The Introduction to EpiData, Epi Info, SPSS and Stata short course provides you with a comprehensive overview of data types and sources, the creation of datasets, analyses and data management using different statistical software packages – with specific reference to biomedical and health-related data. You will acquire the necessary skills to enter variable data formats, check for errors, create and transform variables, and analyse data for descriptive and analytical statistics. The course uses hands-on experience, group presentations and individual coaching with the aim of assisting you to collect and analyse data for research purposes and/or to complete a health-data analysis project.

At the end of this course, participants should be able to:
•  Introduce the concepts of data types, data sources, creation of datasets and data management,
•  Use different statistical packages SPSS, EPIDATA/EPINFO and STATA,
•  Introduce data collection form and entry using EPIDATA and EPINFO,
•  Create datasets, enter variables of different formats, enter data, check for errors, create variables, and transform variables. Using SPSS and STATA,
•  Analyze data for descriptive statistics using SPSS and STATA,
•  Analyze data for analytic statistics using SPSS and STATA

•  Type and sources of data
•  Data collection methods
•  Primary data collection methods
•  Secondary data and its use in Public Health research
•  Sources of Secondary data
•  Problems associated with using secondary data
•  Create data in SPSS
•  Create variables (numbers, string, dates)
•  Transform data
•  Label variables
•  Check for errors
•  Transform data from excel to SPSS/ STATA
•  Write a Syntax file
•  Frequencies
•  Creating Graphs
•  Simple data analysis:
•  Descriptive statistics
•  Analytic statistics

Using EPIDATA
1.  Create a QES, REC and CHK file from the paper copy of the research questionnaire for various types of variables.
2.  Set up checks for data cleaning while entering data.
3.  Set up the data files for double entry and validation.
4.  Document file structures, write codebooks, and export the data into a format suitable for STATA, SPSS or SAS for data analysis.