Data Collection and Analysis

Learn the fundamental activities in Data Science here, how to accurately collect and store your data, how to clean "dirty" data, and how to then query your data and analyze it in order to make sense of it. The Data Science landscape is constantly changing as the tools and software used to store and analyze data changes, so get up to speed with the resources in this section.

What is Data Collection and Analysis?

Collecting and analyzing data is a vital part of any research project. Without data, it would be difficult to determine whether a research hypothesis is true or false. Data can be collected through a variety of methods, such as surveys, interviews, experiments, or observations. Once collected, data must be analyzed in order to draw conclusions. There are a variety of statistical methods that can be used to analyze data, such as regression analysis or ANOVA.