 Data Analysis
video

# What is Data Analysis?

Module 1

Module Structure

3 Lessons

This field got its start with capturing and counting census and other demographic data. Later, people figured out that there are better ways of the presentation of information and started tabulating the data.Then using probabilities, early statisticians estimated the population of cities to plan for the future.As mathematics advanced, various theories of distribution were formed. One of the most well-known -- and popular still -- theorems is the Bayes law.Later, statistics as a field really took off. Various sampling methods, least squares methods and hypothesis testing followed soon.

These are the main types of analyses: descriptive analysis, inferential, exploratory and visual analysis.Descriptive: summary of data and quick look into the data. Some common measures are: range, mean, mode, standard deviationInferential: estimates properties of underlying distribution of the data. Some common tools in this type of analysis: random sampling, hypothesis testing, confidence intervalsExploratory: helps us uncover insights and visualize statistical properties. Some common techniques are: steam and leaf, box-plots, histograms.Visual: builds upon exploratory analysis. Some common visualizations are: bar charts, part-to-whole charts, correlations, and geographic.

Methods of analysis