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During my summer internship, I closely observed how scientific models are combined with real-time data to generate tailored information for each farm to guide daily agricultural operations. I realize one big difference between the data science in industry settings and the work that we do in academics, is how this company’s science does not stop at the point when the model was proved to be working. Instead, the model is continuously being validated, updated, and improved for better performance in daily operations when new data or tools are coming in.

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It is the time of the year when you look back at the promises that you have been trying to keep but failed. An honest review of the year 2018 using data collected via Fitbit, web browsing time via Chrome, and self-logged time. Breakdown of awake time in an average day This time usage data is manually logged using an IOS app, for about three months during summer and fall.

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In my previous post, I talked about managing projects with Github and how crucial it is to make your work reproducible. While we craft our writings on paper to present the idea better, it is equally important to make our code readable for someone trying to understand the work. I listed here a few points on writing more explicit code, mostly from my own experience. Read more about good and bad R code style on Google’s R Style Guide.

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This post is inspired by Professor Mallory’s presentation on Reproducible Research Practices for Economists. See the presentation version that I gave at a lab meeting. Summary Introduced project management practices for file management and version controls. Principles for organized project management: keep raw data intact, use version controls, use progress management and save files in the relative path. Introductions to R, RStudio, R markdown, Github Steps to manage a project with RStudio and Github (added in Stata version)

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I spent the last week on a road trip and had many thoughts on what to write during those long driving hours. I decided to start with a writing plan. I allocate only about an hour to writing blog posts every day. It is likely that I will not finish writing these topics any time soon but let’s review it in October. Suggestions on related topics are welcome. An updating list:

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The number one reason for procrastinating is perhaps the task at hand is too hard to accomplish, and the mind would prefer more manageable tasks. Instead of writing up your result from the last set of regressions or editing the paper draft for one more time, your brain is easily satisfied at checking emails or grading homework. The small and manageable tasks make you look busy and bring you the sense of achievement when you cross them off your to-do list.

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I came across this article Daily Routine of a 4 Hour Programmer recently and was impressed by how the author manages to work only four hours a day and remain productive. This article makes me reflect on my productivity and time use, and how to keep a productive daily schedule by resting correctly. Instead of the 9-5 office schedule, the schedule of a Ph.D. student is quite flexible. The working hours, however, can be much longer.

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