Quantitative Research

1. Quantitative Research

2. In this lesson, we will deepen our skills in quantitative research methods to: • Explain how survey tools can be used to evaluate your campaign’s impact. • Describe the value of sample size for your quantitative research and measurement of impact. • Define representative sampling and identify the key factors in bias.

3. Review of Research Questions and Research & Planning Timeline (15 Mins) Discovering Key Concepts Representative Sampling, Sampling Size and Design (1.5H) Reading and Group Workshop (1.5H) Revisiting Your Research Plan and Rubrics (1.5H) QUANTITATIVE RESEARCH SESSION OUTLINE

4. Research Planning Process

5. Conceptualization • (1) • Scope: • target population, or the group of people that you want to study with the survey. • Comparison Site

6. SURVEY SAMPLING • RANDOM SAMPLING • Define target population • Choose a sample frame • Stratified sampling • Research Design • (2)

8. What is Statistics? A method for collection and interpreting quantitative data • Collection: Data is collected the right way • Analyzing: Mathematical tools or models for interpreting data

11. Statistics and your Survey: Sampling • Usually impossible to interview everyone in your area (at most sites) so you take a sample • A sample is a subset of your TA that is used to represent the whole group. • If they represent the WHOLE group then…. • You want to select a representative sample

12. Why is ‘representative’ so Important?

13. What is representative?

14. What is the full spectrum?

15. The Normal Distribution

16. Who represents your Target Audience?

17. Designing your Survey: Representative Sampling *Representative: The survey is designed such that the frequencies (or percent types of people) sample reflect the true frequencies (or percent types) in the population • Age range • Gender • Employment • Socio-economic status

18. Representative sample step: Determine your sample scope Where do your target audience or audiences live?

19. Sampling and Campaign Decisions How many samples do I need to collect?

20. Confidence Interval: • reflects the range of numbers that reflect the ‘true value” Key Concepts

21. Confidence Level: tells you how sure you can be you that your sample is generally representative of your population. • NOTE: Don’t worry about this – just know that we use a 95% confidence level and it tells you how confident you are that your estimate (of knowledge e.g.) is accurate

22. Select your Sampling Strategy • Design a truly random sample • How many samples do I need to collect? • Sample Size Calculator: http://www.surveysystem.com/sscalc.htm • Population Size: ? • Confidence interval: 5% (Rare standard) • Confidence level: 95% (Rare standard)

23. How many samples do you need here?

24. Where can you go to collect your data? • Door to Door • Any Other Defined Place • Pre-Determined Location • Central Location • Data Collection • (3)

25. Sample Size Factors to consider • Determining your Sample Size • Confidence Intervals • Population Size • Sample Size Estimator

26. Tips for Data Management Here are some key tips for staying on top of quantitative data: • Create a plan • Create a data input process • Stay Organized • Write legibly, neatly, clearly • Document the choices • Get help

27. Back up your Data!

28. ADDING TO MY RESEARCH PLAN

29. ..\..\Research Plan Template_Phils2_10September2012.docx • SAMPLE CALCULATOR • www.surveysystem.com/sscalc.htm

31. Review Serena Research Plan Quantitative Data Collection ( page 6) – review the gold standard and make your own section in your research plan

32. In this lesson, we will deepen our skills in quantitative research methods to: • Explain how survey tools can be used to evaluate your campaign’s impact. • Describe the value of sample size for your quantitative research and measurement of impact. • Define representative sampling and identify the key factors in bias.