Data Analysis Chapter 1: Introduction and Data Events

Study Notes

Data Analysis Overview

Data analysis involves studying and analyzing collected data to understand events, make predictions, and make informed decisions.

Types of Data

Data can be categorized into two types: categorical and numerical.
Categorical data is divided into nominal and ordinal values.
Nominal variables have no intrinsic order, while ordinal variables have a predetermined order.
Numerical data is divided into discrete and continuous values.
Discrete values can be counted and are distinct, while continuous values are produced by measurements and assume any value within a defined range.

Data Visualization

Data visualization is essential to understand data, individually and in the context of the entire dataset.
Various data visualization methods have been developed to transform information into figures, making it easier to understand.

The Data Analysis Process

Data analysis is a process consisting of several steps that transform raw data into data visualizations and predictions using a mathematical model.
The process involves a sequence of stages, each playing a key role in the subsequent ones.
The stages include:
Problem definition
Data extraction
Data preparation (data cleaning and transformation)
Data exploration and visualization
Predictive modeling
Model validation and testing
Deployment (visualization and interpretation of results, and deployment of the solution)

Description

Test your knowledge on recognizing problems during data analysis, converting events into data, and studying and analyzing collected data. This quiz is based on Chapter 1: An Introduction to Data Analysis.