Analyzing the Data

At a glance

  • Youth Advisory Councils (YACs) need to understand the data they use.
  • There are pros and cons to using both types of data—qualitative and quantitative.
  • It's critical to know what data will be helpful when making decisions.

Determine where to focus attention

Bar graphs and pie charts inside a magnifying glass.
Understanding a topic is one thing. Knowing what data will be helpful when making decisions is critical.
  • Are you interested in a specific topic?
  • What about the topic interests you?
  • Here is an example:
    • Are you looking at data to help you understand what school-based mental health services are available in your district?
    • Would you like to understand the differences in services provided in your district's schools?
    • Do you want to know whether teens in your district need mental health training—such as how to identify and respond to mental health challenges among peers?

Determine what stories the data/facts reveal

Draw conclusions:

  • Whose experiences are focused on in the data?
  • Whose experiences are left out?
  • Do the data show that some students' needs are addressed differently from other students with different backgrounds?

Identify gaps in the data

Sometimes, you don't have the data you need to make decisions:

  • Is the problem you care about addressed in the available data?
  • If not, you may need to collect new data.
    • Work with experts to determine what data you need and how to best collect the data.

Determine the limitations of the dataset

Qualitative data focus on why the problem may exist and how it affects people.

  • These data are based on people's experiences and knowledge.
  • Open-ended surveys or interviews may offer less reliable evidence if they rely on the views of only a few people.

Quantitative data focus on numbers, helping you understand the scope of the problem.

  • These data rely on information gathered from many people.
  • These data give a big picture view of the problem in a large population.
  • You should pair both types of data when making decisions.