From the course: 11 Useful Tips for Regression Analysis

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Include missing observations

Include missing observations

From the course: 11 Useful Tips for Regression Analysis

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Include missing observations

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- [Instructor] Missing data are everywhere. It's an unfortunate fact of life that most real world datasets, have missing values. Individuals refuse to state their income on household surveys. Ages are not reported. Firms do not state their profit and countries report missing GDP values. But it's missing data a bad thing? Yes, it is. The general assumption is always missing data in any dataset and any regression is a likely to be a problem. The severity of it depends on what assumptions we make about the missing data. There's a few assumptions, but we often assume that data is missing for a reason. Specifically, we assume that missing data is determined by other variables. These other variables might be in our dataset or they might not be. Either way doing nothing with this kind of missing data will lead to biased estimates. So what can we do about the missing data? Quite a lot. But the main choices normally…

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