When I was a PhD student I had a colleague who was about to finish her practical work in the lab and was gathering all of her data in order to write her papers and her PhD thesis. All of her analyzes were done in Excel. Because she knew that I was quite good in data analysis we discussed some of her analyzes and the conclusions she drew together with her hypotheses. Since her assays were pretty complex and time consuming she only had a few replicates. When we stepped through her calculations ins Excel I realized that she used the STDEV.P-Function in excel since it is the first STDEV-function in the list when yout type =STDEV into a cell. However, this was (and in practice is almost always) the wrong function to use and it gave her inccorect results and conclusions. Especially because she only had few replicates. By the way, Excel has two functions for the standard deviation, the STDEV.P and STDEV.S-function. The former one is only applicable if you know the entire population (which is rarley the case). You mostly need the STDEV.S-function in practice. As you can guess, the situation was very unfortunate and uncomfortable for her especially because she was about to finish her PhD soon.
I asked her if she knew the difference between the two types of standard deviations and she said she read the Excel help and thought she would be on the safe side. I have to admit the Excel help is not very helpful and sometimes even confusing. However, at the end you have to defend your your data and your project and you need to be comfortable and confident with data analysis.
So if you feel you have a bit of a lack of data analysis knowledge, you might think about joining our training ‘Data Analysis in Excel for Life Scientists’.
Among other things it will cover the following topics:
|Introduction||Why become familiar with data analysis?|
Learn how to perform different calculations (e. g. scalar and matrix calculations) in Excel
Learn other basics like integration, differentiation and how to use the Solver in Excel
|Data Exploration||Learn how to preprocess your data|
Learn how to effectively play around with your data
Learn how to create different statistical graphs and how to create publication-ready graphs
|Statistical Hypothesis Testing||Learn different statistical tests such as Student’s t-test, ANOVA, rank-based tests, testing for normality and equivalence testing|
How to interpret p-values
How to interpret error bars (especially confidence intervals)
|Regression Analysis||Regression analysis basics|
Linear regression and nonlinear regression using the Solver in Excel
Are you interested? Get a quote here: