2.11 General Discussion for '17 - '18

What exactly would be a good answer the Getting Started question about making a visualization out of that table? You canâ€™t really put the quantitative data all on one chart, because the most common response is different for every age group. As in, a bar chart would just tell you that the percentage of teens who text is greater than the percentage of 19-65-year-olds who watch TV. Which isnâ€™t really the story of the data. How does one visualize the story of the data?

Hi @jasperlafortune! This is one of those â€śthinking promptsâ€ť where there is no one right answer. The Teaching Tip in the lesson provides some guidance. Hereâ€™s what it says:

"Please note: this data is completely fabricated and is only intended to serve the purposes of the warm up. It is intentionally slightly ambiguous. If students ask questions seeking clarification thatâ€™s a good sign, but you might have to simply respond: â€śWell, this is the data we haveâ€ť.

There are no right or wrong answers here as long as students attempt to represent the data in a different way somehow."

I would hope my students would say that this isnâ€™t great data to start with. If anything, I would think it is interesting about who they were able to ask or how they decided to break down the age groups in the way they did. I would also think we could talk about how â€śtalking with friendsâ€ť was the most popular for all ages, but not for any single age - that might mean that it was a close second in several of the categories.

Again, I read this as a â€śget students talking and thinking about dataâ€ť type of question - not necessarily a formative assessment on how well can students select a way to represent data in a story. I think this foreshadows the lesson for the day and perhaps increases student critical thinking skills on data and connects it back to the â€śbad data visualizationsâ€ť lesson. I could see someone taking this data and doing all sorts of terrible things with itâ€¦ hopefully this data gives students some empathy for people making data visualizations with less than ideal data.

Iâ€™m curious what your students come up with though!

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I didnâ€™t end up using that question. I felt it would be better suited to the lesson on Telling a Data Story, as the thinking we want students to do for that particular table seems to be â€śWhat story is this data telling?â€ť, rather than â€śHow could I visualize the story this data is telling?â€ť

But then, I frequently have to cut out elements of lessons because I have 3 hours/week instead of 5, so itâ€™s not a big deal. I brought it up here, not because I wanted the right answer, but because I wasnâ€™t even sure what a possible answer would be. If an exemplary answer is â€śHonestly, this is bad data to begin with,â€ť it would be helpful to communicate as much to teachers, maybe in the Teaching Tip?

I am working through the second half of unit 2 right now and just finished 2.11. I gave my students a data set that I found online about death rates by state and causes and asked them to investigate the data for any patterns/trends, create a data visualization and write a story about the data they are displaying. They are confused on the â€śstoryâ€ť. I just want to make sure that I am understanding this correctlyâ€¦
Their story should be about looking at the raw data for any patterns/trends (to find a pattern might involve creating different types of graphs with the data) that the data reveals.
I told them their story could not be â€śthe highest death rate for homicide was in D.C.â€ť That is just a fact from the data, not a storyâ€¦ right? Am I thinking about this correctly? I am having self doubt

They are having a very difficult time finding patterns/trends with datasets. Any suggestions to help explain?

They could make a story around that fact and give a plausible explanation about the facts.

When I did this, I asked students leading questions. In the movie database, some trends are more obvious than others. You can look at the examples in the lesson plan. In the scatter plot, the older viewers seem to be more generous with their rating and teens seem to be hard to please. If you look at the line chart with data broken down by gender, women seem to rate movies higher then men. Since you are using a different database for this lesson, you may want to look for patterns yourself and then start leading the students to seeing those patterns by giving them suitable prompts.