Added week2: Basic statistics

Auquan · Aug 8, 2019 · 208a812 · 208a812
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diff --git a/week-01/04_random_variables.ipynb b/week-01/04_random_variables.ipynb
@@ -19,7 +19,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Uniform Distribution\n",
+    "## Uniform Distribution\n",
     "The uniform distribution can also be defined within the framework of a continous random variable. We take $a$ and $b$ to be constant, where $b$ is the highest possible value and $a$ is the lowest possible value that the outcome can obtain. Then the PDF of a uniform random variable is:\n",
     "\n",
     "$$f(x) = \\begin{cases}\\frac{1}{b - a} & \\text{for $a < x < b$} \\ 0 & \\text{otherwise}\\end{cases}$$\n",
@@ -115,7 +115,7 @@
    "source": [
     "The most widely used distribution with widespread applications in finance is the normal distribution.\n",
     "\n",
-    "# Normal Distribution\n",
+    "## Normal Distribution\n",
     "\n",
     "Many important tests and methods in statistics, and by extension, finance, are based on the assumption of normality. A large part of this is due to the results of the Central Limit Theorem (CLT) which we will talk about below. The convenience of the normal distribution finds its way into certain algorithmic trading strategies as well. "
    ]