Prerequisites: This course is designed for students who have taken or are taking Introduction to Epidemiology (MPBH 403) and Biostatistics I (MPBH 404 or 409).
This course introduces students to statistical computing. The emphasis is on manipulating data sets and basic statistical procedures such as t-tests, chi-square tests, and correlations. The course currently focuses on the use of SAS and STATA software packages.
Outcomes: Execute data management techniques to create public health analytical datasets (i.e., data importation from various sources, cleaning, validation, subsetting, merging, and transforming datasets); Construct clear and concise documentation of newly created datasets; Use SAS data-step programming, macros, and built-in procedures for statistical analysis and visualization (i.e., PROC MEANS, FREQ, SGPLOT, and UNIVARIATE); Demonstrate the ability to use descriptive techniques to summarize public health data (i.e., t-tests, chi-square tests, and basic regression models); Describe the results of basic statistical analyses.
This course introduces students to statistical computing. The emphasis is on manipulating data sets and basic statistical procedures such as t-tests, chi-square tests, and correlations. The course currently focuses on the use of SAS and STATA software packages.
Outcomes: Execute data management techniques to create public health analytical datasets (i.e., data importation from various sources, cleaning, validation, subsetting, merging, and transforming datasets); Construct clear and concise documentation of newly created datasets; Use SAS data-step programming, macros, and built-in procedures for statistical analysis and visualization (i.e., PROC MEANS, FREQ, SGPLOT, and UNIVARIATE); Demonstrate the ability to use descriptive techniques to summarize public health data (i.e., t-tests, chi-square tests, and basic regression models); Describe the results of basic statistical analyses.