Business statistics

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Lab 2 Guide: Visualizing Data

This week’s lab is designed to give you an introduction to visualizing data in creative and intellectually rewarding ways.

Complete the following steps for this week’s lab. 

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1. Read Intro Essay for TED Studies Statistics: Visualizing Data.

2. Watch Modules 1-6

a. These TEDTalks are pretty cool examples of creative uses of data.

3. Read Putting It Together: Summary Essay

a. Complete activities 1, 2, 3, and 6.

b. Respond to the activity questions in your lab report. Make your responses brief but clear. Use the Lab 2 Report 

Lab 2 Guide: Visualizing Data

This week’s lab is designed to give you an introduction to visualizing data in creative and intellectually rewarding ways.

Complete the following steps for this week’s lab.

1. Read Intro Essay for TED Studies Statistics: Visualizing Data.

2. Watch Modules 1-6.

a. These TEDTalks are pretty cool examples of creative uses of data.

3. Read Putting It Together: Summary Essay

a. Complete activities 1, 2, 3, and 6.

b. Respond to the activity questions in your lab report. Make your responses brief but clear. Use the

Lab 2 Report Template

.

2-Watch Modules 1-6.

The beauty of data visualization – David McCandless

The best stats you’ve ever seen | Hans Rosling

Nathalie Miebach: Art made of storms

Chris Jordan: Turning powerful stats into art

Blaise Aguera y Arcas: Jaw-dropping Photosynth demo

Deb Roy: The birth of a word

3-Read Putting It Together: Summary Essay

a. b- Respond to the activity questions in your lab report. Make your responses brief but clear. Use the Lab 2 Report Template.

Lab 2 Report Template

Use the following template to complete your lab report. Before turning the report in, delete unnecessary information, such as these directions and examples, and save the report with a file name using the following convention: Your Last Name_Lab 2 Report (Ex: Petrak_Lab 2 Report).

Each section of the report should start on a new page (as in this template).

Putting it Together Activity Responses

1. The Happy Planet Index

Watch Nic Marks’s TEDTalk “The Happy Planet Index”. Marks argues that when we measure only economic indicators such as GDP, we are focusing on the wrong things.

a. What does Marks think we should be measuring?

b. How are these things related?

c. How does he use data visualization to make his point?

d. In his main graph, what should we be focusing on for the countries shown in the bottom left?

e. What should we be focusing on for the countries in the top right?

f. Consider Marks alongside Hans Rosling (Module 1 speaker in this lab), comparing the messages they share about the relative well-being of the world’s nations and the data visualization tools they use to make their points.

2. NOAA video on CO2 levels in the atmosphere

Watch this NOAA video on CO2 levels in the atmosphere. This powerful visual representation of data starts out only showing a small piece of the full graph.

a. Why do you think the designers created it this way?

b. Can you think of other ways the designers might have displayed this data?

c. How might Nathalie Miebach have represented this scientific data? (Nathalie Miebach is the author of the Module 4 talk, which is not required watching for this lab. A simple search about her is enough to give you a good idea of how she would conceptualize a representation of data.

3. Exploring Climate and Development Links” from the World Bank

“Exploring Climate and Development Links” from the World Bank shows excellent visualization of predicted temperature and precipitation changes over the next century under different scenarios. Look at projected temperature changes and projected precipitation changes under both scenarios. Be sure to scroll around on the map to find your own region.

a. Why do you think the designers chose the colors that they did?

b. Do you find the colors effective?

c. When you click on the map, an overlaid graph appears.

d. What does this graph show?

6. Movie Narrative Charts from xkcd.com

The web comic xkcd.com includes movie narrative charts that illustrate character interactions over space and time. These include charts for the Lord of the Rings trilogy, the original Star Wars trilogy, Jurassic Park, 12 Angry Men, and Primer.

a. What do you think about presenting the information this way?

b. Explain why the charts for the last two movies 12 Angry Men and Primer are not as interesting as the first two. (You might have to look up a summary of each movie if you’re not familiar with one or both.)

c. Name another movie (or series) for which you think this method would be interesting and effective. Explain your choice.

a. If you can’t think of a movie that would be an interesting illustration of this method, then give an example of a movie (or series) that is especially poorly suited to this method and explain your choice.

d. This space/time illustration for movies might remind you of the visualization method used by Deb Roy. How are they similar?

