Comprehensive Quantitative Data Analysis Training is designed to:
- Be familiar with the different quantitative data types and methods
- Be able to choose an appropriate sampling strategy
- Understanding the fundamentals of data cleaning
- Be familiar with descriptive and inferential statistical techniques
- Be able to read quantitative outputs from correlation and regression outputs
- Be familiar with data visualization approaches

Also, please see the below additional Quantitative Methods and Analysis resource:
- A good description from a professor at University of Massachusetts School of Public Health on how to use Excel for Statistical Analysis: https://people.umass.edu/evagold/excel.html
- Dr. Stephanie Evergreen is an expert on data visualization and has authored several books on the subject. The link above is a link to her blog which contains some really good tips on data visualization: https://stephanieevergreen.com/blog/
- A good website for reference to specific SPSS commands: https://www.spss-tutorials.com/
- Website from UCLA for helpful examples on STATA, SPSS and other statistical software: https://stats.oarc.ucla.edu/
- A great resource for all topics related to MEL: https://usaidlearninglab.org/
- This report is a good example of how to incorporate descriptive analysis into a report: https://pdf.usaid.gov/pdf_docs/PA00MS3S.pdf
- This is a good blog post explaining sampling and has a simple sample calculator to determine a basic sample size: https://www.qualtrics.com/blog/calculating-sample-size/
- This is a more advanced sampling calculator by the U.S. National Institutes of Health: https://researchmethodsresources.nih.gov/Tools