The first step is getting the data ready for analysis. The survey was administered online and the program used generated column headers using the questions asked. Start by giving each column a simple variable name: blood, height, sex, weight, eye. Then examine the data for potential issues. Students were instructed to enter numerical values in a specific format, which they did not all follow to the letter. Because the data were collected anonymously, there is no way to investigate these problematic values (although some errors are easy enough to correct).There are several approaches to finding problematic data. Some statistical software will let you use conditional formatting to highlight values you deem too large or too small to be realistic. Plotting the data also helps find outliers that are obvious errors. Write a short summary of the problems you noticed and how you addressed them. Be specific about how you handled any changes to the raw data- the reader needs to be able to replicate your decisions