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Filter search resultsData visualization checklist
Stephanie Evergreen (Evergreen Data) and Ann K.ResourceChoosing visual properties for successful visualizations
This whitepaper, by Noah Iliinsky, IBM Visualisation Expert, covers the various visual properties of data visualisation and how to appropriately apply them to various types of data.ResourcePresenting data effectively: Communicating your findings for maximum impact
This book, authored by Stephanie Evergreen, outlines a step-by-step process for enhancing the presentation of data in reports to increase its effectiveness.ResourceKnight lab - storytelling tools
This suite of tools is useful for creating highly interactive, beautiful representations of data.ResourceBig data visualization: review of the 20 best tools
This webpage provides a list of useful tools for visualising data sets for those with and without coding skills.ResourceDiscussion Paper: Innovations in Monitoring and Evaluation
This discussion paper produced by the United Nations Development Programme discusses various innovations that are occurring in M&E, and the advantages and disadvantages of these methods.ResourceWeek 30: Presenting data effectively
Last week I was lucky enough to be involved in a series of workshops by Stephanie Evergreen on presenting data effectively.BlogWeek 42: Dot plots, bullet charts, slopegraphs and more. We've updated our visualise data section!
Following up from Stephanie Evergreen's seminar on Presenting data effectivelyBlogThree ways to improve your DataViz
If you’re like me, you think you’ve got a pretty good handle on data visualisation – you know how to make basic customisations to graphs in Excel, you know you should probably think carefully about whether or not to put that large tablBlogIn search of Blue Marble Evaluators
You can't see the Earth as a globe unless you get at least twenty thousand miles away from it. On December 7, 1972, the first photograph was taken of the whole Earth from space. That photo became knownBlogRegression discontinuity
Regression Discontinuity Design (RDD) is a quasi-experimental evaluation option that measures the impact of an intervention, or treatment, by applying a treatment assignment mechanism based on a continuous eligibility index which is a variaMethodQuasi-experimental methods for impact evaluations
This video lecture, given by Dr Jyotsna Puri for the Asian Development Bank (ADB) and the International Initiative for Impact Evaluation (3ie), demonstrates how the use of quasi-experimental methods can circumvent the challenge of creatingResourceQuasi-experimental design and methods
This guide, written by Howard White and Shagun Sabarwal for UNICEF looks at the use of quasi-experimental design and methods in impact evaluation.ResourceUNICEF webinar: Quasi-experimental design and methods
What is the main difference between quasi-experiments and RCTs? How can I measure impact when establishing a control group is not an option?ResourceEvaluation reporting: A guide to help ensure use of evaluation findings
This guide addresses the issue of ensuring that evaluation findings are used by stakeholders.ResourceFrom narrative text to causal maps: QuIP analysis and visualisation
This paper focuses on analysing raw data to produce useful visual summaries, describing in detail the processes involved in a QuIP analysis.Resource