There is a mathematical formula so beautiful that it is almost unbelievable.
Euler's identity combines the famous numbers π, π, Ο, 0, and 1 in a single constellation. At first sight, most people doubt that it is true. Surprisingly, it is.
This is why.
π§΅ ππ½
Let's talk about the famous exponential function πΛ£ first.
Have you ever thought about how is this calculated in practice? After all, raising an irrational number to any power is not trivial.
It turns out that the function can be written as an infinite sum!
In fact, this can be done with many other functions.
For those that are differentiable infinitely many times, there is a recipe to find the infinite sum form. This form is called the Taylor expansion.
It does not always yield the original function, but it works for πΛ£.
Taylor expansions are advantageous for two reasons.
First, we can approximate functions by cutting of the sum at some N.
Second, we can simply extend functions to the complex plane with this formula!
The exponential function is not the only one that can be written as a Taylor series.
We can also do this with the trigonometric functions sine and cosine.
(Feel free to check this by hand using the general Taylor expansion formula.)
By plugging in ππ§ into the exponential function, we discover that the complex exponential function can be written in terms of trigonometric functions!
(We use that πΒ² = -1.)
In the special case π§ = Ο, we obtain the famous formula called Euler's identity.
This is how the magic happens.
When asked, Euler's identity often comes up among mathematicians as the most beautiful formula ever.
It is not only amazing because it connects together a bunch of famous constants, but because it establishes a connection between the exponential and trigonometric functions.
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The single biggest argument about statistics: is probability frequentist or Bayesian?
It's neither, and I'll explain why.
Buckle up. Deep-dive explanation incoming.
First, let's look at what is probability.
Probability quantitatively measures the likelihood of events, like rolling six with a dice. It's a number between zero and one. This is independent of interpretation; itβs a rule set in stone.
In the language of probability theory, the events are formalized by sets within an event space.
The Law of Large Numbers is one of the most frequently misunderstood concepts of probability and statistics.
Just because you lost ten blackjack games in a row, it doesnβt mean that youβll be more likely to be lucky next time.
What is the law of large numbers, then? Read on:
The strength of probability theory lies in its ability to translate complex random phenomena into coin tosses, dice rolls, and other simple experiments.
So, letβs stick with coin tossing.
What will the average number of heads be if we toss a coin, say, a thousand times?
To mathematically formalize this question, weβll need random variables.
Tossing a fair coin is described by the Bernoulli distribution, so let Xβ, Xβ, β¦ be such independent and identically distributed random variables.