This course will provide additional training in R and introduce students to the programming environment Python, and
train them in how to use functions/packages to manipulate and statistically analyze data. Students who take this course will
learn to:
1. Identify and use standard variable types;
2. Write expressions with appropriate syntax;
3. Input and output data in various formats;
4. Conduct common statistical analyses using standard functions;
5. Produce statistical graphics;
6. Find and use appropriate libraries and modules;
7. Know key libraries and modules;
8. Use vectorized calculations;
9. Efficiently manipulate data types and objects;
10. Write functions;
11. Identify appropriate situations for applications of for loops and while loops and be able to implement them;
12. Identify appropriate situations for applications of if-then and other decision statements and be able to implement them;
13. Access a database from SQL;
14. Implement SQL procedures and understand their usage;
15. Run SQL queries;
16. Create an SQL database from existing files;
17. Use nested statements appropriately;
18. Write programs to implement more complex data analysis and data manipulation;
19. Know the pros and cons of each language relative to each other and other programming languages; and
20. Know the proper use of the output from statistical software to communicate the results of statistical analyses through oral and written means.

Students will demonstrate competence through individual or group programming projects, labs, and examinations throughout the course.

Course topics include:
Data input/output
Data formats and types
Data management
Basic procedures, functions for statistical modeling, inference, and statistical graphics
Introduction to algorithms, flow control, conditional execution, and program design
Accessing data using SQL
Writing programs for more complex data manipulation and analysis