Data Exploration

Statistics are needed not only to understand data science or machine learning but also to get a sense for the data. Irrespective of domain, statistics are necessary to understand the behavior of data in different situations. Learning more and more about your data is fun. You can find some critical insights that were previously undiscovered.

We can divide statistics into two parts: descriptive and inferential statistics.

Descriptive statistics are the summaries of information that was collected for analysis. These can be done using charts like histograms and pie charts, or with numbers such as the mean, variance, or correlation between data variables.

Inferential statistics observes the data by looking only at a set of points. For example, these statistics could deal with all the taxi drivers working in New York on the basis of the behavior of 100 random drivers’.