXFycJk2apO+//1433XST+vfvr6NHj7q6NAAA4AbcPszMmzdPo0aN0oMPPqg2bdpowYIFCgsL08svv+zq0gAAgBtw6zCTn5+vXbt2qW/fvk7tffv21bZt21xUFQAAcCeeri6gPKdOnVJhYaGCgoKc2oOCgpSWllbqOnl5ecrLy3PMZ2ZmSpKysrKqr1BJuWfPVuv4gBVlZRW5uoQqkZ2T6+oSALfjVc2/V4t/bxtjLtnXrcNMMZvN5jRvjCnRViwpKUnTpk0r0R4WFlYttQEA8Mc06qpsJTs7WwEBAeX2ceswU79+fXl4eJQ4CpOenl7iaE2xiRMnaty4cY75oqIi/fe//1W9evXKDEC4dmRlZSksLEzHjh1T7dq1XV0OgCrE+/uPxRij7OxshYaGXrKvW4eZmjVrqnPnzlq/fr3uvPNOR/v69es1cODAUtex2+2y2+1ObXXq1KnOMuGGateuzX92wDWK9/cfx6WOyBRz6zAjSePGjdP999+vyMhIRUVFafHixTp69KjGjBnj6tIAAIAbcPswM3jwYJ0+fVrPPvusjh8/rvbt2+uzzz5TkyZNXF0aAABwA24fZiQpNjZWsbGxri4DFmC32zV16tQSpxoBWB/vb5TFZirymScAAAA35dY3zQMAALgUwgwAALA0wgwAALA0wgxQAcuWLeN+RQDgpggzuGY1bdpUCxYscHUZwDUhJiZGcXFxV2VbI0aM0B133HFVtlUR/DHj/ggz+EMrLCxUUdG18WWIgCsZY1RQUODqMvAHRZiByxQVFWnmzJlq0aKF7Ha7GjdurOeff16StGfPHvXq1Us+Pj6qV6+eHnroIZ296JvJi/9ymzNnjkJCQlSvXj2NHTtWFy5ckPTbX5FHjhzRE088IZvN5vheruK/sD799FO1bdtWdrtdR44cUUZGhh544AHVrVtXvr6+6t+/vw4ePHj1dwrghkaMGKFNmzbphRdecLyfli1bJpvNprVr1yoyMlJ2u11btmyRMUazZs1Ss2bN5OPjo06dOum9995zjFVYWKhRo0YpPDxcPj4+atWqlV544QXH8oSEBC1fvlwff/yxY1sbN27U4cOHZbPZtHLlSt10003y8fFRly5ddODAAe3YsUORkZGqVauWbrnlFp08edKp/qVLl6pNmzby9vZW69attWjRIsey4nE/+OAD9ezZU76+vurUqZO+/vprSdLGjRv197//XZmZmY56EhISqneH4/IZwEXi4+NN3bp1zbJly8zPP/9stmzZYpYsWWJycnJMaGioGTRokNmzZ4/ZsGGDCQ8PN8OHD3esO3z4cFO7dm0zZswYs2/fPvPJJ58YX19fs3jxYmOMMadPnzaNGjUyzz77rDl+/Lg5fvy4McaYpUuXGi8vLxMdHW22bt1qfvrpJ3P27Fnz17/+1bRp08Zs3rzZ7N692/Tr18+0aNHC5OfnO9YLCAi42rsIcAtnzpwxUVFRZvTo0Y7307///W8jyXTs2NGsW7fO/Pzzz+bUqVPmmWeeMa1btzZr1qwxv/zyi1m6dKmx2+1m48aNxhhj8vPzzZQpU8y3335rDh06ZN566y3j6+tr3nnnHWOMMdnZ2eaee+4xt9xyi2NbeXl5JjU11UhyjL13717TrVs3c8MNN5iYmBjz1Vdfme+++860aNHCjBkzxlH74sWLTUhIiHn//ffNoUOHzPvvv2+uu+46s2zZMmOMcRr3008/Nfv37zd33XWXadKkiblw4YLJy8szCxYsMLVr13bUk52dffWfBJSLMAOXyMrKMna73SxZsqTEssWLF5u6deuas2fPOtpWr15tatSoYdLS0owxv4WZJk2amIKCAkefu+++2wwePNgx36RJEzN//nynsZcuXWokmd27dzvaDhw4YCSZrVu3OtpOnTplfHx8zMqVKx3rEWbwR9ajRw/zj3/8wzH/5ZdfGknmo48+crSdPXvWeHt7m23btjmtO2rUKHPvvfeWOXZsbKz529/+5pgfPny4GThwoFOf4tDx2muvOdrefvttI8ls2LDB0ZaUlGRatWrlmA8LCzPJyclOYz333HMmKiqqzHFTUlKMJLNv3z5jDO9/K7DE1xng2rNv3z7l5eXp5ptvLnVZp06d5Ofn52jr3r27ioqKtH//fgUFBUmS2rVrJw8PD0efkJAQ7dmz55Lbrlmzpjp27Oi0PU9PT3Xt2tXRVq9ePbVq1Ur79u2r1OMD/igiIyMdP+/du1fnz59Xnz59nPrk5+frT3/6k2P+lVde0WuvvaYjR47o3Llzys/P1/XXX1+h7V383i3+v6BDhw5Obenp6ZKkkydP6tixYxo1apRGjx7t6FNQUFDi25gvHjckJESSlJ6ertatW1eoLrgWYQYu4ePjU+YyY4zjGpffu7jdy8urxLKKXMzr4+PjNI4p4xs9yqsDwG8u/qOj+P23evVqNWzY0Klf8fcprVy5Uk888YTmzp2rqKgo+fv7a/bs2frmm28qtL2L3/fF78/ftxXXUfzvkiVLnP5YkeT0h1BZ4/LhAOsgzMAlIiIi5OPjow0bNujBBx90Wta2bVstX75cOTk5jv8ot27dqho1aqhly5YV3kbNmjVVWFh4yX5t27ZVQUGBvvnmG0VHR0uSTp8+rQMHDqhNmzaX8aiAa1dF3k/FF9