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Week 1 von Mind Map: Week 1

1. Concepts and ideas

1.1. Replicate your results by different people

1.1.1. Cannot be replicated due to: No time No money Unique

1.1.2. Make code available to everyone

1.2. Validation of data analysis

1.3. Research pipeline

1.3.1. Article Author goes left to right Reader goes right to left

1.4. What needed

1.4.1. Data should be available

1.4.2. Avilable code

1.4.3. Documentation of code and data

1.4.4. Standard ways of distribution

1.5. Players

1.5.1. Author

1.5.2. Readers

1.6. Literate Programming

1.6.1. Article Text Code

1.6.2. Presentation code

1.6.3. General concept Documentation language Programming language

1.6.4. Types Sweave uses Latex Lacks features: caching, multiple plots Not well udapted knitr uses R

2. Scripting your analysis

2.1. Script everything

3. Structure of data analysis

3.1. Steps

3.1.1. Define a question Narrow as much as possible This helps remove the noise of other data

3.1.2. Define ideal data set May depend on your goal Descriptive Exploratory Inferential Predictive Causal Mechanistic

3.1.3. What data you can access Free on the web Buy data Might need to generate it

3.1.4. Obtain data Try to get raw data If got from web: record url and time accessed

3.1.5. Clean data if it preprocessed already, understand how understand souce of data determine if data is good enough quit change data

3.1.6. Exploratory data analysis

3.1.7. Statistical prediction/modeling Get the value of uncertancy

3.1.8. Interpret results Use apropriate language Give explanation Interpret the results

3.1.9. Challenge results All steps Measures of uncertanty Think of potential alternatives

3.1.10. Synthesize/write up results Lead with questions Don't include analysis if can pretty figures

3.1.11. Create reproducible code

4. Organizing analysis

4.1. Data

4.1.1. Raw data If downloaded from web - add date in README

4.1.2. Processed data Should be named so it is easy to understand which script generated the data

4.2. Figures

4.2.1. Exploratory figures

4.2.2. Final figures

4.3. R code

4.3.1. Raw / unused scripts

4.3.2. Finl scripts

4.3.3. R markdown files

4.4. Text

4.4.1. README Should contain step-by-step instructions for analysis

4.4.2. Article Title Intro Used methods results Conclusions