Data management in life sciences, basic principles

N° Evaluation criteria Requirements 1 Know the basics of the R language The student is able to explain the following concepts: command, argument, script, object (type and class), working directory, packages. 2 Be familiar with the R studio interface The student writes his commands in a script. They use the interface to define their working directory. 3 Creating objects The student is able to create vectors, matrices and data frames. 4 Know the basic commands The student is able to use the cheatsheet commands. 5 Import a dataset from a file The student is able to import a dataset from a file taking into account the characteristics of the file: format, title, missing values. 6 Explore a dataset The student examines the dataset by checking for missing values, coding errors, outliers. He/she extracts the problematic values and corrects them. They will also check the format of the columns. 7 Describe the dataset To answer the question, the student summarises the dataset using summary parameters: mean, standard deviation, median, quartile, frequency, percentage. It applies them to a set of data with or without a second variable. 8 Making graphics To answer the question, the student is able to choose the right graphic representation. They will understand the arguments provided by the teacher to improve the aesthetics. 9 Exporting analysis results The student is able to export tables and figures. For the latter, the resolution and size will be defined.