08/26/2020

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The following topics will be covered in this lecture:

- What is R and RStudio
- How to install packages and get help
- How to use R as a calculator
- Variables and data types

This course will lean heavily on programming;

- while it is possible to perform statistical analysis by hand for some very simple problems, any realistic problem solving must be done on a computer.

This course does not assume that you are already familiar with programming;

- this course will also not require a deep knowledge of programming or computer science.
- However, everyone is responsible to learn enough R to become proficient with standard modeling and plotting functions.

Students are recommended to use the lessons in Sofware Carpentry as a free reference for scientific programming in R.

- The first week of lectures will use the lesson R for Reproducible Scientific Analysis as a basis for the lessons.

- There are a number of common choices of programming/ scripting languages for performing statistical modelling, e.g.:
- SAS
- SPSS
- STATA
- Python
- R
- We will use R for the following reasons:
- it is free and open source software with extensive documentation and tutorials available;
- it has well established libraries for statistical modeling with a wide functionality;
- the “Faraway” package has extensive educational examples available for running our analyses;
- there are free interactive, introductory lessons from DataCamp which will be used for the first homework.