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# Getting Started with Data

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How to Simplify Apache Kafka. Get eBook.

A regular question I get asked is “What materials would you recommend for someone just getting started in a more data oriented job?” In this blog post I’m going to try to give a set of options, both books and websites, that will answer that question.

## Where Am I At?

I currently work as a conversion optimization specialist. What that means is I design/run/analyze feature experiments on web sites. The ultimate goal is usually centered around driving more, or larger, purchases. In working with other analysts, I’ve noticed a set of core skills that, when all are present, make the analyst one of my go-tos and that have led me to some success at what I do.

• Website: Github

• You’re gonna need to learn to code.
• Search for data, or statistics, or anything, and I bet you find sample code.
• Book: Think Stats

• Learn a little Python, learn a little stats. A great primer on using the two together.
• Might want to cover the statistics reading I’ve outlined first.
• Descriptive statistics
• Basic linear regression
• Establishing a “gut” for data
• Descriptive statistics
• Statistical tests (Binomial and t-tests at least)
• Confidence intervals
• Linear regression
• Web Article: How Not to Run an A/B Test

• Experiment design
• Dipping your toes into power analysis
• Book: The Flaw of Averages * Why the most prevalent descriptive statistic, the average, can be a terribly misleading golden hammer in search of a nail.

• Free Online Class: Probability & Statistics, Carnegie Mellon

• Probability (including Bayes theorem)
• Statistics
• Exploratory data analysis
• In depth treatment on linear regression.
• Tons of theory, but focused on learning to use statistical software to do the analysis.
• Best read after either taking a stats 101 class or learning more about classic statistical tests and how to use them correctly.
• Technology: R Studio * I have read several books on R, but none of them really helped me much. The best thing has been this program, as it’s made it simple to get data into R and viewable so I can focus on analyzing it.

This is a selection of books that I’m currently reading and learning from, but may or may not have gotten any results from yet.

• Textbook: Statistics: A Bayesian Perspective

• A very approachable introduction to Bayesian Stats. It is exceedingly less dense than some of the other material in this list.
• Also starts to get into multiply probability distributions, and is very helpful in visualizing them.
• Textbook: Doing Bayesian Data Analysis

• Once you’re done with the previous book, this one builds on it quite nicely.
• Gets down to actually computing more advanced Bayesian statistics problems, including hypothesis tests.
• Also fairly approachable, but I wouldn’t recommend it to an absolute novice.
• Textbook: Introduction to Bayesian Statistics

• Very dense. Currently making my way through this bit by bit.
• Nice to use after hitting the first book, and great in parallel with “Doing Bayesian Data Analysis."
• More mathematically focused, but still starts from the basics, so it’s definitely a book that you can use to slowly build up to a more rigorous exploration of Bayesian Statistics.

(Note: This article and the opinions expressed are solely my own and do not represent those of my employer.)

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