43 lines
1.4 KiB
Plaintext
43 lines
1.4 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n# Normal distribution: histogram and PDF\n\nExplore the normal distribution: a histogram built from samples and the\nPDF (probability density function).\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"import numpy as np\nimport scipy as sp\nimport matplotlib.pyplot as plt\n\ndist = sp.stats.norm(loc=0, scale=1) # standard normal distribution\nsample = dist.rvs(size=100000) # \"random variate sample\"\nplt.hist(\n sample,\n bins=51, # group the observations into 50 bins\n density=True, # normalize the frequencies\n label=\"normalized histogram\",\n)\n\nx = np.linspace(-5, 5) # possible values of the random variable\nplt.plot(x, dist.pdf(x), label=\"PDF\")\nplt.legend()\nplt.show()"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.11"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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