By: Emiley J in data-science Tutorials on 2020-04-04
Goal->Describe a set of data: Commonly applied to census data,
Goal->Find relationships you dont know - discovering new connections, correlation doesn not imply causation
Goal->Use a relatively small sample of data to say something about a bigger population - common statistical model
eg. effect of air polution control on life expectency in US from analysing 545 counties
Goal->Use data on some objects to predict values for another object - x predicts y doesnot mean x causes y
eg. how target figured out teen girl was pregnant
Goal->To find out what happens to one variable when you make another variable change - usually randomized studies (gold standard for data analysis)
eg. Like a what-if analysis
Goal->Understand the exact changes in variables that lead to changes in other variables for individual objects - physical / engineering science
eg. Mechanistic - Empirical pavement design - fhwa.dot.gov
Data is the second most important thing in data science. the first most important is the question that you want to solve.
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