Six types of Data Analysis you will do as a Data Scientist
Key Takeaways
The video discusses six types of data analysis that a Data Scientist may encounter, including descriptive, exploratory, inferential, predictive, causal, and mechanistic analysis, using statistical measures and data sampling to draw inferences and make predictions.
Full Transcript
six types of data analysis you will do as a data scientist one descriptive present a report of what has happened already it usually involves using basic measures of statistics to represent findings two exploratory open-ended exploration to check for patterns trends or relationships three inferential looking at a sample data set available to you and making inferences from it on the population in other words running experiments getting data and drawing inferences about the population for predictive predicting labels or things that may occur in the future based on signals from the past five causal identifying of a change in one factor leads to a change in other factors of the entire population and to what extent six mechanistic finding the underlying mechanism of the observed patterns trends or relationships trying to answer the how of the occurrence to be informed of more such videos please subscribe
Original Description
Data Scientists often have multiple hats to wear. One hat they wear sometimes is that of a Data Analyst. In this video, I briefly take you through the six types of data analysis you might encounter in your work as a Data Scientist. If you liked the video, please give it a thumbs up and don't forget to subscribe to the channel.
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