We can look at our data in Prism as a table or we can look at our data and represent it as a graph. Therefore, we can carry out a parametric statistical analysis on these data. GraphPad Prism allows you to undertake normality tests and we've done a normality test on these data and you can see that all three groups, Control, Drug A and Drug B pass normality tests. These three data sets have equal end numbers and I want to undertake a one-way ANOVA to see whether these means are different.īefore you undertake any parametric statistical test, it is best advised to check that your data first fit within a Gaussian normal or bell shaped distribution. Group B contains drug A's data and Group C contains the data from an experiment using Drug B. Since I'm undertaking a one-way ANOVA and have three sets of data, I've entered my control data into Group A. For instance, if I was undertaking a T-test, I would enter Group A and Group B because a T-test only compares two sets of data.

You use the column format table, as you can see in front of us on the screen and you enter your groups into the individual columns. The way you enter data in Prism to undertake both T-tests and one-way ANOVA are the same. Probably the three most used statistical tests in biomedical science are the Student T-test or T-test, regression analysis and the analysis of variance, or ANOVA. In this short video I'm going to work through the steps required to undertake a one-way ANOVA in GraphPad Prism. Hello, my name is James Clark from King's College London. This video is part of the Essential Statistics series, presented by Dr James Clark, from the School of Cardiovascular Medicine and Sciences at King’s College London. Format and annotate a graph of your results.Select the parameters for your analysis.Correctly enter your data for a one-way ANOVA.This video walks you through the steps required to perform a one-way ANOVA, including what analysis choices and options you will have to make about your experiment to perform the analysis.

Graphpad prism anova post hoc