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The QAC site is at http://qac.wesleyan.edu.
March 24, 2014, 3:31 pm
“Last week we hosted data artist Jer Thorp for several days. As part of our Distinguished Innovator in Residence Program (a partnership between University Libraries and TLOS with others contributing as well) we bring in creative thinkers to meet with students, brainstorm with faculty, give a public lecture, and essentially spark new conversations across campus. I highly recommend his Ted Talk.
I was fortunate to hear Jer speak four different times to diverse audiences. A theme that surfaced and resonated with us was the notion of Data Across the Curriculum, which is analogous to Writing Across the Curriculum. Our CIO added, “what if we had a common data set?” similar to the Common Book concept. Imagine the interdisciplinary possibilities of merging these two—a thought-provoking book accompanied by a related thought-provoking data set.
The concepts of data literacy, data fluency, and data understanding were prevalent throughout. Jer suggested using an app like Open Paths (note, he is directly involved with this free product) to give students and others access to and control over their own location data. His recommendation was to use personal data as a means of intrigue. Since the information is directly associated with their lives, students could understand it and would find it interesting and relatable. The patterns that emerged would (hopefully) make sense to them. By making data personal, it becomes less abstract—this is my life, not just some random numbers. What’s the story here?”
To read more, check out the article at http://chronicle.com/blognetwork/theubiquitouslibrarian/2014/03/24/data-across-the-curriculum-is-personal-data-the-key/?cid=wc&utm_source=wc&utm_medium=en
By Tim Harford
“Big data is a vague term for a massive phenomenon that has rapidly become an obsession with entrepreneurs, scientists, governments and the media.
Five years ago, a team of researchers from Google announced a remarkable achievement in one of the world’s top scientific journals, Nature. Without needing the results of a single medical check-up, they were nevertheless able to track the spread of influenza across the US. What’s more, they could do it more quickly than the Centers for Disease Control and Prevention (CDC). Google’s tracking had only a day’s delay, compared with the week or more it took for the CDC to assemble a picture based on reports from doctors’ surgeries. Google was faster because it was tracking the outbreak by finding a correlation between what people searched for online and whether they had flu symptoms.”
For more information, check out the article at http://www.ft.com/cms/s/2/21a6e7d8-b479-11e3-a09a-00144feabdc0.html#ixzz2xk7uLAkA
This past summer, I participated in the Quantitative Analysis Center’s Summer Apprenticeship Program and served as a research assistant for Professor Masami Imai of the Economics Department. We conducted an event-study analysis to assess the impact of the Bank of Japan’s regime change and nonconventional monetary policy on asset prices.
Since the 1990s, stagnation and deflation have plagued the Japanese economy. In an effort to stimulate growth, the Bank of Japan has adopted non-traditional monetary policy measures of forward guidance of future policy rates, targeted asset purchases, and quantitative easing. Specifically, we considered the effectiveness of the Bank of Japan’s most recent policies under the new leadership of Prime Minister Shinzō Abe and Bank of Japan Governor Haruhiko Kuroda.
From our research, we found that across the majority of nonconventional monetary policy announcements, interest rates decreased as expected. However, we also observed that the Nikkei Index and dollar/yen rate failed to move in the predicted directions. Targeted asset purchases and quantitative easing were found to have insignificant effects on asset prices. We observed that nonconventional monetary policy measures are associated with only temporary changes in asset prices.
As expected, our results show that the Bank of Japan’s regime change under Governor Kuroda had the most significant effect on asset prices. On April 4, 2013, the Bank of Japan announced its plan to double the monetary base and conduct open-ended asset purchases as part of “Quantitative and Qualitative Monetary Easing”. The announcement generated significant effects on interest rates and the dollar/yen exchange rate. Long-term interest rates on Japanese Government Bonds, spanning from the yield on the 6-year JGB to the yield on the 40-year JGB, significantly decreased after the announcement. The Nikkei closed up 272 points on the announcement date, but the movement failed to be significant.
Through this research, I gained a strong understanding of the Japanese banking system and also developed proficiency in Stata and R statistical packages. I have sharpened my quantitative and analytical skills through my work with Professor Imai and Professor Kaparakis, and I look forward to continuing to assist Professor Imai with his research in the spring.
Feb. 20, 2014 by adistler
I stumbled across these numbers when I was searching around Business Insider online and found them particularly interesting since I am a user for almost all these websites and social media tools. I also must confess that it’s only 10 am and I’ve sent 17 snaps via snapchat already.
Interesting Statistics in the World of Business and Social Media:
Advertisers can now target users on Twitter by which operating system and version they use, specific device, and Wi-Fi connectivity. (Twitter Blog)
Snapchat’s owners turned down a $3 billion acquisition offer from Facebook. (Wall Street Journal)
WeChat now has 272 million monthly active users, up 15% from the previous quarter. (Tencent)
Dropbox now has 200 million users. (TechCrunch)
Google generates more revenue than the magazine and newspaper industries in the U.S. (Business Insider)
Taken from: http://techcrunch.com/2013/11/19/how-many-users-does-snapchat-have/
By Dana Louie
This command describes your missing data for you. It was helpful this summer when I was trying to replicate findings that had been produced two years ago when less data was available. I had to figure out what of my data needed to be coded out and was able to check my work using this command.
First, you’ll need to install the package by first giving Stata the command: findit mdesc. Then you can use mdesc with or without a variable list after the command. Hope that this comes in handy sometime!
By Dana Louie