The winners of the 2021 Ig Nobel Prize are announced today. One of them caught my attention, which happens to be in the Economics category by Pavlo Blavatskyy for for discovering that the obesity of a country’s politicians may be a good indicator of that country’s corruption. Very interesting indeed and although it made me […]
Tag: analytics
Raw Data to Machine Learning to Decision-Tree: step-by-step
We have data on consumer loans and consumers’ basic info such as income, credit score, and status of the loans. What the loaner wants to know the risk of loaning to specific categories of consumers. Actuaries do this all the time, and while I’m not and never desire to be one, I find that the […]
Did your promotion work?
In an earlier blog How Well Are Your Incentives Working? I shared methods on how to calculate the various chances of success based on some campaign data (e.g. new sign-ups for membership) from various trials using Binomial distribution. In this post, I show how to determine if events occurred due to random chance or affected […]
Waffle Charts (3 methods + bonus)
You may heard of “waffle” charts. They’re usually depicted with little blocks in a larger area to give an easy view of proportions. The idea is not any different from a pie chart, or an area chart, or even a treemap…it all depends on your audience and preference. However, it’s suitable for small number of […]
Counting words/elements correctly in Excel
In some of my previous posts, you’ve already seen my Python examples on how to count words accurately in a document or in blocks of text (search for: Wordcloud). It’s also possible to count the words in Excel, but we have some gotchas there to be aware of. In this blog, I demonstrate some of […]
Putting together our Presidents (Infographic in Excel)
In several of my earlier blogs, I demonstrated working with raw data from multiple sources to generate visual and statistical analysis. You can find them in the following posts: Let’s Play With All The Presidents (Excel)-Part1 Let’s Play With All The Presidents (Excel)-Part2 Getting To Know Our Presidents In this blog, I share the combined […]
When you’re going “blank”! (Excel, Python)
You have data (of course, you do) and you have data that have something missing (of course, you do). The question is multi-fold around that…do we ignore the data, do we remove them from your analysis, or do we interpolate to fill in the missing data? And if so, what type of interpolation is best? […]
Word Cloud III – Python & Excel together
In two my earlier blogs, I shared two methods & codes in Excel and Python on how to create Word Clouds from any text or document. You can find them here: How To Find The Most Occurring Words In A Document? (python) and Creating Word Cloud Accurately And Easily In Excel (Excel) Now, I’ll turn […]
Be the right kind of ‘Mean’
No, I’m not talking about stingy, spiteful kind…rather mathematical mean: arithmetic and statistical means to be exact. In fact, a handful of mean functions and applications. In most common situations, when we say ‘Mean’ even the statisticians mean the Average…or the arithmetic mean we all know since early childhood. We continue use it because while […]
Understanding Step Charts (and creating them in Excel)
This is an example of a Step chart: And this is a line chart of exactly the same dataset. The dataset is of daily sales amounts in a fictitious salon. Which are shown below: Which chart makes more sense intuitively? The Step chart shows exact ups and downs and exactly when they occur clearly. It […]