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"Quality is never an accident. It is always the result of intelligent effort." - John Ruskin
Lesson Prerequisites
Lesson Prerequisites
This lesson assumes you have completed the Intro to Stata lesson.
0. Intro to Collecting High Quality Data
0. Intro to Collecting High Quality Data
In this lesson we will cover why high quality data is important and what can be done to ensure data is of high quality
- Why high quality data is important
Bad data can lead to bad results, which lead to misguided recommendations and ultimately bad policy!
2. What errors are we worried about
2. What errors are we worried about
We're worried about data that can make our results unreliable--either because they are noisy or biased
3. What leads to errors and how to mitigate errors in data collection
3. What leads to errors and how to mitigate errors in data collection
We can make our data vulnerable to error before, during and after data collection. Fortunately, there are strategies to reduce the likelihood of (or at least mitigate the consequences of) error at each stage
<-- One of the two top links to the left should work
<-- One of the two top links to the left should work
4. Example with data
4. Example with data
This dataset was downloaded on February 3rd 2016 after 3 days of data collection. Do we see any problems?
5. Conclusion
5. Conclusion
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