2. Evidence-Informed Policy Making
Module 3
Assessing Evidence
[DATE & LOCATION HERE]

3. What will be covered in this module?
TOPIC 1
An approach to critically assessing evidence
TOPIC 2
Assessing evidence products
TOPIC 3
Understanding research design

4. Sampling and inferencing in research

5. The Law of Large Numbers
LLN "guarantees" stable long-term results for averages of some random events.
E.g. you want know the average height of a group of 100 people. If you randomly choose one person, and measure his/her height, your estimate could be very far away from the population average.
However, if you randomly pick 25 people and measure their height, you will get very close to the true value in the population.
Important to remember that LLN only applies when a large number of observations are considered.

6. Source: Authors based on (Newman, Fisher, & Shaxson, 2012)
“Evidence-informed policy is that which has considered a broad range of research evidence; it considers other factors such as political realities and public debates. It is not exclusively based on research. In some cases, research evidence may be considered and rejected.”

7. Further Resources
‘Is your Evidence Robust Enough? Questions for Policymakers’ (Louise Shaxson, Policy Press 2005)
Assessing the Strength of Evidence: A How To Note, DfID
Africa Check it is an award winning fact checking website
CLEAR- Regional Centres for Learning, Evaluation and Results strengthening capacities and systems for monitoring and evaluation (M&E) and performance management (PM), to guide evidence-based development decisions
Systematic reviews and impact evaluations for international development topics from 3ie:
A critical view of systematic reviews for development policy