Course Description
Programming techniques in modern statistical software, including SAS and R for students with some experience with computer programming. Topics include data input/output; data formats and types; data management; flow control, conditional execution, and program design; statistical graphics and exploratory data analysis; basic procedures, and functions for statistical modeling and inference.
Additional Requirements for Graduate Students:
Additional and/or alternative problems of a more challenging
nature will be required for graduate students on homework
assignments and exams.
Athena Title
Statistical Software Program
Equivalent Courses
Not open to students with credit in STAT 4360E or STAT 6360E
Undergraduate Prerequisite
CSCI 1301-1301L and (STAT 4220 or STAT 4230/6230)
Graduate Prerequisite
STAT 6220 or STAT 4230/6230 or STAT 6320 or STAT 6420 or STAT 8200 or permission of department
Semester Course Offered
Offered spring and summer
Grading System
A - F (Traditional)
Course Objectives
This course will introduce students to important modern statistical software packages, including SAS and R, and train them in how to use these packages to manipulate and statistically analyze data. Students who take this course will learn how to get data into and out of statistical software packages. They will learn the various data types, formats and modes used in statistical software and will learn how to manipulate data structures such as SAS datasets and R data frames ,including sorting, merging, transposing, assigning, and generating data. They will learn statistical programming techniques in modern software, including flow control, conditional execution, R functions, and SAS macros. Students will be introduced to basic statistical graphics and methods of exploratory data analysis and how to implement them. Students will learn software tools such as SAS procedures and R functions to implement basic methods of statistical inference and modeling. More broadly, students will learn the appropriate role of statistical software in conducting statistical analyses and the proper use of output from statistical software to communicate the results of statistical analyses through oral and written means.
Topical Outline
Course topics include data input/output; data formats and types; data management; flow control, conditional execution and program design; statistical graphics and exploratory data analysis; basic procedures and functions for statistical modeling and inference; communicating the results of statistical analyses using statistical software and its output. Software-specific topics may include SAS data frames; SAS functions and commands; select SAS procedures for data management and statistical analysis; the SAS macros language; the SAS output delivery system; R objects such as data frames, matrices, vectors, their modes and how to manipulate them; R functions and how to write them; R packages; using R for statistical graphics and data analysis. At the instructor’s discretion, statistical software packages other than SAS and R may also be considered.
Syllabus