Going Back to the Basics?

With data science languages, sometimes learning the basics can be the hardest part. The QAC offers several .25 credit classes that introduce students to the necessities of different languages, but even fitting all the necessary information into a half a semester can be difficult. This past quarter, Professor Pavel Oleinikov utilized a website called DataCamp to help his students get comfortable with the basics of Python. DataCamp is an online collection of data science lessons that teaches users through videos and repetitive exercises. The website has an in-browser code box that allows users to code right on the website without having to download any software. Each lesson takes roughly 30 minutes to 1 hour to complete, making it a convenient way to nail down a specific skill.

Students in Pavel’s Working with Python class really enjoyed being assigned DataCamp lessons as homework. “We only have 3 hours, and that may seem long but that’s not a lot of time considering the concepts that we’re learning,” said Anthony Price. These .25 credit classes move quickly, and so there isn’t much time to backtrack if students are lost. And students can always Google around for answers, but sometimes the vast amount of material returned can be overwhelming. This is why it is important to have resources in place so that students don’t give up before they get comfortable.

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Can we Utilize Passion in Data Science?

It can be easy to think of data science as cut and dry analysis consisting solely of numbers. But according to Economics major Leah Giacalone ’17, if people think of it that way it’s just because they haven’t tried it yet. “Personally, I’ve always found being able to code super exciting,” she said. “The first time I wrote code and then it worked was the most exciting thing ever. I always tell people that and they don’t believe me.”

If you are someone who doesn’t believe in the passion underlying data science, then maybe it’s time to give it a go, because an increasing number of companies are utilizing passion as a power source for their problems. An example of this is Kaggle, a website founded in 2010 that allows companies to post their data and research problems online so that people from around the world can compete to create the best solution. Kaggle is using the overflow of big data to its advantage to create a sort of Kickstarter for data science. It’s engaging, fresh, and possibly a good way for data analysis hopefuls to break the ice with coding.

Recently, Kaggle was used at Wesleyan by Professor Pavel Oleinikov in his class “Introduction to Text Mining.” Pavel asked his students to use customer reviews from Yelp to create an algorithm that could best predict whether a Yelp review was positive (4 or 5 stars) or negative (1 or 2 stars). The students used reviews of Arizona hotels as a guide for creating dictionaries of 20 positive and 20 negative words that would then be built into their model. The accuracy of the students’ models was then tested on Pennsylvania hotel reviews and judged by a mean utility metric that assigned a score between -1 (wrong in every case) and 1 (got everything correct). Narin Luangrath ‘17, a Math and Computer Science double major, won the class competition with a mean utility score of .72.

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Seasons of Internships

I’ve feared the moment that my summers would be turned over to internships for a long time. I can’t remember for how long I’ve known internships are important – probably for as long as I’ve known about applying for college. My relationship with the idea of internships has gone through stages, with me sliding from thinking that they are silly resume builders to valuable and necessary work experience almost every day. I recently decided that I wanted to pursue some sort of consulting internship, and then felt a drop in my stomach similar to when I decided to apply for Wesleyan. But while there is a large and personalized application process still ahead of me, I don’t want to feel as scared as I did then. With this in mind, I sat down with Asie Makarova ’17 and Taylor Chin ’18 to discuss two of the main myths about internships and what truths, based on their experience, lie beneath.

Both Asie and Taylor had similar beginnings to their internship journey. “I started pretty early applying to things Junior fall,” Asie remembered. She found her connection through LinkedIn, by reaching out to a friend’s dad who then put her in contact with FTI Consulting. Taylor also came across his internship on LinkedIn when he noticed that an old friend from high school had connections at an energy intelligence software company called EnerNOC. From there, both Taylor and Asie got offered interviews at their respective companies.

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New Age Research in a New Age World: An Interview with the QAC’s Congressional Politics Research Lab

When seen through a news report or a computer screen, the impact of current political research can seem very disconnected from what’s really taking place. It can be hard to try to understand the results and implications of politician’s behaviors and opinions without an already-written history book. But with this new age of media presentation comes the new age digging tool of data analysis, which is once again proving to be the key to decoding to today’s political discourse.

And that’s not its only use. Once again, Wes students are proving it possible to not only use online politics for research purposes, but to get your foot in the door of Data in the Real World. In April, John Murchison ‘16, Grace Wong ‘18, and Joli Holmes ’17 attended the Midwest Political Science Association conference in Chicago to present a poster about their research on congressional politics.

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Is it our future to be agnostic?

As interest in data and data analysis grows, future students interested in the career have to work harder to understand the boundaries and guidelines. It won’t always be as simple as it was for Evan Thorne ‘15, who came to Wesleyan thinking he wanted to study Economics before discovering the QAC department. “I was starting to work with data sets in my math and computer science classes when I heard about big data,” Evan said, explaining that it was soon after he began taking classes with the QAC that he realized he wanted this as a career.

But what is “this”? Data science? Data analysis? Data manipulation? Sometimes it can be hard to define. But Evan did not flounder when I asked him for a definition of his job at CKM Advisors, the company where he was hired right after graduation. He began by explaining to me that an analyst is someone who is able to take in what’s readily available to them and then dissect it to look at more basic stats and trends. Data scientists, however, are able to find things that aren’t available – unstructured data – and take it in raw. “Every data scientist is an analyst in a way,” Evan explained, “but it’s at a much bigger level.” At CKM, Evan is a data scientist, and he is responsible for all of the analytic process: data ingestion, wrangling, manipulation, analysis, and visualization.

