The Truth About Why Programmers Are More Intelligent Than Doctors?

Doctors Are Smarter Than All? Is That Possible? — And What That Means For You Discussed In Details!

Nobody: I’m a doctor, will you marry me?

In my country, there is a misconception that All doctors are so brilliant or, even more ridiculously, that Doctors are wiser than others. Today, I want to put this myth to the test.

Manifesto: Question Description

Imagine there is a particular illness called the D, and we have 8 D positives out of every 10,000 people; with a test that is 99% accurate (to clarify, Rapid Covid tests are believed to be 70% reliable/Source). What does a positive test signify in this situation?

Let me illustrate; Joe had always known that in medical diagnostics, a positive test signifies you have the disease, a test result means you are not infected, and so on. In fact, a positive is undesirable, and we prefer negatives. Our Joe was walking down the street one day when he came across a banner that read: FREE D TEST!

He thought to himself, “If it’s free, I’ll do it.” He received the results after a week. He was both astonished and terrified (D was incurable) because the test did not yield the desired findings! Joe couldn’t tell his family or even his partner about it (can you guess why?).

Just for the record, I’ve always had a thing for viruses.

The Truth About Intelligence

Most dictionaries paraphrase Intelligence as the capacity to use knowledge in a way that affects one’s environment or allows one to think abstractly as determined by objective standards.

Once more, what does a positive test mean? You would absolutely state that the test result for a D+ patient must read POSITIVE. And I can see why.

Data Scientist: The Sexiest Job of the 21st Century

Let’s examine the issue, though, from the perspective of a programmer (more specifically a data scientist: who has the sexiest job of the 21st century as Harvard Business Review says):

Let’s use T for the event “Joe’s Test Is Positive” and D for the event “Joe Has The Disease.” The laws of probability state that Joe has the disease, conditional on testing positive is P(D|T), and that we must calculate.

Basic Concepts Of Probability

Now, let’s go step by step. We have the probability that someone with the disease tests positive (which is the test accuracy) and it is P(T|D) = 0.99; We also have the probability that any given person has the disease (8 out of 10,000), and it is P(D) = 0.0008. If we think about the problem a bit more, we get to the conclusion that we also have the probability that someone without the disease tests positive, and it is P(T|¬D) = 0.01. The probability of not being diseased is also P(¬D) = 0.9992. What do we want? I said earlier, P(D|T), which we don’t have. But we do have P(T|D), right? Let’s use math.

Hard Stuff: Conditional probability

In probability theory, conditional probability is a measure of the probability of an event occurring, given that another event (by assumption, presumption, assertion, or evidence) has already occurred. (Wikipedia)

Remember that Joe had no symptoms and he took the test since it was free.

The event of testing positive could be rewritten as either “With the Disease & Tested Positive” or “Without the Disease & Tested Positive”:

Which could be rewritten again as:

And the final result, which we were waiting for too long:

Proof of Bayes theorem

Now that we have the formula for what we want, we only need to fill in the blanks right? Hell, no! We programmers do like to overcomplicate things and use Python for everything. It's like going on a date with your girlfriend by an A-10.

I know that A-10 Warthog is single-seated, but you get the irony, right?

Anyways, I open a Jupyter Notebook and write the code:

The true accuracy for this test is only 7% and not 99%

Conclusion

Without a doubt, 7.27% is a lot smaller percentage than 99%. It implies that, despite Joe’s fright, there is no need for it. He most likely does not have AIDS at all. I assume you must have guessed what the illness was.

An intuitive way to put it would be:

Consider the 81 million people who live in Germany; we would anticipate 64 thousand to have AIDS, yet only a little more than 63 thousand would test positive for HIV. So I encourage you to use a condom because even though they test negative, less than a thousand people are still with AIDS. Additionally, we anticipate that more than 800,000 people will test positive even though only 64,000 of them actually have the disease if we screen everyone.

I should point you that this information came from UNAIDS’ 2010 statistics on Germany. I was too lazy to look for the most recent information on AIDS in Germany after 2010, thus I didn’t discover it. I also didn’t speak German. You could also conduct the research independently.

In Other Countries

We are even more shocked if the same analysis is performed in other nations. For instance, I tested it in the US, Rwanda, and Eswatini, and the accuracy of the results is as follows:

• A positive HIV test in the US indicates a slightly higher than 23% likelihood of having AIDS;
• Rwanda has a rate of about 70%;
• And in Eswatini, disregard the HIV test; you most likely have AIDS, according to the 96% probability I received. Which makes me think of the proverb: In Eswatini, you are the F — K itself, not just f — ked.

Where is Eswatini?

You may find the Jupyter Notebook for this project and many other funny codes on my GitHub.

The majority of this post is purely for entertainment purposes. Take nothing seriously. If anyone is upset, please let me know in the comments so I can change it. I use parody to inform the world. The world must help Africa.

Many thanks to King Mswati III of Eswatini and his 15 wives.

King Mswati III of Eswatini & Some of His Wives