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{
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"metadata": {
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"name": "",
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"signature": "sha256:24d12ab64e5e93c82e0acf22e043d94d7006b033acc4160a5a99e702b6873929"
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},
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"nbformat": 3,
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"nbformat_minor": 0,
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"worksheets": []
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}
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{
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"metadata": {
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"name": "",
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"signature": "sha256:6e213e0ffdde370316cc333b037d57ea45f20abdf0e10161f44da1cba400842d"
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},
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"nbformat": 3,
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"nbformat_minor": 0,
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"worksheets": [
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{
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"cells": [
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"from scipy import stats\n",
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"import scipy as sp\n",
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"import numpy as np\n",
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"import math\n",
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"import matplotlib.pyplot as plt\n",
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"%matplotlib inline"
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],
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 1
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"x = np.random.uniform(size=1000)\n",
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"\n",
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"plt.hist(x)\n",
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"plt.show()"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"metadata": {},
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"output_type": "display_data",
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"png": 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"text": [
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"<matplotlib.figure.Figure at 0x107ab0510>"
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]
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}
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],
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"prompt_number": 2
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"y = x**4\n",
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"\n",
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"plt.hist(y)\n",
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"plt.show()"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"metadata": {},
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"output_type": "display_data",
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"png": 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Untitled0.ipynb

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