Course Curriculum

7 Sections
00

Introduction

3 Lessons 19 min
  • Course Overview & Downloads 3 min
  • What Is Messy Data? 12 min
  • Common Types of UX Spreadsheet Data 4 min

Resources Provided

  • 0.1_CheatSheet_UX-Data-in-Spreadsheets (PDF)
  • 0.1_CheatSheet_UX-Data-in-Spreadsheets_Functions-and-Tools (PDF)
01

Top 3 Priorities While Cleaning Data

4 Lessons 23 min
  • Privacy and Security 5 min
  • Documentation: Why It's Important 7 min
  • Documentation: How to Document Effectively 5 min
  • Efficiency 6 min

Resources Provided

  • 1.2_Template_Documentation (Microsoft Excel)
  • 1.2_Template_Documentation (Google Sheets)
02

Missingness

6 Lessons 65 min
  • Missingness: Importance of Identifying 3 min
  • Missingness: Causes (Part 1) 5 min
  • Missingness: Causes (Part 2) 8 min
  • Missingness: How to Identify (Part 1) 6 min
  • Missingness: How to Identify (Part 2) 16 min
  • Missingness: Listwise Deletion 5 min

Practice Activities

  • Missingness (Instructions) 16 min
  • Missingness (Walkthrough) 6 min

Resources Provided

  • 2.5_DemonstrationData_Missingness (Microsoft Excel)
  • 2.5_DemonstrationData_Missingness (Google Sheets)
03

Duplicates

5 Lessons 61 min
  • Duplicates: Importance of Identifying 4 min
  • Duplicates: Causes 10 min
  • Duplicates: Key Variables 5 min
  • Duplicates: How to Identify 14 min
  • Duplicates: Deciding Which to Keep 8 min

Practice Activities

  • Duplicates (Instructions) 15 min
  • Duplicates (Walkthrough) 5 min

Resources Provided

  • 3.4_DemonstrationData_Duplicates (Microsoft Excel)
  • 3.4_DemonstrationData_Duplicates (Google Sheets)
04

Inconsistent Formatting

2 Lessons 18 min
  • Inconsistent Formatting: Common Issues 14 min
  • Inconsistent Formatting: Find and Replace 4 min

Resources Provided

  • 4.1_DemonstrationData_Inconsistent-Formatting-and-Fixing-Incorrect-Data-Types (Microsoft Excel)
  • 4.1_DemonstrationData_Inconsistent-Formatting-and-Fixing-Incorrect-Data-Types (Google Sheets)
05

Incorrect Data Types

1 Lesson 24 min
  • Fixing Incorrect Data Types 5 min

Practice Activities

  • Inconsistent Formatting & Incorrect Data Types (Instructions) 16 min
  • Inconsistent Formatting & Incorrect Data Types (Walkthrough) 3 min
06

Exploratory Data Analyses

7 Lessons 77 min
  • Why are Exploratory Data Analyses Important? 6 min
  • Descriptive Statistics (Part 1) 12 min
  • Descriptive Statistics (Part 2) 7 min
  • Pivot Tables 7 min
  • Basic Data Visualizations 11 min
  • When to Use Which Exploratory Data Analysis Method 12 min
  • Final Thoughts 1 min

Practice Activities

  • Exploratory Data Analysis (Instructions) 16 min
  • Exploratory Data Analysis (Walkthrough) 5 min

Resources Provided

  • 6.2_DemonstrationData_Exploratory-Data-Analysis_Spreadsheet-Functions (Microsoft Excel)
  • 6.2_DemonstrationData_Exploratory-Data-Analysis_Spreadsheet-Functions (Google Sheets)
  • 6.3_DemonstrationData_Exploratory-Data-Analysis_Quantitative-Usability-Testing-Data (Microsoft Excel)
  • 6.3_DemonstrationData_Exploratory-Data-Analysis_Quantitative-Usability-Testing-Data (Google Sheets)

Learning Outcomes

  • Use a systematic approach to data cleaning to prepare datasets for accurate and trustworthy analysis
  • Understand the top 3 priorities while data cleaning
  • Apply spreadsheet functions and tools to identify and address common data quality issues
  • Apply exploratory data analysis techniques to identify and assess data quality issues

Course Preview

 to watch NN/g videos

Tools Used in This Course

To complete activities in this course, you will need access to either Google Sheets or Microsoft Excel.

All other resources can be accessed through a standard PDF reader.

Turn Problems Into Solutions

Save time with high-efficiency data cleaning techniques

  • Apply functions and tools to identify and address common data quality issues, like formatting
  • Identify duplicate entries and select the most appropriate approach for handling them in different scenarios
  • Identify incorrect data types in a dataset and correct them for analysis

Protect data while cleaning it

  • Understand the importance of protecting participant data
  • Use proper techniques to create thorough data-cleaning documentation
  • Better protect participant data with consistency and accuracy

Evaluate and improve data quality

  • Select relevant descriptive statistics and data visualizations for identifying outliers
  • Identify missingness and apply the listwise deletion method appropriately
  • Select appropriate exploratory data analysis (EDA) methods based on dataset and research goals

What People Are Saying

  • This course gave me practical insights I can refer back to whenever quantitative research comes up, especially since I don’t have prior experience in this area. The presentation was lovely and engaging. It was also valuable to hear Rachel Banawa’s personal experiences and common pitfalls to avoid.

    Erika
    Researcher, Beta Participant

  • I thoroughly enjoyed this course. The instructor was engaging and was clearly passionate about the topic. She spoke clearly and used excellent examples to reinforce key concepts. I would highly recommend it.

    Paulina
    Principal Visual Designer, Beta Participant

  • This course was highly relevant to my day-to-day work. I was able to immediately apply what I learned. The instructor explained concepts in a clear, practical, and user-friendly way with no fluff. The downloadable resources were very helpful, and the activities were especially engaging.

    Ebun Omiwole
    Assistant Director, Beta Participant

Frequently Asked Questions

How long will I have access to this course?
Once purchased, your access will never expire. This ensures you can learn at your own pace and return to review content as often as you'd like, whenever you need.
Will I get personalized instructor feedback on course activities?
No, personalized feedback is not provided for activities completed during the course. Most courses provide answer keys to activities that help learners reflect on their progress and understanding of course materials and examples.
What content can I download?
You can download a variety of resources provided with each course, including templates, how-to guides, cheat sheets, posters, reading lists, and more. Video lessons provided in all courses will not be available for download.
Can I access this course offline or on a mobile device?
Offline access isn't available yet, although we plan to add it. Most courses offer downloadable resources for offline reference.

For the best experience, mobile devices are not recommended.
Is this course eligible for the NNGroup UX Certification Program?
Unfortunately, self-paced courses do not count toward UX Certification. However, learners who complete the final exam will receive a “Recognition of Completion” to demonstrate their achievement.

See our Live Online courses for options that count toward UX Certification.
What can I share with my employer to show I’ve completed the training?
Upon completing a course’s final assessment, you will receive a “Recognition of Completion” showcasing your dedication to learning the topic. This document can be shared with your employer or professional network to demonstrate your new skills and commitment to professional development.