Learning how to handle your data, how to enter them into the computer, and how to read them into R are among the most important topics you will need to master. R handles data in objects known as dataframes. A dataframe is an object with rows and columns (a bit like a matrix). The rows contain different observations from your study, or measurements from your experiment (these are sometimes called cases). The columns contain the values of different variables (these are often called fields). The values in the body of a matrix can only be numbers, but the values in the body of a dataframe can be numbers, but they could also be text (e.g. the names of factor levels for categorical variables, like male or female in a variable called gender), they could be calendar dates (e.g. 23/5/04), or they could be logical variables (TRUE or FALSE). Here is a spreadsheet in the form of a dataframe with seven variables, the leftmost of which comprises the row names, and other variables are numeric (Area, Slope, Soil pH and Worm Density), categorical (Field Name and Vegetation) or logical (Damp is either true = T or false = F).

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Perhaps the most important thing about analysing your own data properly is getting your dataframe absolutely right. The expectation is that you will have used a ...

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