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So once you've analyzed your data
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and it's time to start thinking about
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what you're gonna communicate to an audience,
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you have to figure out what you're gonna communicate.
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You have to actually look at your data
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and decide what's really in there
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that's gonna go in your story.
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And this is what we usually refer to
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as finding the true so what.
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What really matters?
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What is worth bubbling up to your audience?
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Now, most data stories,
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not because they should be,
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but just they end up being kind of boring,
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not very interesting,
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because the tendency is,
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"Hey, I did all this hard work.
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I investigated the data.
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Here's all the data."
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We just regurgitate everything
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we discovered to our audience,
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versus actually narrowing it down,
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focusing, filtering, to just the most important stuff.
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So our goal here is to definitely try to avoid that.
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We want to actually bubble up
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what is gonna really be compelling for our audiences.
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So, part of that is distinguishing
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between the interesting and the important.
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So you may find all kinds of interesting stuff
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in your data set.
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All kinds. It's truly interesting.
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It's really interesting, new,
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something you didn't know before,
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whatever the case may be.
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But is it actually important?
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You may discover something that may lead to another idea.
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The question is, is that other idea relevant,
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important, or is it just a distraction?
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It can be hard to distinguish between those two things.
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But generally, you know,
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if you really focus on the story you're trying to tell,
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the important things you know your audience needs.
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Remember the KWYs?
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You'll be able to recognize the difference
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between important stuff and just interesting stuff.
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Now, as part of that,
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you have to be certain.
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You have to look at it and ask yourself,
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"Does my audience really need this?
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Is this really important?"
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Which also, once again, isn't always quite so clear.
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You also may run into a situation
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where you come across data,
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and maybe you're looking at your data
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and you come across the same idea
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multiple times in the dataset.
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This is true here.
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It's true here.
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It's true here.
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It's true here.
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And listen, that may be really important to say,
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"Hey every way we looked at the data four times,
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we found the same story".
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That may be worth saying.
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Or, it may just be mildly interesting
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that you found something four times,
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but the most important thing is
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that you found that thing.
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Depends on who the audience is.
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So if you're telling a story about,
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let's say you're investigating cancer rates
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in a certain region,
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and no matter which way you slice it,
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you found high cancer rates in this region
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coming at it from 12 different directions.
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And you're speaking to an academic audience,
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proving an academic point about this research.
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You might say that you've found it 12 times.
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If you're telling an audience of
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like a general newspaper audience let's say, general public,
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maybe it's just important to say this thing happened.
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Not to talk about all the methodology
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and the 12 different ways.
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So different audience, different needs,
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different levels of importance,
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different emphasis on what's a true so what
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versus maybe just interesting.
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You also have to ask yourself, is it clear.
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And that's part of that same argument.
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So if I'm telling a general audience about
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I found these elevated cancer rates in this region,
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and I spend 20 minutes going down an rabbit hole
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of the 12 different ways I proved it,
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they're gonna get lost.
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It's not gonna be clear to them.
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Again, for an academic audience,
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it may be a different situation.
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Another question you would ask is,
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is there a story here?
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So I've figured out what's interesting versus important.
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I'm elevating the important stuff.
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But if I just throw a bunch of stuff at you,
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a bunch of facts, it's just a collection of facts.
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When you weave them in together into a narrative,
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which we're gonna talk about in the next module,
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it's much more impactful on your audience.
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So it is part of the true so what
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to recognize "Is this important?"
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Yes. "Is this relevant?"
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Yes. And "Does this fit into a narrative?"
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Now, it may be so important,
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that even though it does not
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fit into your overall narrative,
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you cannot avoid talking about it.
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Fine. So think about how you're gonna do that
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within the context of that narrative you're creating.
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At least at a minimum,
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say "Hey, here's the narrative I'm telling,
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telling, telling, telling a story, story, story.
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By the way, this has nothing to do with that,
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but this is really important.
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I'm gonna say it anyways."
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Do that. Just be aware that that's what you're doing.
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Just know that you have this other thing
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that's not part of your narrative.
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Or like I said before,
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if it's not part of the narrative,
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and the narrative is really focused,
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and it's not that level of importance,
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maybe it needs to be left out.
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Again, this is your decision based
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on your audience, what you're doing.
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But I want you to think about things like this.
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And then also you have to think about
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is it aligned with your questions.
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This is where we started.
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I'm asking questions of my data.
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I'm trying to discover something specific.
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Now maybe I discover something new
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that's not aligned with my questions,
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and maybe that takes over the entire project.
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Okay, that could happen.
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Maybe I'm gonna go off on a tangent
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that's more important than this original place.
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That's fine. But the point is, once again,
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how do you distinguish between important versus interesting?
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This is interesting, but does it aligned with my questions?
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Which is important?
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That's the key thing here today for me now.
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If it's not, maybe it's really not important.
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Maybe it's some just interesting.
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You also, by the way, as part of this process,
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can put your findings in rank order.
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There is no way,
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zero chance I'm gonna leave my data story
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without saying this one.
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This is the most important insight.
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Boy, if I miss this,
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I might as well just jump off a cliff.
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There's this one, there's this one,
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there's this one, there's this one.
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Once I get past this line,
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these are all nice to have insights
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I might share with my audience.
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By putting them in rank order,
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it makes it easier to do that.
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Certainly feel free to literally
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just put them in rank order.
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And above all,
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do all of this in the context of the KWYs.
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What is my data saying, obviously,
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what does my audience need from me,
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and what do I really want to say about it?
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Like I said earlier, the KWYs drive every decision, truly.
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You're looking at an insight.
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You're trying to decide
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is this important or interesting?
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Does this fit in my story
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or can I leave it on the cutting room floor?
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What are your KWYs?
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Well, my audience really needs to understand X.
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Does this have to do with X?
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Is this central to X?
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Yes. Okay. It goes in the story.
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Is this central to X, this one over here?
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Hmm. I mean, it's important.
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It's kind of interesting.
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Okay. Maybe not.
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I'll keep saying the same thing over and over again.
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I think you all get it.
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So we can move on.
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And the next thing I'm gonna talk about
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is an example of finding a so what.