This app was developed by the Bioinformatics Core of Cancer Research Uk Cambridge Institute to accompany a training course. On the course webpage you will find lecture notes from the course and practical exercises that use this app Introduction to Statistical Analysis




View source Code for app

Data Import Parameters

Hypothesized Mean

You need to specify the Hypothesized (or population) mean that you intend to use in the statistical test
You can choose to transform the data prior to statistical testing

Display Parameters

You can use the algorithm in R to guess how many bins to use in the histogram
Otherwise, you can choose your own number of bins
The current value of the true mean is defined on the Data Input tab
The boxplot and histogram of the data are shown below
Numerical summary of the data...

            The red solid line on the histogram shows a normal distribtion. You should assess whether your data are approximately normally-distributed before proceeding with a t-test
            
Don't forget to check that the value of the Hypothesized mean is correct. You change this on the Data Input tab

One sample test


            

Report Parameters

R Script

You will be able to re-run this analysis in R by downloading the R code below We recommend RStudio to run the R code and compile a pdf or HTML report that will show the results of your analysis along with the code used
RStudio
The input file that you are analysing must be in your R working directory in order for the script to run In order to compile the report in RStudio, you will need to install the tidyverse package install.packages('tidyverse'))

Download R Script

Download R Markdown file