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Statistics: Visualizing Data

Putting It Together: Summary Essay and Activities

What’s Next? Trends and Questions in Statistics and Data Visualization

TED designed Visualizing Data to enable learners to recognize the powerful insights data can
provide when presented in a compelling fashion. We will continue to be inundated with data as
technology makes it easier and easier to collect the data. Learning how to “see” the patterns and
connections in data will become an increasingly sought after and valuable skill in virtually every
field. Learning how to create effective data visualizations will be even more valuable.

Coping with the deluge of what we call “Big Data” is one of the primary challenges for statisticians,
data analysts, and those who can benefit from the information it contains. Think of the data you
have generated in the past 24 hours – a record of every website you’ve visited, credit card
purchases, surveillance video at a business your visited, GPS tracking of where your phone has
traveled, road sensors that have monitored a vehicle you were in, photos posted online, every text,
tweet, and email have all been added to the day’s store of new data.

Organizing all of this data to be useful, while maintaining appropriate safeguards on individual
privacy, is an ongoing concern. New technology enables us to collect and store vast amounts of
data, but developing technologies that allow us to access, process, and display it in an
understandable form to address questions of interest is a daunting task.

While the TEDTalks in this series show how experts can extract and communicate valuable
information from data, one of the major challenges is to develop this capacity in non-experts who
have questions that data can help address, and to educate the general public to be intelligent
consumers of data-based analyses.

In the activities that follow, we encourage you to explore other uses and styles of data visualization.
These options just begin to scratch the surface. Start looking and you will find data visualizations
being used in almost any field. What are you interested in? Go explore the data and see what you
find!

Summary Activities

1. Watch Nic Marks’s TEDTalk “The Happy Planet Index”. Marks argues that when we
measure only economic indicators such as GDP, we are focusing on the wrong things. What
does Marks think we should be measuring? How are these things related? How does he use
data visualization to make his point? In his main graph, what should we be focusing on for

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the countries shown in the bottom left? What should we be focusing on for the countries in
the top right? Consider Marks alongside Hans Rosling, comparing the messages they share
about the relative well-being of the world’s nations and the data visualization tools they use
to make their points.

2. Watch this NOAA video on CO 2 levels in the atmosphere. This powerful visual
representation of data starts out only showing a small piece of the full graph. Why do you
think the designers created it this way? Can you think of other ways the designers might
have displayed this data? How might Nathalie Miebach have represented this scientific
data?

3. “Exploring Climate and Development Links” from the World Bank shows excellent
visualization of predicted temperature and precipitation changes over the next century
under different scenarios. Look at projected temperature changes and projected
precipitation changes under both scenarios. Be sure to scroll around on the map to find
your own region. Why do you think the designers chose the colors that they did? Do you
find the colors effective? When you click on the map, an overlaid graph appears. What
does this graph show?

4. Watch the CDC’s animated demonstration on trends in obesity levels in the United States.
You’ll need to scroll down to the bottom of the page to find the graphic labeled “Percent of
Obese (BMI ≥ 30) in U.S. Adults.” The animation shows how obesity rates have changed
over the period from 1985 to 2010. Be sure to watch the entire thing: Stop the animation
and use the previous button to scroll it back to 1985 and play it from the start. Do you find
the data visualization effective? Does this animation catch your eye and stay with you
more than reading a paragraph describing the obesity epidemic in the U.S.? Discuss the
use of color in this data visualization. Do you find the colors effective? Would you change
anything in the design of this data visualization? How might David McCandless or Chris
Jordan have represented this data?

5. Read the blog post “How Governments Can Better Use Data Visualization” by economist
and data visualization creator Jon Schwabish. In his blog post, Schwabish shares five
examples of poor graphical representations of data. Pick two of the five to analyze. In each
case: Describe why Schwabish believes the graph is not effective. Do you agree with his
assessment? Discuss ways in which the data might have been presented in a more effective
way.

6. The webcomic xkcd.com includes movie narrative charts that illustrate character
interactions over space and time. These include charts for the Lord of the Rings trilogy, the
original Star Wars trilogy, Jurassic Park, 12 Angry Men, and Primer. What do you think
about presenting the information this way? Explain why the charts for the last two movies
12 Angry Men and Primer are not as interesting as the first two. (You might have to look up
a summary of each movie if you’re not familiar with one or both.) Name another movie for

http://www.esrl.noaa.gov/gmd/ccgg/trends/history.html

http://climate4development.worldbank.org/#/risk

http://www.cdc.gov/obesity/data/adult.html

http://www.visualisingdata.com/index.php/2012/08/guest-post-how-governments-can-better-use-data-visualization/

http://xkcd.com/657/

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which you think this method would be interesting and effective. This space/time
illustration for movies might remind you of the visualization method used by Deb Roy. How
are they similar?

7. The” Many Eyes” project sponsored by IBM includes lots of interesting data visualizations
and has features that let users create their own visualizations based on a vast array of
contributed datasets at the site or by uploading their own data. You can search by keyword
for data that interests you and choose from an assortment of visualization methods to
create and modify displays within the site. Give it a try! You can publish a visualization you
create to the site, submit comments on those already there–and maybe someone else will
comment on yours.

8. Google Fusion Tables is an application that allows you to combine your own data with other
data on the web, collaborating with other users, visualizing the data and sharing it via
Google Drive. Google provides excellent tutorials on creating data visualizations and the
application also points users to many public data sources. Pick one of the data sources and
create your own data visualization.

http://www-958.ibm.com/software/data/cognos/manyeyes/

http://www.google.com/fusiontables

  • 8. Google Fusion Tables is an application that allows you to combine your own data with other data on the web, collaborating with other users, visualizing the data and sharing it via Google Drive. Google provides excellent tutorials on creating data visua�

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Statistics: Visualizing Data

Introductory Essay from the Locks

The Reality Today

All of us now are being blasted by information design. It’s being poured into our eyes
through the Web, and we’re all visualizers now; we’re all demanding a visual aspect to
our information… And if you’re navigating a dense information jungle, coming across
a beautiful graphic or a lovely data visualization, it’s a relief, it’s like coming across a
clearing in the jungle. –David McCandless

In today’s complex ‘information jungle,’ David McCandless observes that “Data is the new soil.”
McCandless, a data journalist and information designer, celebrates data as a ubiquitous resource
providing a fertile and creative medium from which new ideas and understanding can grow.
McCandless’s inspiration, statistician Hans Rosling, builds on this idea in his own TEDTalk with his
compelling image of flowers growing out of data/soil. These ‘flowers’ represent the many insights that
can be gleaned from effective visualization of data.

We’re just learning how to till this soil and make sense of the mountains of data constantly being
generated. As Gary King, Director of Harvard’s Institute for Quantitative Social Science says in his New
York Times article “The Age of Big Data”:

“It’s a revolution. We’re really just getting under way. But the march of quantification,
made possible by enormous new sources of data, will sweep through academia,
business and government. There is no area that is going to be untouched.”

How do we deal with all this data without getting information overload? How do we use data
to gain real insight into the world? Finding ways to pull interesting information out of data can
be very rewarding, both personally and professionally. The managing editor of Financial Times
observed on CNN’s Your Money: “The people who are able to in a sophisticated and practical
way analyze that data are going to have terrific jobs.” Those who learn how to present data in
effective ways will be valuable in every field.

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Many people, when they think of data, think of tables filled with numbers. But this long-held notion is
eroding. Today, we’re generating streams of data that are often too complex to be presented in a
simple “table.” In his TEDTalk, Blaise Aguera y Arcas explores images as data, while Deb Roy uses
audio, video, and the text messages in social media as data.

Some may also think that only a few specialized professionals can draw insights from data. When we
look at data in the right way, however, the results can be fun, insightful, even whimsical–and accessible
to everyone! Who knew, for example, that there are more relationship break-ups on Monday than on
any other day of the week, or that the most break-ups (at least those discussed on Facebook) occur in
mid-December? David McCandless discovered this by analyzing thousands of Facebook status updates.

