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PhD Candidate in Applied Economics | Passionate about data | Research on climate change & extreme events policy | Amateur photographer & mountain lover

GIS for non-GIS people — Especially helpful for social-scientists who want to use georeferenced data

I came across something called “gridded rainfall data” exactly two years back while working on my dissertation, analyzing the socio-economic impacts of climate change. I was completely unfamiliar with the georeferenced spatial data before. I did not even know how to read those files, let alone analyzing them. All non-GIS folks who needed to use spatial data at one point in their life know what I am talking about!

After turning the internet upside down, I realized I needed to learn some basics about spatial data, so I took an online course on Coursera (I recommend taking any basic course…


When to use Zero inflated Poisson (ZIP) models and when not to use them

When the dependent variable is a count (a non-negative integer) variable, such as the number of items bought online, the number of children a couple has, etc., the Poisson model is used to predict the number of occurrences of the variable. It is the most basic count data model and assumes equality of conditional mean and variance. But this is a very strong assumption and often the data set is over-dispersed (the conditional mean and variance are not equal).

Over-dispersion can be caused by an excess number of zeros in the data. There are many real-world phenomena that almost never…

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