Actually not. This is not a text about you. But, as Gladwell puts it in Outliers, if you find yourself being that type of outlier, you’re quite lucky. And rare.
Actually not. This is not a text about you.
But, as Gladwell puts it in Outliers, if you find yourself being that type of outlier, you’re quite lucky. And rare.
According to Meriam-Webster, an outlier is:
“a statistical observation that is markedly different in value from the others of the sample”
But you’re not here for that, are you?
Let’s simply explain when a data point is considered an outlier, why that might happen, and what you can do about it.
Data science is omnipresent to advanced statistical and machine learning methods. For whatever length of time that there is data to analyse, the need to investigate is obvious.
Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.
If you’re interested in the exciting world of data science, but don’t know where to start, CRISP-DM Framework is here to help.
These statistical tests allow researchers to make inferences because they can show whether an observed pattern is due to intervention or chance. There is a wide range of statistical tests.
Explaining the working of the most common central methods like mean, median, mode and how it can help in dealing with our data.As we know to deal with our data has a number of steps like data extraction, data cleaning, handling missing data, exploratory data analysis, etc. and statistics play a very important role in many of these steps