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)
1
Part 1: Preparing Data
7
Part 2: Analyzing Data
13
Part 3: Reporting Data
19
Part 4: Mock Exams

Practice questions

Let’s try to practice the material in this chapter with a few example questions.

Questions

  1. Simon’s Grocery Store collects data on the number of sales of every vegetable it sells every day. If you wanted to see whether there is a statistically significant difference between the number of sales of pumpkins and the number of sales of summer squash, which analysis would be most appropriate?
    1. T-test
    2. Chi-square
    3. Correlation
    4. Simple linear regression
  2. Now, Simon’s Grocery Store groups cereal brands into Great Sellers and Poor Sellers based on sales performance in the past. It also notes the color of the box for each brand. The grocery store would like to know whether there is a relationship between the color of the box and whether the brand is a great seller or a poor seller. Which analysis would be most appropriate?
    1. T-test
    2. Chi-square
    3. Correlation
    4. Simple linear regression
  3. Simon’s Grocery Store collects data on every product it sells. Now...