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ENG 102 Advanced Research Library Tutorial

What is data literacy and why should I care?

Data literacy is the ability to read, understand, create, and communicate data as information. It's a fundamental skill in today's data-driven world, empowering individuals to make informed decisions and draw meaningful insights from data in their personal and professional lives. Seeking and analyzing data can support decisions we make every day and the actions we take as individuals. You will likely include data in your college writing as evidence to support statements or claims. You need these skills to extrapolate and concisely communicate information derived from data.

Key components of data literacy include:

  • Reading data: This involves interpreting various forms of data, such as graphs, charts, tables, and reports, to understand what they are showing.
  • Working with data: This can involve collecting, cleaning, and organizing data to make it useful for analysis.
  • Analyzing data: This is the process of using various techniques to identify patterns, trends, and relationships within data and draw conclusions.
  • Communicating with data: This is the skill of effectively presenting data-based findings to others in a clear, concise, and compelling way, such as through storytelling, to provide concrete evidence. 
  • Reasoning with data: This is the ability to use data to inform decisions, solve problems, and think critically about the information presented.

Data literacy is not just for data scientists or analysts. It's a skill that is becoming increasingly important for everyone, from business leaders and employees to students and citizens, as data becomes more integrated into all aspects of life.

Using data and statistics as evidence in writing

As a student, incorporating data and statistics into your research requires you to find reliable sources for numbers to interpret and use as evidence to support your arguments and point of view. Citation of numbers is another important aspect of data literacy, as statistics may differ from one source to another due to collection methods, etc. (See the "Sources for Data and Statistics" box on the "Online Research: Sources and Pitfalls" section of this tutorial!)

When looking at data, also consider the following:

  • Who created the data? Is their purpose for collecting data clear?
  • Be careful about using data that could be collected or used out of context and use care with your methodology. Look at other data points, such as population numbers and percentages to make sure you are not using skewed data, or do your research laterally. 

For further reading: