A look at the HIV Incidence per 1000 per country especially the African regions.

The following refers to the Club Soccer Predictions dataset that can be found here: https://data.fivethirtyeight.com/. I will refer to football rather than soccer from now on. I will attempt to see how I can use this data to make bets against the my local bookmakers. The main goal is to have a minimum profit margin of 20%, however I realize that my account may be restricted or closed if /when the bookmakers pick up that I have clear winning betting strategy. I live in Namibia and therefore have no access to betting exchanges such as Betfair or Matchbook.

How much bitcoin do you need to buy a house in Namibia? In this blog post I attempt to answer this question.

This is an update from the post made way back in September 2020 titled Bitcoin yearly lows.

When to buy? When to sell? I often have a look at bitcoin charts. The one I like the most is the rainbow chart from www.lookintobitcoin.com. The rainbow chart shows possible entry(buy) and exit(sell) points. This is by no means financial advice. Proceed with caution and never put in more than you are willing to lose. That said, we are all gamblers here. On we proceed 😁.

Showing how the bitcoin stock to flow strategy holds true.....with charts and tables off course.

In thus post we go though the Real-time Covid 19 Data dataset. We will attempt to see if there is a link between Covid-19 death rate and population density. We will 1st focus on Namibia and it's neighbouring countries. After that we will focus on Namibia vs the rest of the world. The data is up to 23 June 2021.

In this post we will cover a simple heart attack prediction model. There are many factors that lead to a heart attack. We will attempt to build a model on data collected containing factors that may lead to a heart attack. We will also do some predictions and measure the performance of the model.

We will take a dive into the complete IPL dataset that stretches from 2008 to 2020. We will attempt to answer questions regarding batsman strike rates, batsman vs bowler and boundary percentage of total runs during the powerplay . The methods used to derive the answers were groupings and pivot tables and visualized through charts and tables. For two of the three questions, the findings appeared congruent to anyone who is a cricket fan. The last question’s finding was however a surprise.

I see a lot of posts regarding USA's money printing on the subreddit r/Bitcoin. I wanted to see for myself if there is a correlation. The data I need would be bitcoins price in U$ and the M2 money supply of USA. M2 is a measure of the total money supply that includes all cash, checks and deposits.

This is part 2 of the "MovieLens" Dataset series(If I can even call it that). Here we are going to attempt to answer question 2 : What was the average top rated genres(Animation, Sci-fi of Horror) for all of the years in the dataset?

I recently enrolled in the Python for Data Science(UCSanDiegoX -DSE200x) course at edX. In the course I got to explore the "movielens" dataset which you can download here. In this post I am gonna attempt to answer two questions. What was the average top rated movies for the last 10 years? and What was the average top rated genres for all of the years in the dataset?

Crypto prices has risen significantly in the past 2 months so I decided to do a follow up post. This is based on a previous post of mine titled Bitcoin return on investment : 2 years.

In this post, we will include the NBA dataset. We will compare the samples means of our hockey players vs our basketball players. Then we will attempt to categorize a random sample to the hockey or the NBA data set. That means if we blindly draw one player from the two data sets, we can say from which data set that player came from. We can even tie a statistic to it.

Welcome to part 4 of this series. This will be a short one. We will focus on Chapter 8:The Central Limit Theorem. There are many technical definitions online for the central limit theorem, but Chalers Wheeler explains it simply in one sentence. “The core principle underlying the central limit theorem is that a large , properly drawnsample will resemble the population from which it is drawn”-Page 128.

Welcome to part 3 of this series. We will focus on Chapter 4:Correlation. Correlation measures the degree to which two variables are related to one another. When two variables are positively correlated, a change in variable A is associated with in a change in variable B in the same direction. When two variables are negatively correlated,a positive change in variable A is associated with a negative change in variable B or vice versa.

As promised in the previous post, I will show how the standard deviation is calculated for our hockey players’ height and weight. We should arrive at the below figures.

I re-read Naked Statistics by Charles Wheeler. This book has many practical examples so I decided to use some of those examples on other data. This may or may not be a start to a Naked Statistics series. If it is, then this will be part 1. All errors or omissions that you may encounter are my own and not the fault of the author of the book.

The data in this post will comprise of the average housing prices in Namibia, the price of gold and the price of bitcoin from 2015 to 2....

Bitcoin has a fixed supply of 21 million. This means that there will be only 21 million bitcoins mined (actually a bit lower than that)...e

The tweets posted from major party candidates for the 2019 Namibia Presidential Election looks interesting ...

People often ask me :"Is bitcoin is a worthwhile investment?". To which I always respond:"Yes, if you understand bitcoin...at least the ......

There has been a some posts flying around on the yearly low prices on bitcoin. I tried to find one for 2020. The the latest .......

I will use some of what I learned from chapter 2 of this book to create a prediction model. The model is going to be trained on the ..........

Most of us look at the daily confirmed cases of Covid-19 every day. What we see is that number increasing. While that is true, the daily confirmed cases...

In this post I am displaying a diamond predicting model using machine learning. We will use Python with sklean. This is an overview and not a tutorial.

Who is the best IPL team? Who has the best home winning record? Who performs the best in away games? We are going to answer all those .....