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.

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.

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.

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.