A Simple Explanation for Understanding the Monty Hall Problem
This article aims to be a simple explanation of the Monty Hall problem. The Monty Hall problem is a famous thought experiment that when understood […]
Mine Your Business
Data Sciences. Simply explained. In plain English.
Time Series Analysis – A Gentle Introduction
Time series data contains a column of values (e.g sales, costs) and a column of even time intervals (eg. days or months). Time series analysis […]
Statistical Significance: About P-values and Confidence Intervals
A friend recently asked me what is a P-value. I have previously described P-values in presentations but his question prompted me to write a blog […]
Correlation: Necessary but not Sufficient for Causation
The statement “correlation does not imply causation” is well known and has become part of everyday language. The expression should more accurately be “correlation does […]
Bayesian Statistics – A Important Method Simply Explained
Bayesian statistics is an alternative to another form of statistics called frequentist statistics. Bayesian statistics can be a useful tool for situations in which frequentist […]
The Seahawks Superbowl Play: Understanding Probability
Permutations and combinations are important concepts to understand in order to estimate probability and make better decisions. Behind the Seahawks fateful Superbowl decision are permutations […]
Understanding False Positives and False Negatives
How effective are predictions? You may have come across some nerdy technical explanations of prediction effectiveness, such as mean squared error, accuracy, precision and recall. […]
Predicting Customer Churn is Like Predicting who will get the Flu
We all know that some of our customers churn out of our products. What if we could predict which customer is next most likely to […]
Q. How do I know if my data has signal? A. Look at a picture
Data analysis is a bit like mining for gold. In gold mining, sluice machines sift through tons of dirt before finding a few ounces of […]
