Book Image

CompTIA Data+: DAO-001 Certification Guide

By : Cameron Dodd
Book Image

CompTIA Data+: DAO-001 Certification Guide

By: Cameron Dodd

Overview of this book

The CompTIA Data+ certification exam not only helps validate a skill set required to enter one of the fastest-growing fields in the world, but also is starting to standardize the language and concepts within the field. However, there’s a lot of conflicting information and a lack of existing resources about the topics covered in this exam, and even professionals working in data analytics may need a study guide to help them pass on their first attempt. The CompTIA Data + (DAO-001) Certification Guide will give you a solid understanding of how to prepare, analyze, and report data for better insights. You’ll get an introduction to Data+ certification exam format to begin with, and then quickly dive into preparing data. You'll learn about collecting, cleaning, and processing data along with data wrangling and manipulation. As you progress, you’ll cover data analysis topics such as types of analysis, common techniques, hypothesis techniques, and statistical analysis, before tackling data reporting, common visualizations, and data governance. All the knowledge you've gained throughout the book will be tested with the mock tests that appear in the final chapters. By the end of this book, you’ll be ready to pass the Data+ exam with confidence and take the next step in your career.
Table of Contents (24 chapters)
Part 1: Preparing Data
Part 2: Analyzing Data
Part 3: Reporting Data
Part 4: Mock Exams


We covered a lot of information in this chapter. First, we talked about t-tests and how they are used to see whether there is a significant difference between two groups that use numeric variables. Then, we ran right into chi-square tests, and how they have two main types: chi-square goodness of fit and chi-square test for independence. A chi-square goodness of fit test sees whether a sample is a good representation of a population, while a chi-square test for independence compares two categorical variables to see whether there is a relationship between them. Next, we talked about correlation and how it can be used to see whether two numeric variables are related and how strongly they are related. Finally, we talked about simple linear regression and how it can be used to see whether one numeric variable can predict another. This wraps up everything you need to know about analyzing data for the exam.

In the next chapter, we will move on to reporting data!