# Lab Statistics & Math

## R You Ready? Using R for Statistical Tests

We’ve been slowly coaxing you along in our R tutorials. We’ve introduced what R is, gave you a basic tutorial into how to use R and also spent some time learning how to explore your data with R. By now you are probably itching to use R for more complicated analyses. To indulge you, I…

Read More## An Easy Way to Start Using R in Your Research: Exploratory Data Analysis

As you’ve probably kind of guessed from our previous articles Introducng R and the Basic R Tutorial, we think R programming language and R-studio are great tools for data analysis and figure production. And now we are about to prove it! So, you’ve collected some data and are pretty sure you know what statistical test…

Read More## You did a Co-IP…now what?

You spent the last few weeks tweaking your Co-immunoprecipitation conditions, testing different antibody/bead combinations, and sampling a panaply of solutions and FINALLY! You have your Co-immunoprecipitation (Co-IP) elution… Now what? Well, you have a few choices. It really all depends on what you need know about the proteins in your elution. Do you need to identify…

Read More## Let’s Talk About Stats: Getting the Most out of your Multiple Datasets with Post-hoc Testing

So you’ve performed a test such as an ANOVA and have found that there is statistical significance in your data (lucky you!), however you now want to know where that significance lies. When you are comparing multiple sets of data it might seem like a logical thought to simply perform an individual t-test between each…

Read More## Let’s Talk About Stats: Comparing Multiple Datasets

Last week I focused on the left-hand side of this diagram and talked about statistical tests for comparing only two datasets. Unfortunately, many experiments are more complicated and have three or more datasets. Different statistical tests are used for comparing multiple data sets. Today I will focus on the right side of the diagram and…

Read More## Let’s Talk About Stats: Comparing Two Sets of Data

There are so may statistical tests out there it can be difficult to determine which is the right test to use. Below is a simple diagram to help you quickly determine which test is right for you. Although this is by no means a comprehensive guide, it includes some of the most common tests and…

Read More## Let’s Talk About Stats: Understanding the Lingo

The first hurdle in learning about statistics is the language. It’s terrible to be reading about a particular statistical test and have to be looking up the meaning of every third word. The type of data you have, the number of measurements, the range of your data values and how your data cluster are all…

Read More## How to Deal With a Failed Experiment

Scientific success is often defined by how well your experiments progress and the results you produce. However, scientific research is driven by a curiosity about the unknown, and you cannot always be prepared for the unknown. Inevitably there will come a time when your experiments fail. In this article I give you some of the…

Read More## Beneath the Lab Coat Part 2: What is lurking under our readers’ lab coats?

Recently, we wrote an article highlighting the prevalence of science-themed tattoos among scientists, and the particular significance these tattoos have among those who choose to get them (https://bitesizebio.com/articles/beneath-the-lab-coat-why-do-scientists-get-inked/). As a follow-up, we reached out to our readers to collect images and stories about their unique, science-themed tattoos. Some of you were kind enough to share…

Read More## Internships During Graduate School: How to Start a Side Career Without Quitting Your Day Job

The clock strikes 10:00 pm, your thumb has a raging case of carpal tunnel syndrome, the trash is full of tubes containing unsuccessful PCR reactions, and you wonder…Is this really what I want to do with my life? How do you get your mojo back when you’re knee deep in research? One option to consider…

Read More## The Ten Lab Commandments: Or the Guide to a Happy Lab

I was lucky enough to do my PhD in an extremely friendly and well-organised lab. In my opinion, these two key traits are required for a successful research experience. This environment, while appearing effortless, was due in part to the hard work of the senior postdoc who kept the lab, and all of us, in…

Read More## A Guide for Solving Your Lab Math Problems

Math is an important part of lab life, from making solutions to calculating protein concentrations, and miscalculations can cause mayhem for your experiments. Therefore it is important that your math is right, or you could spend weeks trying to figure out what’s going wrong in your experiments. I was hopeless at remembering how to do…

Read More## Show Us Your Moves: Making an MSD Plot

In the previous article, I showed you how to interpret mean-squared displacement (MSD) and showed four easy things you can learn from an MSD graph at a quick glance. Now let’s turn from analyzing an MSD plot to making one. I am going to use the programming language R to generate simulated data and then…

Read More## How Does it Move? Interpreting Motion of an Object with the Mean-Squared Displacement

Stuff moves. It is useful to study how stuff moves, because motion analysis can tell us a lot about the object that is moving. For example, we can learn if an object’s motion is aimless, diffusive wandering, or directed towards some goal, free to explore the available environment, or restricted to a confined space. Studying…

Read More## An Easy Way to Start Using R in Your Research: Basic Tutorial

So now you’re convinced that R is the language for you, you’ve downloaded R-Studio (from http://www.rstudio.com/) and opened it, and. . .what the hell do you do now? Great question! I always find it easiest to learn by doing something, rather than just by seeing a list of possibilities, so here I’ll walk you through…

Read More## An Easy Way to Start Using R in Your Research – Introduction

Working with large datasets can be very frustrating and time consuming. If only there were more tools out there to simplify things without needing to invest a PhD’s worth of time to learn how to use them! I am here to tell you that there is a solution, and a free one at that. If…

Read More## BioNumbers: An Online Database of Useful Biological Numbers

Who wants to know how many cells are in a single colony of Escherichia coli? (3.39). Or the egg size of Drosophila melanogaster? (12.3 nL). Or how about the genomic mutation rate in Arabidopsis thaliana? (0.28 – 0.42 mutations per diploid genome per generation). Who am I kidding? Who wouldn’t want to know those numbers?!…

Read More## Statistics: A Good P-value is Not Enough

Like many scientists, I don’t consider myself a statistics expert. But I am determined to do things right in my science, and that includes statistics. In my experience, a lot of scientists who are “scared” of statistics fall into the trap of ignoring the existence of anything beyond a t-test. But using the right method…

Read More## Time for T: How to Use the Student’s T-test

To pull together our discussions so far on hypothesis testing and p-values, we will use the t distribution as an example to see how it all works. The t distribution (you may have heard it called Student’s t) is a probability distribution that looks like a bell-shaped curve (or normal distribution). If we sample repeatedly from…

Read More## Pseudoreplication: Don’t Fall For This Simple Statistical Mistake

Now we come to the third part of our trifecta; in the last two posts I have gone over p-values and how they determine significance in null hypothesis testing, and we talked about degrees of freedom and their effect on the p-value. Finally, we come to pseudoreplication: where it can all go terribly wrong. Replication…

Read More