# Excel and Data Analytics

Written by Happy Rugbere · 1 min read

So, this will be a short but highly educative piece, so stay glued. I remember my first significant encounter with Microsoft Excel. Being techy, I learned that people could pay me to use computer software was a fantastic discovery. Working with Petrofac Engineering company in the United Kingdom, excel was used in production modeling. There was this Indian boy in the company that was an economist. We were doing simulations to understand how various production volumes would affect the revenue from the asset. I loved playing around with the model, checking responses to changes in different variables.

When oil price fell to \$30/bbl a couple of months later, I was called into a room full of my bosses to explain. I just flew open my laptop, showed them where we assumed \$110/bbl, and changed it to 50 dollars. The entire spreadsheet turned red immediately, executing the conditional formatting. While playing with these figures didn’t quite make a difference to the global oil price, it made me feel good.

Fast forward nine years later, I am seated in a Lagos Business School class listening to Dr. Bongo. Seeing this again brought back memories of when I felt like a data magician. We are presently learning probabilities of continuous and discrete variables. Dr. Bongo has a way to get you comfortable with numbers. I can say that the courses I am currently taking at LBS are actively affecting the way I view the world around me.

From Dr. Bongo’s lessons, I can see that probability has left the era of ‘if you flip a fair coin.’ Good predictions are used to build artificial intelligence models to pick the best decisions for entire countries automatically. Dr. Bongo ensures that you always think in numbers. While there are qualitative and quantitative data, quantitative (numbers) data tell a better story. My data analytics vocabulary is no way better. Things I have learned include:

• Probability Unions: This is gotten by simply adding all the data points in a data set without double counting
• Finding the intersect: The intersect is denoted with an inverted ‘u.’ It is part of the data set with data points from both variables present.
• Z value: This is the measure of the deviation from the mean
• Normal Distribution curve: Curve that is bell-shaped and shows the trend of a standard normal variable. The topmost part of the normal distribution curve (or center) is the mean.
• The almighty empirical rule: the rules states that 68%, 95%, and 99.5% of the data examined are 1,2, and 3 standard deviations from the mean.

Data analytics seems like one course that would immediately impact my business. I am excited about this and my journey through the school, the learning experience, and the people.

I will close this with the bit a number of you like the most, my glorious words of wisdom. So today is from Ryan Holiday:

“Like any good school, learning from failure is not free. The tuition is paid in discomfort or loss and having to start over.”

Signed: The Prince of Business

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## 2 Replies to “Excel and Data Analytics”

1. Joshua Adeyemi Oluwafemi says:

@Prince, I totally agree with you that “probability has left the era of ‘if you flip a fair coin.’ Good predictions are used to build artificial intelligence models to pick the best decisions for entire countries automatically”.
Data analytics is not just a course that we study only to pass-through LBS, it’s a decision tool and I am getting to understand it better.
Thank you

1. Thanks Joshua, I am glad to see that I am not the only one seeing it this way

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