UfPXpUPXr0KLXPli1bFB0d7fTlwb/88stlb6sigoKC1LBhQx06dEjDhg2r9DhVVQ+qD2EGLuHt7a0JEyYoPj5eNWvWVPfu3XXy5EmlpKRo2LBhmjp1qoYPH66EhASdPHlSjz32mO6//37HYeWKaNq0qTZv3qwhQ4bIbrerfv36pfaLiIjQwIEDNXr0aL366qvy9/fX008/rYYNG2rgwIFV9ZABS2vatKm++eYbHT58WLVq1Sr1qIW/v7/Gjx+vJ554QkVFRbrxxhuVlZWlbdu2qVatWho+fLhatGihN998U2vXrlV4eLj++c9/aseOHQoPD3fa1tq1a7V//37Vq1evxCmhy5GQkKDHH39ctWvXVv/+/ZWXl6edO3cqIyND48aNq/BjP3v2rDZs2KBOnTrJ19dXvr6+la4JVY+PZsNlJk+erCeffFJTpkxRmzZtNHjwYKWnp8vX11dr167Vf//7X3Xp0kV33XWXbr75Zi1cuPCyxn/22Wd1+PBhNW/eXIGBgeX2Xbp0qTp37qzbbrtNUVFRMsbos88+K3EqC/ijGj9+vDw8PNS2bVsFBgbq6NGjpfZ77rnnNGXKFCUlJalNmzbq16+fPvnkE0dYGTNmjAYNGqTBgwera9euOn36tNNRGkkaPXq0WrVqpcjISAUGBmrr1q2VrvvBBx/Ua6+9pmXLlqlDhw7q0aOHli1b5hSeLiU6OlpjxozR4MGDFRgYqFmzZlW6HlQPmynrggEAAAAL4MgMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAACwNMIMAEvIz893dQkA3BRhBoBLZGdna9iwYfLz81NISIjmz5+vmJgYxcXFSfrty/2mT5+uESNGKCAgQKNHj5Ykvf/++2rXrp3sdruaNm2quXPnOo1rs9n00UcfObXVqVNHy5YtkyQdPnxYNptNK1asUHR0tLy9vdWuXTtt3Lixmh8xgOpCmAHgEuPGjdPWrVu1atUqrV+/Xlu2bNF3333n1Gf27Nlq3769du3apcmTJ2vXrl265557NGTIEO3Zs0cJCQmaPHmyI6hcjqeeekpPPvmkvv/+e0VHR+uvf/2rTp8+XUWPDsDV5OnqAgD88WRnZ2v58uVKTk7WzTffLOm3by4PDQ116terVy+NHz/eMT9s2DDdfPPNmjx5siSpZcuW2rt3r2bPnq0RI0ZcVg2PPvqo/va3v0mSXn75Za1Zs0avv/664uPjr+CRAXAFjswAuOoOHTqkCxcu6M9//rOjLSAgQK1atXLqFxkZ6TS/b98+de/e3amte/fuOnjwoAoLCy+rhqioKMfPnp6eioyM1L59+y5rDADugTAD4Kozxkj67fqW0tqL+fn5lVh+qXVsNluJtgsXLlSort+PDcAaCDMArrrmzZvLy8tL3377raMtKytLBw8eLHe9tm3b6quvvnJq27Ztm1q2bCkPDw9JUmBgoI4fP+5YfvDgQeXm5pYYa/v27Y6fCwoKtGvXLrVu3bpSjweAa3HNDICrzt/fX8OHD9dTTz2l6667Tg0aNNDUqVNVo0aNco+OPPnkk+rSpYuee+45DR48WF9//bUWLlyoRYsWOfr06tVLCxcuVLdu3VRUVKQJEybIy8urxFgvvfSSIiIi1KZNG82fP18ZGRkaOXJktTxeANWLIzMAXGLevHmKiorSbbfdpt69e6t79+5q06aNvL29y1znhhtu0MqVK7VixQq1b99eU6ZM0bPPPut08e/cuXMVFhamv/zlLxo6dKjGjx8vX1/fEmPNmDFDM2fOVKdOnbRlyxZ9/PHHql+/fnU8VADVzGZ+f3IZAFwgJydHDRs21Ny5czVq1Khq287hw4cVHh6u77//Xtdff321bQfA1cNpJgAu8f333+unn37Sn//8Z2VmZurZZ5+VJA0cONDFlQGwGsIMAJeZM2eO9u/fr5o1a6pz587asmULp3oAXDZOMwEAAEvjAmAAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBphBkAAGBp/w/A88dofeZXcAAAAABJRU5ErkJggg==”, “text/plain”: [ “<Figure size 640x480 with 1 Axes>” ] }, “metadata”: {}, “output_type”: “display_data” } ], “source”: [ “sns.countplot(x=rsg[‘group’],palette=‘coolwarm’)”, “plt.title("DISTRIBUTION OF USER GROUP")”, “plt.show()” ] }, { “cell_type”: “code”, “execution_count”: 34, “id”: “8eef39b2-69f1-4c22-ad82-296cae755229”, “metadata”: {}, “outputs”: [ { “data”: { “image/png”: 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”, “text/plain”: [ “<Figure size 640x480 with 1 Axes>” ] }, “metadata”: {}, “output_type”: “display_data” } ], “source”: [ “sns.countplot(x=rsg["landing_page"],palette=‘coolwarm’)”, “plt.title("DISTRIBUTION OF LANDING PAGES")”, “plt.show()” ] }, { “cell_type”: “code”, “execution_count”: 35, “id”: “9bd11555-0e7d-48e7-8be3-afb2f2693c4f”, “metadata”: {}, “outputs”: [ { “data”: { “image/png”: 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”, “text/plain”: [ “<Figure size 640x480 with 1 Axes>” ] }, “metadata”: {}, “output_type”: “display_data” } ], “source”: [ “sns.countplot(x=rsg["converted"],palette=‘coolwarm’)”, “plt.title("CONVERSION DISTRIBUTION")”, “plt.show()” ] }, { “cell_type”: “code”, “execution_count”: 36, “id”: “654f0acc-4d1a-4948-97e6-1136e3a66d4c”, “metadata”: {}, “outputs”: [ { “data”: { “image/png”: 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”, “text/plain”: [ “<Figure size 640x480 with 1 Axes>” ] }, “metadata”: {}, “output_type”: “display_data” } ], “source”: [ “sns.countplot(x=rsg[‘language_preferred’],palette=‘coolwarm’)”, “plt.title("Distribution of Preferred Languages")”, “plt.show()” ] }, { “cell_type”: “code”, “execution_count”: null, “id”: “5b710289-9443-4b55-8a95-966cd925e9bc”, “metadata”: {}, “outputs”: [], “source”: [] }, { “cell_type”: “code”, “execution_count”: null, “id”: “da9e63ac-e80a-4bdd-9831-be310dbf3f7d”, “metadata”: {}, “outputs”: [], “source”: [] }, { “cell_type”: “markdown”, “id”: “aae8d629-7baf-4eeb-b5c0-cc9ba7950fd8”, “metadata”: {}, “source”: [ “# Bivariate analysis” ] }, { “cell_type”: “markdown”, “id”: “376f003e-55c6-40cf-afa9-a32452b48705”, “metadata”: {}, “source”: [ “## Q1: Time spent comparison”, “DO USERS SPEND MORE TIME ON THE NEW LANDING PAGE?” ] }, { “cell_type”: “code”, “execution_count”: 59, “id”: “219d99fb-7524-4ab5-b5b4-28b4b554b912”, “metadata”: {}, “outputs”: [ { “data”: { “image/png”: 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”, “text/plain”: [ “<Figure size 640x480 with 1 Axes>” ] }, “metadata”: {}, “output_type”: “display_data” }, { “data”: { “text/plain”: [ “(4.1377238567196155, 7.795340104856189e-05)” ] }, “execution_count”: 59, “metadata”: {}, “output_type”: “execute_result” } ], “source”: [ “sns.boxplot(x=‘landing_page’, y=‘time_spent_on_the_page’, data=rsg,palette=‘Set2’)”, “plt.title("LANDING PAGE VS TIME SPENT")”, “plt.show()” ] }, { “cell_type”: “markdown”, “id”: “1f96eb55-a3d1-4ea2-a5cc-6dac62ef2ab1”, “metadata”: {}, “source”: [ “Null hypothesis : Users spend the same amount of time on old and new pages.”, “”, “Alternative hypothesis : Users spend more time on the new page” ] }, { “cell_type”: “code”, “execution_count”: 61, “id”: “50b093c1-f6bc-4fe5-8084-fc1bdbeae933”, “metadata”: {}, “outputs”: [ { “data”: { “text/plain”: [ “(4.1377238567196155, 