index.Rmd

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title: "Design of Data Analysis"
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# About this Course {-}

The concept of reproducibility of a scientific investigation is most directly connected to the analysis of the data. Therefore, this course provides an overview of the structure of a data analysis and how to design an analysis to maximize the potential for reproducibility by research team members and by others. A key premise of this course is that reproducibility failure is often a consequence of poorly specified data analyses and a lack of understanding of the primary goal of the analysis by key stakeholders. The idea that “prevention is the best medicine” underlies this module, as proper design, structure, and execution of data analyses can prevent problems further downstream. We will therefore cover key analytic design concepts such as analytic iteration, analysis requirements and expectation setting, and unexpected outcomes and root causes. 

## Learning Objectives {-}

1. Implement the basic analytic cycle of the sense-making process: setting expectations about the data, comparing results to expectations, diagnosing unexpected outcomes, hypothesizing explanations and alternatives, and revising our understanding of the data.
2. Given a problem statement, characterize the stakeholders for a data analysis and what they hope to obtain/learn from the analysis
3. Write a high-level description of final/key/primary outputs and measures of uncertainty to be produced by the analysis
4. Develop a summary of key assumptions or constraints concerning inputs, data, or other factors.
5. Develop a set of requirements/expectations for the analysis regarding the outputs
6. Identify key analytic and data processing choices in an analysis that may significantly affect outputs
7. Identify any unexpected outcomes for a given analysis plan
8. Apply techniques for identifying root causes of any unexpected outcomes produced by the analysis 


## Available course formats {-}

This course is available in multiple formats which allows you to take it in the way that best suites your needs. You can take it for certificate which can be for free or fee.

- The material for this course can be viewed without login requirement on this [Bookdown website](http://hutchdatascience.org/Design_of_Data_Analysis/). This format might be most appropriate for you if you rely on screen-reader technology.
- Our courses are open source, you can find the [source material for this course on GitHub](https://github.com/fhdsl/Design_of_Data_Analysis/).