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Data from Surprising Origins: Looking at the Work of R. Luke Dubois

When R. Luke Dubois sat down with a group of students for lunch on Friday, November 20th, he could have begun by introducing himself: Known as R. Luke Dubois or just Luke Dubois, he is an artist based in New York City with many notable works related to data, some of which have been on display at the Zilkha Gallery since the beginning of the semester. But instead he began by asking us what we were working on.

At first, most of us nervously fidgeted in silence. We hadn’t been expecting the spotlight to be on us. After a couple awkward moments, I offered up an explanation of my final project for my data analysis class. Dubois responded with interest and gave some suggestions. After that, other students slowly began to come forward with their ideas, and he continued to react excitedly. He then powered up the projector behind him and showed us some related work by other artists, such as Fernanda Viegas and Martin Wattenberg.

After this discussion had gone on for a while, I realized that Dubois wasn’t going to talk about himself or his work unless he was prodded to. I turned the spotlight back on him by asking whether he thinks of himself as an artist or data researcher. Dubois jerked his eyes upwards, and when they re-centered on us he had a funny smile on his face. “I’m a musician,” he responded. “I play the cello badly. I played so badly that I switched to a computer.”

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Data and a Polygraph: A Look into Data Journalism

As the uses and values of data become more well-known, more and more unique ways of exploring and presenting data are emerging to the forefront of the Internet. When Wesleyan invited one of these explorers, Matt Daniels, to give a talk on data journalism and media art, I immediately dug into his portfolio. Daniels hosts his projects on a website called Polygraph, and currently has only focused one exploring data related to music. I was immediately transfixed by the name of his site – polygraph isn’t a word commonly connected to data or information – and, due to blanking on the definition, Googled it. I found the following:

pol·y·graph [ˈpälēˌɡraf]

NOUN

  1. A machine designed to detect and record changes in physiological characteristics, such as a person’s pulse and breathing rates, used especially as a lie detector.

With this definition swirling in my head, I came to Daniels’ talk eager to learn what he was all about. Daniels, one of the many young creators who are storming the tech industry, began by clicking to a slide of the visualization that made him “internet famous.” He describes that the goal of this project was to look at the usage of unique words by rappers in their songs. The visualization charts these usages, along with the amount of unique words used by authors ranging from Shakespeare to Melville. The visualization was then followed by some text that further fleshed out what he had discovered. And there you find Daniel’s formula, the foundation of this data journalism he has fallen into: a code narrative + a prose narrative = an interesting and interactive read.

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Don’t Count Data Out: A Conversation with Dana Louie ‘14

When I mention that I’m taking classes in the QAC department, I’m often met with blinking eyes and blank stares. Few people know what it is, or if they do they ask something along the lines of: “Oh, that <em>data</em> thing?” They say data like it’s some sort of disease that is not understandable or conquerable.

Data is far from a disease, but it <em>is</em> capable of spreading everywhere. Data are not static numbers on a screen; data are what is behind your favorite <em>New York Times</em> article. Data is extremely customizable and manipulatable and, most importantly, for everyone.

Despite those who have never heard of the QAC before, the department has been running at Wesleyan for years, and many now graduated students stumbled their way into their first QAC class only to leave with a career in data analysis. One of those students is Dana Louie ’14, who I had the pleasure of chatting to when she came to campus to give an info session for Analysis Group, the firm she works for. Dana’s discovery of the QAC happened through the QAC summer program, where she took classes in morning and then worked on research with professor in the afternoon. The following year, she was selected to be QAC tutor, and her fate in the department was sealed.

“People can succeed [in QAC classes] even with no background,” Dana said confidently, referring to the fear that keeps a lot of students from getting off the bench and entering the world of the QAC. When talking with my friends about by own experiences in the QAC, they often say something along the lines of “Wow, that sounds really cool. I wish I could do that.” I always respond with “You can,” just as Dana as saying. There are many intro classes in the QAC (QAC201, QAC211), and many chances to start to learn one of the programming languages.

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Data Analysis Beyond the QAC: A Conversation with Zach ’15 and Sanvir ‘15

Do you ever wonder how the fascinating theories you’re learning at Wesleyan might help you get a job after graduation? It’s so easy to be romanced by Wesleyan’s niche majors and broad-based interdisciplinary options. And that’s how it should be – you should definitely take advantage of that eye-opening class on Race & Medicine and those lectures on the origins of medieval eastern-European dance. But as Aunt Mildred and Uncle Al like to remind you at family reunions, knowing a lot about the political history of the Sung Dynasty isn’t enough to get you a job.

That’s where QAC comes in. As the QAC web site explains, QAC “coordinates support for quantitative analysis across the curriculum, and provides an institutional framework for collaboration across departments and disciplines.” Putting it another way, data analysis skills combine beautifully with the critical thinking skills and broad-based theories you’re learning in your other classes, and open the door to research and employment opportunities across a wide spectrum of fields. “Irrespective of your major, you can do data analysis work to help you with whatever you’re doing,” Sanvir ’15 pointed out. “If you really look into it, you can do something with data to make your work more interesting. An example would be English word mapping.”

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