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@vivekkr12
Last active April 2, 2020 23:21
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FY 2021 H1B lottery analysis
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# H1B Lottery"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import math\n",
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This year **275000** applications were filed for lottery in which **46%** had a US Masters"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"total_applicants = 275000\n",
"masters_applicants = .46 * total_applicants\n",
"other_applicants = total_applicants - total_applicants\n",
"\n",
"overall_quota = 65000\n",
"masters_quota = 20000"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Non Masters Applicant's Chances"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Chances of non masters applicants: 0.23636363636363636\n"
]
}
],
"source": [
"non_masters_p = overall_quota / total_applicants\n",
"print('Chances of non masters applicants: {}'.format(non_masters_p))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Modelling as a geometric distribution:\n",
"\n",
"$X_{non-masters} \\thicksim Geom(0.236)$ \n",
"$P(X_{non-masters} \\le k) = 1 - (1 - p)^k$"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"k = np.arange(1, 7)\n",
"non_masters_ps = 1 - (1 - non_masters_p) ** k\n",
"non_masters_exp = 1 / non_masters_p"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(k, non_masters_ps)\n",
"plt.axvline(x=non_masters_exp, linestyle='--')\n",
"plt.xlabel('Attempts')\n",
"plt.ylabel('Probability');"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Masters Applicant's Chances"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Chances of masters applicants: 0.41632273656813534\n"
]
}
],
"source": [
"# probability of getting picked in the general pool\n",
"masters_common_p = non_masters_p\n",
"\n",
"# probability of getting picked in masters pool\n",
"masters_selected_common = masters_common_p * overall_quota\n",
"masters_applicants_left = masters_applicants - masters_selected_common\n",
"\n",
"masters_specific_p = masters_quota / masters_applicants_left\n",
"masters_p = masters_common_p + masters_specific_p\n",
"\n",
"print('Chances of masters applicants: {}'.format(masters_p))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Modelling as a geometric distribution:\n",
"\n",
"$X_{masters} \\thicksim Geom(0.416)$ \n",
"$P(X_{masters} \\le k) = 1 - (1 - p)^k$"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"k = np.arange(1, 7)\n",
"masters_ps = 1 - (1 - masters_p) ** k\n",
"masters_exp = 1 / masters_p"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(k, masters_ps, color='green')\n",
"plt.axvline(x=masters_exp, linestyle='--', color='green')\n",
"plt.xlabel('Attempts')\n",
"plt.ylabel('Probability');"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Compare Masters and Non Masters"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>attemps</th>\n",
" <th>non_masters_prob</th>\n",
" <th>masters_prob</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>0.236364</td>\n",
" <td>0.416323</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>0.416860</td>\n",
" <td>0.659321</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>0.554693</td>\n",
" <td>0.801153</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>0.659947</td>\n",
" <td>0.883938</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>0.740323</td>\n",
" <td>0.932257</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>6</td>\n",
" <td>0.801701</td>\n",
" <td>0.960460</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" attemps non_masters_prob masters_prob\n",
"0 1 0.236364 0.416323\n",
"1 2 0.416860 0.659321\n",
"2 3 0.554693 0.801153\n",
"3 4 0.659947 0.883938\n",
"4 5 0.740323 0.932257\n",
"5 6 0.801701 0.960460"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pd.DataFrame({'attemps': k, 'non_masters_prob': non_masters_ps, 'masters_prob': masters_ps})"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(16, 8))\n",
"plt.plot(k, non_masters_ps, label='Non Masters')\n",
"plt.plot(k, masters_ps, label='Masters', color='green')\n",
"plt.axvline(x=non_masters_exp, label='Non Masters Expectation', linestyle='--')\n",
"plt.axvline(x=masters_exp, label='Masters Expectation', linestyle='--', color='green')\n",
"plt.xlabel('Attempts')\n",
"plt.ylabel('Probability')\n",
"plt.legend();"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Non masters candidate are expected to get H1B in 5 attempts as masters candidates are expected to get it in 3 attemps.\n"
]
}
],
"source": [
"print('Non masters candidate are expected to get H1B in {} attempts and masters ' \n",
" 'candidates are expected to get it in {} attemps.'.format(math.ceil(non_masters_exp), math.ceil(masters_exp)))"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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