The right data for the job
Imagine that different types of data are different people that you are interviewing for a job. The job is to answer a specific research question. You want to know what their qualifications are—will they do a good job? Are their strengths a good match for the task? Like we’ve mentioned before, if there are issues with the underlying data, then there will be issues with the results. It’s important to consider if the data collected make sense for the question that was asked.  Today, the data “qualifications” we’ll be looking at are what kind of data were collected and how the...

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Correlation doesn’t equal causation (but it does equal a lot of other things)
Correlation ≠ causation Data are pieces of information, like the number of books checked out at the library or reference questions asked. Those pieces of information are simply points on a chart or numbers in a spreadsheet until someone interprets their meaning. People create charts and graphs so that we can visualize that meaning more easily. However, sometimes the visualization misleads us and we come to the wrong conclusions. Such is the case when we confuse correlation (a statistical measurement of how two variables move in relation to each other) with causation (a cause-and-effect relationship). In other words, we assume one...

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What’s typical and why does it matter?
Average is one of those statistics that comes up a lot. What does it mean? How can we use it? What are its limitations? Today we’re going to talk about both the average, also known as the mean, and another statistic called the median. Means and medians are both ways to find out what’s typical and to compare multiple things. It’s easier to understand what these two statistics tell us when you know how they are calculated. Don’t worry if you don’t think of yourself as a “math person.” We’re only going to use addition and division.  What is it? Let’s do the...

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Do the Data Have an Alibi?
It’s hard to know who you can trust out there. “Fake news” is now a prevalent concept in society and the internet makes it possible for anyone to publish—well, anything. As library professionals, you’ve probably already acquired a great deal of experience determining the credibility of sources. Many of the same skills are needed to evaluate the credibility of data. So amid the bombardment of new (sometimes conflicting) data out there, here are some questions to ask when verifying sources and checking for bias. Although not fool-proof, these strategies can help you avoid misleading information and false claims. Let’s establish something...

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Habits of Mind for Working with Data
Welcome back! We’re excited to have you with us on this data journey. To work with data, it helps to understand specific concepts—what is per capita, what is an average, how to investigate sources. These are all valuable skills and knowledge that help you navigate and understand data. What you may not realize is that the mindset you use to approach data is just as important. That’s what this post is about: how to work with data and not melt your brain. I have melted my brain many times, and it can happen no matter how great your hard skills...

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Measuring Social and Emotional Learning Competencies in a Summer Learning Program
By on April 23, 2020 in School
  Denver Public Library (DPL), in collaboration with Library Research Service (LRS), was recently featured in School Library Journal. The article highlights DPL’s evaluation of their summer learning program and use of data to inform programmatic decision making. Below is a summary of the results. To learn more about their data collection methods, analysis, and application of findings, you can read the full article here. Denver Public Library (DPL) knew anecdotally they were positively affecting the social and emotion learning (SEL) of their youngest patrons, but needed to find a way to measure it. So in 2017, when they began shifting from...

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