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    • Ask the MEL Team
      Have a question about the lecture content or an idea posed in a discussion board? Submit it here. Answers to questions will be posted here so that everyone can share in the learning process.
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    • Ask the MEL Team 2017
      Have a question about the lecture content or an idea posed in a discussion board? Submit it here. Answers to questions will be posted here so that everyone can share in the learning process.
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    • Session 2 – Module 4
      You have been asked by officials from the Dunwith province to help determine how to spend their limited M&E resources. Officials are collaborating with NGO’s working to institute a sanitation marketing campaign. The organizations have limited time and money to understand the needs of people on the ground. They want to sample to get data on the needs of local villagers. Their biggest questions are whether to conduct probability or non-probability sampling and how to reduce the amount of bias in the data collected? How would you advise them? Do you need more information, if so, what do you need to know? (hint: you already know they have limited time and money)
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    • Session 2 – Module 5
      Module 5 contains a great deal of detailed information regarding statistical analysis. For statisticians or people who deal with numbers this information may be easy to follow. However, for many of us this information is complicated and difficult to understand. A major part of a successful project is making sure that the stakeholders, partners and communities understand how your work has long-term benefits. This involves presenting complicated statistical information to people who don’t understand statistical analysis. How do you convey research results so that the people who read your report and don’t know much about statistics will understand? Have you had an experience where your results were misunderstood because they were not presented in a manner that was easy to follow? How do you prevent this from happening in the future?
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    • Session 2 – Module 6
      This module describes balancing acts. For example, in terms of statistical power you want a sample size big enough that there is a good chance of getting significant results IF they exist. But not too big that there is an added cost without a benefit. You also have to consider that costs will increase with increasing sample size, but at a certain point you will not get much value in terms of a smaller confidence interval. There is an art to determining that point – the “optimal sample size”. How would you advise stakeholders on determining the “optimal sample size”? What resources would you need? How would you make your case? What if they disagree with your suggestions?
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