The house always wins. We all know this phrase. But this is more than a phrase. This is a simple, mathematically proven fact. And you’ll only have to know three statistical concepts to see why the house always wins.

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Photo by Kay on Unsplash

You are at the casino. The roulette wheel is spinning and the ball is bouncing. Bounce, bounce, bounce, you smile: “it’s red!” And then it bounces one more. No, it’s black! You lose everything again and go home with empty pockets.

Well, I hope you won’t — because you don’t go to casinos, you don’t buy scratch tickets, you don’t play the lottery or any gambling game in general.

Why? Because these games are designed to make you lose money.

And in this article I’ll tell you why. (Check out the podcast or video version of it, too!)

The house always wins. We all know this phrase. But this is more than a phrase. This is a simple, mathematically proven fact. And you’ll only have to know three statistical concepts to see why the house always wins. …

I’ve worked with over 500 aspiring data scientists in the last few years and I’ve seen some typical mindset mistakes they tend to make. In this article, I’d like to share five of these.

data science mindset mistkaes
data science mindset mistkaes
Photo by Lewis Ngugi on Unsplash

Getting stuck due to syntax issues

To do data science, sooner or later, you’ll need to learn how to code (mostly in Python, SQL, bash and/or R). And for everyone who’s new to coding, by far the biggest struggle is syntax.

I know that if you’ve never coded it might look intimidating.

But you have to understand one very important thing:

A computer is a powerful tool. It does automations and heavy calculations that we, humans, would never be able to. But a computer is not smart. So you have to tell it in a very meticulous way what you want to get done.

In programming, a single mistyped character, a line break, or a missing comma can cause an issue. You missed a space? Your script will break. This is how it is! …

Before I created my first-ever online video course, I spent hours and days researching the different cameras, microphones and software I needed. Eventually, I invested in my “starter kit,” which worked fine. But as I became more and more experienced with the course creation process, I realized that my initial set up wasn’t the best for me, so I changed and tweaked quite a few things.

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photo credit: | Nathan Dumlao

I was raised as a child who was expected to go to university. “If you don’t get a college degree, you won’t get a job.” I’m not sure anyone ever told me this exact sentence, but I remember that when I was 18 years old, I took this as a fact.

I was a good student. I got the best grades in high school and I got into the university I always wanted to get into. I know my parents were pretty proud of me — and I also know that they were pretty sad when I, four years later, decided to drop out. Why did I drop out? …

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photo credit: Alex Knight | Unsplash

I started 18 months ago. It’s a tech blog where I write entry level data science and analytics articles and tutorials for beginners. In February 2018 I reached a long-awaited milestone: 20,000 monthly visitors.

When I started my blog, I decided to be fully transparent with everything about it. This blog post is one of my first steps towards that. I’ll share every detail that I find interesting:

  • how did I get my first 100 and then my first 1,000 readers?
  • how much time does blogging take daily?
  • what’s my content and marketing strategy?
  • how did I do it on top of my full-time job?
  • how did I overcome the fact that I’m not a native English speaker?
  • how much money have I spent on the blog so far?
  • how much money have I earned with the blog so far? …

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Statistics is difficult. Of course it is, as it’s most of the actual science part in data science. But that doesn’t mean that you couldn’t learn it by yourself if you are smart and determined enough.

In this article, I am going to list 6 books that I recommend starting with if you want to learn statistics. The first three are lighter reads. These books are really good for setting your mind to think more numerically, mathematically and statistically. They also do a good job of presenting why statistics is exciting (it is!).

The second three books are more scientific — with formulas and Python or R codes. Don’t get intimidated though! Mathematics is like LEGO: if you build the small pieces up right, you won’t have trouble with the more complex parts either! …

Using various qualitative and quantitative methods to improve results is important anytime I do research. Previously I’ve described how I used the Online Research Framework to make improvements to websites and online products. Today I’ll show you a case study for a more particular situation: when you would like to sell a workshop.

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The Online Research Framework

The research methods

Conversion Rate Optimization (CRO) projects work best when you use quantitative and qualitative research methods together.

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I moved to Sweden 6 months ago with my girlfriend. It is a great country for expats like us, because almost everyone speaks really good English here. Even so, we would like to learn some Swedish, just to understand a bit more in daily conversation and about Swedish culture.

For me this is gonna be a hobby language, so I don’t want to put too much effort into it. Let’s say, I’d like to spend max 10–20 hours and my target is to understand 80% of daily chit-chat. Is it doable? We will see! …

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How can one get her first entry level job as a Data Scientist or a Data Analyst? If you scroll through data science forums, you will find many questions around this topic. Readers of my data science blog ( ask me the same from time to time. And I can tell you this a totally valid problem!

I have decided to summarize my answers for all the major questions!

NEW! I’ve created a comprehensive (free) online video course to help you get started with Data Science. Click here for more info: How to Become a Data Scientist.

One of the most unethical practices in business is using data to lie. Unfortunately, though, it’s not uncommon. I’ll show you three examples you might encounter quite often.

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My aim with this article is not to point fingers at anyone, but to encourage you to be more critical when you see headlines like “we increased our conversion rate by 1500% in 1 day.”

I see examples of lying with data way too often and as a data analyst it really hurts my feelings. Data is your best ally in finding the truth. When you use data to lie, it’s like saying to someone, “I swear this is the truth.” Then lying to her face.

#1 “We increased our subscription rate by 200%!”

This is my favorite one. I guess you’ve also seen different online solutions and services promoting themselves with testimonials…


Tomi Mester

Data analyst @Data36. I create in-depth, practical, true-to-life online tutorials — and video courses to help people learn Data Science.

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