Data science is about putting theory into practice. Build up your hands-on skills in Statistics, Python, R, SQL, Tableau, Excel, Machine Learning, Deep Learning, and Time Series Analysis with our step-by-step, easy to understand tutorials and implement what you’ve learned in your future data science and analytics projects.
If you want to become a business intelligence analyst, a great way to start is to solve a business task in SQL. As the saying goes: “Knowledge that is not put into practice is like food that is not digested.” So, it’s time to get our hands dirty and start writing some...
If you have ever heard of statistics, you have probably heard the term ‘histogram’ as well. This is because visualizing data is a key concept in statistics. Whenever you need to visualize numerical data, you are likely to use a histogram. In this tutorial, we will teach you exactly...
In our previous tutorial, we learned how to create a calculated field in Tableau. Now, it's time to spend some time describing more ways to transform your source data and create custom fields in Tableau. Remember, you shouldn’t go too far with these, as Tableau’s main purpose is...
In our previous tutorial, we became familiar with the ARMA model. But did you know that we can expand the ARMA model to handle non-stationary data? Well, that’s exactly what we’re going to cover in this post - the intuition behind the ARIMA model, the notation that goes with...
A great term in the field of statistics, which you can add to your dictionary, is skewness. It is the most commonly used tool to measure asymmetry. However, in order to fully understand it, basic knowledge of the measures of central tendency is vital. Now, let’s focus on skewness. What is...
