# Lab Statistics & Math

## Build A CV You Can Be Proud Of – Part III: Analytical Skills… Including the Dreaded Statistics!

In the previous article in this series, we covered teamwork and networking. Now it’s time to move on to what many people consider the most boring part of the lab work: the analysis. I know we all wish that a simple histogram or a rather nice-looking Western blot or PCR would suffice. But the fact…

## How Free is Your Degree?

In the last post I talked about p-values and how we define significance in null hypothesis testing. P-values are inherently linked to degrees of freedom; a lack of knowledge about degrees of freedom invariably leads to poor experimental design, mistaken statistical tests and awkward questions from peer reviewers or conference attendees. Even if you think…

## Don’t Be Another P-value Victim

In previous articles, I’ve primed you on hypothesis testing and how we are forced to choose between minimising either Type I or Type II errors. In the world of the null hypothesis fetish, the p-value (p) is the most revered number. It may also be the least understood. The p-value is the probability, assuming the…

## Types of Statistical Errors and What They Mean

This column is loaded with pop quizzes for you to test yourself on. If you haven’t already done so, catch up on yesterday’s piece on hypothesis testing for a refresher. Take a gander at the table below for a summary of the two types of error that can result from hypothesis testing. Type I Errors occur…

## A Primer on Statistical Hypotheses

Hypothesis testing is the foundation around which we prove our science is worth funding, publishing and sitting through a conference presentation for. I can’t overstate the  importance of understanding hypothesis testing, such is the integral part it plays in biological analyses. The Null Hypothesis Fundamental to statistics is the concept of a null hypothesis, and…

## Why You Should Care More About Statistics

In this, the first in a series of articles on statistics, I want to set out some of the main reasons why you, as a biologist, should improve your knowledge of statistics. The general consensus is that biologists are not strong when it comes to statistics. There’s nothing in our brains that stops us from…