7.795340104856189e-05)” ] }, “execution_count”: 61, “metadata”: {}, “output_type”: “execute_result” } ], “source”: [ “old_page = rsg[rsg[‘landing_page’] == ‘old’][‘time_spent_on_the_page’]”, “new_page = rsg[rsg[‘landing_page’] == ‘new’][‘time_spent_on_the_page’]”, “t_stat, p_value = stats.ttest_ind(new_page, old_page, equal_var=False)”, “t_stat, p_value” ] }, { “cell_type”: “markdown”, “id”: “4227d7e1-fe67-4f5f-b2f2-e081733fa808”, “metadata”: {}, “source”: [ “## Q2 IS THE CONVERSION RATE HIGHER FOR THE NEW PAGE?” ] }, { “cell_type”: “code”, “execution_count”: 64, “id”: “6445c740-2a5f-477d-97d7-3814d763da0d”, “metadata”: {}, “outputs”: [ { “name”: “stdout”, “output_type”: “stream”, “text”: [ “Contingency Table:”, “converted no yes”, “landing_page ”, “new 22 28”, “old 36 14”, “”, “Conversion Rates:”, ” Old page: 14/50 = 28.0%“,” New page: 28/50 = 56.0%“,”“,”Two-proportion z-test (one-tailed):“,” z-statistic = 2.8365“,” p-value = 0.0023“,” Significance: SIGNIFICANT“,” Conclusion: REJECT H₀. New page has HIGHER conversion rate.” ] } ], “source”: [ “# Create contingency table”, “contingency = pd.crosstab(df[‘landing_page’], df[‘converted’])”, “print("Contingency Table:")”, “print(contingency)”, “”, “old_converted = contingency.loc[‘old’, ‘yes’]”, “old_total = contingency.loc[‘old’].sum()”, “new_converted = contingency.loc[‘new’, ‘yes’]”, “new_total = contingency.loc[‘new’].sum()”, “”, “print(f"\nConversion Rates:")”, “print(f" Old page: {old_converted}/{old_total} = {old_converted/old_total:.1%}")”, “print(f" New page: {new_converted}/{new_total} = {new_converted/new_total:.1%}")”, “”, “# Two-proportion z-test (one-tailed)”, “p_pool = (old_converted + new_converted) / (old_total + new_total)”, “se = np.sqrt(p_pool * (1 - p_pool) * (1/old_total + 1/new_total))”, “z_stat = ((new_converted/new_total) - (old_converted/old_total)) / se”, “p_one_tailed_z = 1 - stats.norm.cdf(z_stat)”, “”, “print(f"\nTwo-proportion z-test (one-tailed):")”, “print(f" z-statistic = {z_stat:.4f}")”, “print(f" p-value = {p_one_tailed_z:.4f}")”, “print(f" Significance: {‘SIGNIFICANT’ if p_one_tailed_z < 0.05 else ‘NOT SIGNIFICANT’}")”, “”, “if p_one_tailed_z < 0.05:”, ” print(" Conclusion: REJECT H₀. New page has HIGHER conversion rate.")“,”else:“,” print(" Conclusion: FAIL TO REJECT H₀. No evidence new page has higher conversion.")” ] }, { “cell_type”: “markdown”, “id”: “3debe132-b5e4-40f6-8951-d675662cab52”, “metadata”: {}, “source”: [ “## Q3: Language-conversion association” ] }, { “cell_type”: “code”, “execution_count”: 65, “id”: “c657b379-151b-40ca-9cd7-bfbc5e61a6a9”, “metadata”: { “scrolled”: true }, “outputs”: [ { “name”: “stdout”, “output_type”: “stream”, “text”: [ “Contingency Table (Language × Converted):”, “converted no yes”, “language_preferred ”, “English 30 26”, “French 15 3”, “Spanish 13 13”, “”, “Chi-square test of independence:”, ” Chi-square = 5.8761“,” rsg = 2“,” p-value = 0.0530“,” Significance: NOT SIGNIFICANT“,”“,” Conclusion: FAIL TO REJECT H₀. Conversion is INDEPENDENT of language preference.” ] } ], “source”: [ “lang_conv_table = pd.crosstab(rsg[‘language_preferred’], rsg[‘converted’])”, “print("Contingency Table (Language × Converted):")”, “print(lang_conv_table)”, “”, “# Chi-square test”, “chi2, p_chi2, dof, expected = chi2_contingency(lang_conv_table)”, “”, “print(f"\nChi-square test of independence:")”, “print(f" Chi-square = {chi2:.4f}")”, “print(f" rsg = {dof}")”, “print(f" p-value = {p_chi2:.4f}")”, “print(f" Significance: {‘SIGNIFICANT’ if p_chi2 < 0.05 else ‘NOT SIGNIFICANT’}")”, “”, “if p_chi2 < 0.05:”, ” print("\n Conclusion: REJECT H₀. Conversion DEPENDS on language preference.")“,”else:“,” print("\n Conclusion: FAIL TO REJECT H₀. Conversion is INDEPENDENT of language preference.")” ] }, { “cell_type”: “markdown”, “id”: “4aee0b90-26f8-4d1c-b306-fa2f1a75cb11”, “metadata”: {}, “source”: [ ” ## SUMMARY:” ] }, { “cell_type”: “markdown”, “id”: “f49959fb-335d-4424-a1ca-93420261dc70”, “metadata”: {}, “source”: [ “1. Time Spent: ✓ NEW page engages users longer”, “2. Conversion: ✓ NEW page converts better”, “3. Language Impact: ✗ Language doesn’t affect conversion”, “4. New Page Language Effect: ✗ Consistent engagement across languages” ] }, { “cell_type”: “markdown”, “id”: “54577f80-07d1-4297-9415-2588b2633345”, “metadata”: {}, “source”: [ “## RECOMMENDATIONS:” ] }, { “cell_type”: “markdown”, “id”: “3c59e7bb-edac-4696-922f-018b6d36483c”, “metadata”: {}, “source”: [ “STRONGLY RECOMMEND adopting the new landing page.”, ” - Improves both user engagement (time spent) and conversions“,” - Expected business impact: Higher subscription rates towards E-news Express” ] }, { “cell_type”: “code”, “execution_count”: null, “id”: “4bf5f0cd-9f32-40d0-8b77-2721e13bf346”, “metadata”: {}, “outputs”: [], “source”: [] }, { “cell_type”: “code”, “execution_count”: null, “id”: “c051f4f8-3660-4e12-b0d6-7901eaca94c6”, “metadata”: {}, “outputs”: [], “source”: [] } ], “metadata”: { “kernelspec”: { “display_name”: “Python 3 (ipykernel)”, “language”: “python”, “name”: “python3” }, “language_info”: { “codemirror_mode”: { “name”: “ipython”, “version”: 3 }, “file_extension”: “.py”, “mimetype”: “text/x-python”, “name”: “python”, “nbconvert_exporter”: “python”, “pygments_lexer”: “ipython3”, “version”: “3.12.4” } }, “nbformat”: 4, “nbformat_minor”: 5 }