Digital Mapping

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week9lecture1spatialdata.pptx

What’s coming up?

Tuesday April 2nd – Lab #9 is due (Social Explorer)  Tuesday and Thursday April 2nd and 4th – NO LECTURE (Conference Week)

You will be assigned an optional lab - we will use it to assign you extra points on the third part of the midterm.  Thursday April 11th – Lab #10 and Extra Credit Lab Due Tuesday April 16th - Lab #11 Due (Written Reflection) Thursday April 25th - Lab #12 and Take Home Exam Due by the end of Friday April 26th (Oral Presentation – Reflection)

If you are concerned about anything…

Please talk to me – we will figure it out!

Lab #8 due by Thursday… Let me show you…

Where have we been

Math Phobia

Cognitive Load Theory

Real World Problem Solving

Moving plus 1

Focus on Patterns and Relationships

Data collection – organization – Analysis/Presentation – Make Decisions

Summary Statistics – embody data process above

Mean – Measure of Central Tendency – One number that is most similar to the whole data set

Standard Deviation – Variance – are values close to the mean or far away

Where have we been?

The normal curve – tells us if individual values are normal

The normal curve also tells us intervals in which we can expect

68 percent of values to fall into (-1 and +1 SD)

95 percent of values to fall into (-2 and +2 SD)

99 percent of values to fall into (-3 and +3 SD)

Anything outside of 2 SD is an outlier

Outliers are very interesting and rare

They are very different from the average and ‘normal’

When 2 variables are related to each other they are Correlated

You should know a positive and negative correlation

Today

Spatial Analysis in a Fast Food Nation

What is spatial analysis?

How do we use maps to draw conclusion and make decisions?

But first… a dearth of quantitative literacy and why we might need it?

https://www.youtube.com/watch?v=90oc3MQwwS4

In the 80’s A & W introduces the third pounder to compete with McDonald’s Quarter Pounder.

Even though people prefer in blind taste tests prefer the 1/3rd pounder and it’s the same price, the burger isn’t selling.

A & W puts together focus groups to investigate further…

Quantitative Literacy????

"Why," they asked, "should we pay the same amount for a third of a pound of meat as we do for a quarter-pound of meat at McDonald's? You're overcharging us."

Focus Group Results

How we have and will use map in this class

Data Literacy (A & W)

Big Data – “extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions”

Identifying quantitative relationships

Identifying Trends and Patterns

Calculating basic statistics (attached to Latitude and Longitude)

Making maps (requires quantitative literacy)

What is all that?

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How to make sense of it all

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Math is a way of seeing…

Reductionism

“the practice of simplifying a complex idea, issue, condition, or the like, especially to the point of minimizing, obscuring, or distorting it.”

Like the transformation of scale of a map

Or Living

Data

Data = collected observations about the real world

Studying how things in the world behave so we can get what we want out of it

Higher Sales

Less Global Warming

Become Stronger

We collect data to make informed decisions – to manipulate the future towards a particular goal

What are spatial data?

Observations that have geographic information

Everything has a location (lat and lon from the geo reference system)

Different processes have different spatial patterns

Weather

Economy

Sports Fan Allegiance

What patterns appear and how do we interpret them?

Main themes of spatial analysis

Clustering/Distance

Size/Scale/Geographic Extent

Movement over time

How do we ‘look’ at spatial data…

Ignoring a lot – but gaining insights from simplification

And that’s ok! As long as we come back up for air…

Walmart Locations (markets share)

What data do you need to make this map?

How might you collect it?

How are data represented on this map?

What scale are we working at?

Spatial Analysis?

Clustering, Size, Movement?

What other maps would be useful if we wanted spatially analyze Walmart (could be anything)

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How are data represented for WF?

Which visualization is better?

Tell a story about these two maps?

Did they meet on Tinder?

What can we say about the location of WF?

Clustering? Scale?

Who would this information be valuable to?

What decisions would you make based on

Them?

Why do fast food locations cluster?

1854 Broad street Cholera Outbreak on Broad Street (London)

Cholera – Contracted through drinking infected water

Pre-Germ Theory (1860’s)

Location Analysis

Water pumps?

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Example: Dr. John Snow (1813-1858), a legendary figure in the history of public health, epidemiology and anesthesiology created one of the first uses of geographical analysis on a static map to solve a problem of stopping the spread of cholera through Soho, London, England.

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In and Out vs. McDonalds

Tobler's Law of Geography

“Everything is related to everything else, but near things are more related than distant things.”

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Movement (over time)

Types of Data – Chernobyl 86

Data is classified or put into types depending on what it can do and what kind of conclusions we can draw from it

identifying and Interpreting quantitative relationships

Numbers are just a way of expressing these relationships between things

How much radiation is in Chernoybl? (1,2,3,4,5 – Geiger Counter)

Do you have more or less radiation poison than me? (rank)

Is there radiation in this area (yes or no)

What color is the monitor (yellow)

We interpret data to make decisions! We read situations and act! Good vs. bad judgement

Temperature data (you read and analyze it like an expert)

What will I wear?

Umbrella

Plans for later?

Will I leave my bed?

First Assessment!

Is it Qualitative or Quantitative – helps us determine what we can do with data – how we approach it…

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