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datapolitan committed Dec 13, 2018
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# Group Exercise - [NYC Vision Zero](http://www1.nyc.gov/site/visionzero/index.page)
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## Task: Students practice developing key questions around an analytical task unrelated to NYC Parks to encourage broad participation and engagement
## Outcome: Students gain experience formulating and defining an analytical question to be explored in data not directly connected to the work they generally perform
## Format: Individual, small group, large group facilitated ideation, co-creation, and discussion
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+ Roughly 4,000 New Yorkers are seriously injured and more than 250 are killed each year in traffic crashes
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+ .red[What analytic questions would you want answered to reduce and eliminate traffic fatalities in NYC?]
![img-center-40](images/ideate_discuss_decide_horiz_crop.png)

???

## Task: Students practice developing key questions around an analytical task unrelated to NYC Parks to encourage broad participation and engagement
## Outcome: Students gain experience formulating and defining an analytical question to be explored in data not directly connected to the work they generally perform
## Format: Individual, small group, large group facilitated ideation, co-creation, and discussion
## Outline
+ Introduction of task
+ Individual ideation
+ Small group discussion
+ Large group discussion
## Topic
+ How do we reduce and eventually eliminate traffic fatalities in New York City (Vision Zero)?

+ At conclusion of exercise or during the break, facilitator attempts to develop key themes out of the ideation along the lines of [bundled ideas](http://www.designkit.org/methods/30)
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class:center,middle
# Wrap-Up
![img-center-100](images/imp_guide.png)

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+ Facilitator concludes the exercise soliciting questions and introduces the implementation guide at the back of their workbook
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class:center,middle
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# How to Create a Process Map
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+ Facilitator introduces the method for creating a process map. The language is still in flux. Find the language that is most authentic to your understanding that resonates with the students
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![img-right-30](images/ideate_discuss_decide_crop.png)
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# What did you notice about this process?
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+ Facilitator reflects on the exercise and what participants are taking away from the experience
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+ Knowing the problem and sequencing the steps can be harder than working with data
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+ Everyone has something to add, no matter how technical (or non-technical) they are

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# 6 Analytical Steps
![img-center-75](images/sixphases_1.jpg)

## .center[.green[**How did this fit with our map?**]]

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# 1. Problem Formulation
+ What question or need am I trying to answer?
+ What’s my organization’s mission and goals?
+ How can I best apply data to this task?

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# 2. Data Gathering/Preliminary Analysis
+ What data do I think I’m going to need?
+ What condition is it in?
+ Does it tell me what I need?
+ What other data might I need?
+ How much work do I need to put into the data?

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# 3. Data Cleaning
+ Make the data usable and compatible
+ Takes up the most amount of time
+ May require more sophisticated tools depending on the state and size of the data

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# 4. Hypothesis Testing
+ Am I getting the results I’d hoped for?
+ What other questions come up?

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# 5. Verification
+ Do my results make sense?
+ Did I make a simple mistake?
+ Check twice and you’ll sleep easier

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# 6. Visualization
+ “A picture is worth a thousand words”
+ Communicate results clearly and concisely
+ Help to better understand your data

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![img-center-90](images/sixphases_1.jpg)

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# Thinking About NYC Parks
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