Data, Data Everywhere

There is more data available to us now than we can possibly process. Every minute, Internet users add
the following to the big data pool1:

• 204,166,667 email messages sent
• More than 2,000,000 Google searches
• 684,478 pieces of content added on Facebook
• $272,070 spent by consumers via online shopping
• More than 100,000 tweets on Twitter
• 47,000 app downloads from Apple
• 34,722 “likes” on Facebook for different brands and organizations
• 27,778 new posts on Tumblr blogs
• 3,600 new photos on Instagram
• 3,125 new photos on Flickr
• 2,083 check-ins on Foursquare
• 571 new websites created
• 347 new blog posts published on WordPress
• 217 new mobile web users
• 48 hours of new video on YouTube

These numbers are almost certainly higher now, as you read this. And this just describes a small piece
of the data being generated and stored by humanity. We’re all leaving data trails—not just on the
Internet, but in everything we do. This includes reams of financial data (from credit cards, businesses,
and Wall Street), demographic data on the world’s populations, meteorological data on weather and
the environment, retail sales data that records everything we buy, nutritional data on food and
restaurants, sports data of all types, and so on.

1 Data obtained June 2012 from “How Much Data Is Created Every Minute?” on
http://mashable.com/2012/06/22/data-created-every-minute/ .

http://mashable.com/2012/06/22/data-created-every-minute/

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Governments are using data to search for terrorist plots, retailers are using it to maximize marketing
strategies, and health organizations are using it to track outbreaks of the flu. But did you ever think of
collecting data on every minute of your child’s life? That’s precisely what Deb Roy did. He recorded
90,000 hours of video and 140,000 hours of audio during his son’s first years. That’s a lot of data! He
and his colleagues are using the data to understand how children learn language, and they’re now
extending this work to analyze publicly available conversations on social media, allowing them to take
“the real-time pulse of a nation.”

Data can provide us with new and deeper insight into our world. It can help break stereotypes and build
understanding. But the sheer quantity of data, even in just any one small area of interest, is
overwhelming. How can we make sense of some of this data in an insightful way?

The Power of Visualizing Data

Visualization can help transform these mountains of data into meaningful information. In his TEDTalk,
David McCandless comments that the sense of sight has by far the fastest and biggest bandwidth of
any of the five senses. Indeed, about 80% of the information we take in is by eye. Data that seems
impenetrable can come alive if presented well in a picture, graph, or even a movie. Hans Rosling tells us
that “Students get very excited – and policy-makers and the corporate sector – when they can see the
data.”

It makes sense that, if we can effectively display data visually, we can make it accessible and
understandable to more people. Should we worry, however, that by condensing data into a graph, we
are simplifying too much and losing some of the important features of the data? Let’s look at a
fascinating study conducted by researchers Emre Soyer and Robin Hogarth. The study was conducted
on economists, who are certainly no strangers to statistical analysis. Three groups of economists were
asked the same question concerning a dataset:

• One group was given the data and a standard statistical analysis of the data; 72% of these
economists got the answer wrong.

• Another group was given the data, the statistical analysis, and a graph; still 61% of these
economists got the answer wrong.

• A third group was given only the graph, and only 3% got the answer wrong.

Visualizing data can sometimes be less misleading than using the raw numbers and statistics!

What about all the rest of us, who may not be professional economists or statisticians? Nathalie
Miebach finds that making art out of data allows people an alternative entry into science. She
transforms mountains of weather data into tactile physical structures and musical scores, adding both
touch and hearing to the sense of sight to build even greater understanding of data.

http://emresoyer.com/Publications_files/Soyer%20%26%20Hogarth_2012

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Another artist, Chris Jordan, is concerned about our ability to comprehend big numbers. As citizens of
an ever-more connected global world, we have an increased need to get useable information from big
data—big in terms of the volume of numbers as well as their size. Jordan’s art is designed to help us
process such numbers, especially numbers that relate to issues of addiction and waste. For example,
Jordan notes that the United States has the largest percentage of its population in prison of any country
on earth: 2.3 million people in prison in the United States in 2005 and the number continues to rise.
Jordan uses art, in this case a super-sized image of 2.3 million prison jumpsuits, to help us see that
number and to help us begin to process the societal implications of that single data value. Because our
brains can’t truly process such a large number, his artwork makes it real.

