Simple linear regression is an important tool for understanding relationships between quantitative data, but it has its limitations. One obvious deficiency is the constraint of having only one independent variable, limiting models to one factor, such as the effect of the systematic risk of a stock on its expected returns. Real relationships are often much more […]
Tag: statistics
Statistical inference helps us understand the data, and hypothesis testing helps us understand if the data is different from another set of data. These techniques are important when exploring data sets, as they help guide our analysis. However, these techniques are not enough. Most times, we are looking to understand the relationship between two sets of […]
As a generalist consultant you are unlikely to need any statistics for day-to-day project work (there are specialists to call on for situations where it’s needed). The workaday numerical tool is Excel which, with the “Analysis Toolpak”, gives most consultants more than enough of what they need. However, you are likely to build a lot […]
Mark Twain, the fiction writer, first popularised the phrase “there are three kinds of lies: lies, damned lies and statistics”. Twain erroneously attributed the line to a British Prime Minister, who in fact, was never recorded saying any such thing. It’s fitting, given what I’m about to describe, that one of the best-known claims about […]