07_descriptive_statistics/01_basic_descriptive_statistics.ipynb

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    "# Basic descriptive statistics\n",
    "The term [descriptive statistics](https://en.wikipedia.org/wiki/Descriptive_statistics) refers to methods that allow summarizing collections of data. To demonstrate the most important methods, we start by defining a dataset first."
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    "measurements = [5, 2, 6, 4, 8, 6, 2, 5, 1, 3, 3, 6]"
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    "## Measurements of central tendency\n",
    "We can measure the _location_ of our `measurement` in space using [numpy's statistics functions](https://numpy.org/doc/stable/reference/routines.statistics.html) and Python's [statistics module](https://docs.python.org/3/library/statistics.html)."
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   "source": [
    "import numpy as np\n",
    "import statistics as st"
   ]
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       "4.25"
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    "np.mean(measurements)"
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       "4.5"
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    "np.median(measurements)"
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    "st.mode(measurements)"
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   "source": [
    "## Measurements of spread\n",
    "Numpy also allows measuring the spread of `measurements`."
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   "source": [
    "np.std(measurements)"
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       "4.020833333333333"
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   "source": [
    "np.var(measurements)"
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       "(1, 8)"
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    "np.min(measurements), np.max(measurements)"
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       "array([2.75, 4.5 , 6.  ])"
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    "np.percentile(measurements, [25, 50, 75])"
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   "source": [
    "## Exercise\n",
    "Find out if the median of a sample dataset is always a number within the sample. Use these three examples to elaborate on this:"
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   "source": [
    "example1 = [3, 4, 5]"
   ]
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   "source": [
    "example2 = [3, 4, 4, 5]"
   ]
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   "execution_count": null,
   "id": "1a4cfe20-e174-43e6-8bdd-7bb0d70c2474",
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    "example3 = [3, 4, 5, 6]"
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