The Role of Technology in Visualizing Data

The TEDTalks in this collection depend to varying degrees on sophisticated technology to gather, store,
process, and display data. Handling massive amounts of data (e.g., David McCandless tracking 10,000
changes in Facebook status, Blaise Aguera y Arcas synching thousands of online images of the Notre
Dame Cathedral, or Deb Roy searching for individual words in 90,000 hours of video tape) requires
cutting-edge computing tools that have been developed specifically to address the challenges of big
data. The ability to manipulate color, size, location, motion, and sound to discover and display
important features of data in a way that makes it readily accessible to ordinary humans is a challenging
task that depends heavily on increasingly sophisticated technology.

The Importance of Good Visualization

There are good ways and bad ways of presenting data. Many examples of outstanding presentations of
data are shown in the TEDTalks. However, sometimes visualizations of data can be ineffective or
downright misleading. For example, an inappropriate scale might make a relatively small difference
look much more substantial than it should be, or an overly complicated display might obfuscate the
main relationships in the data. Statistician Kaiser Fung’s blog Junk Charts offers many examples of
poor representations of data (and some good ones) with descriptions to help the reader understand
what makes a graph effective or ineffective. For more examples of both good and bad representations
of data, see data visualization architect Andy Kirk’s blog at visualisingdata.com. Both consistently
have very current examples from up-to-date sources and events.

Creativity, even artistic ability, helps us see data in new ways. Magic happens when interesting data
meets effective design: when statistician meets designer (sometimes within the same person). We are
fortunate to live in a time when interactive and animated graphs are becoming commonplace, and
these tools can be incredibly powerful. Other times, simpler graphs might be more effective. The key is
to present data in a way that is visually appealing while allowing the data to speak for itself.

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Changing Perceptions Through Data

While graphs and charts can lead to misunderstandings, there is ultimately “truth in numbers.” As
Steven Levitt and Stephen Dubner say in Freakonomics, “[T]eachers and criminals and real-estate
agents may lie, and politicians, and even C.I.A. analysts. But numbers don’t.” Indeed, consideration of
data can often be the easiest way to glean objective insights. Again from Freakonomics: “There is
nothing like the sheer power of numbers to scrub away layers of confusion and contradiction.”

Data can help us understand the world as it is, not as we believe it to be. As Hans Rosling
demonstrates, it’s often not ignorance but our preconceived ideas that get in the way of understanding
the world as it is. Publicly-available statistics can reshape our world view: Rosling encourages us to “let
the dataset change your mindset.”

Chris Jordan’s powerful images of waste and addiction make us face, rather than deny, the facts. It’s
easy to hear and then ignore that we use and discard 1 million plastic cups every 6 hours on airline
flights alone. When we’re confronted with his powerful image, we engage with that fact on an entirely
different level (and may never see airline plastic cups in the same way again).

The ability to see data expands our perceptions of the world in ways that we’re just beginning to
understand. Computer simulations allow us to see how diseases spread, how forest fires might be
contained, how terror networks communicate. We gain understanding of these things in ways that
were unimaginable only a few decades ago. When Blaise Aguera y Arcas demonstrates Photosynth, we
feel as if we’re looking at the future. By linking together user-contributed digital images culled from all
over the Internet, he creates navigable “immensely rich virtual models of every interesting part of the
earth” created from the collective memory of all of us. Deb Roy does somewhat the same thing with
language, pulling in publicly available social media feeds to analyze national and global conversation
trends.

Roy sums it up with these powerful words: “What’s emerging is an ability to see new social structures
and dynamics that have previously not been seen. …The implications here are profound, whether it’s
for science, for commerce, for government, or perhaps most of all, for us as individuals.”

Let’s begin with the TEDTalk from David McCandless, a self-described “data detective” who describes
how to highlight hidden patterns in data through its artful representation.

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