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Showing posts with the label big data

Statistics/RM videos from The Economist

TED isn't the only source of videos for teaching statistics . The Economist also makes animated videos that are lousy with data. One easy, no-pay-wall source for such videos is The Economists Videographic playlist on YouTube  (there is a limit on number article views/month at their website ). One really statsy video from The Economist that I've featured previously on this blog explains the real life implications for Type I/Type II error in research (and, specifically, how it leads to errors in published research ). The other videos may not be as directly related to the teaching of statistical topics, but they do illustrate data. Topics range from American union membership trends to this video about world population growth . As you may have inferred from the source, many of these videos focus on national and global economic information, but all of the videos do present data that you can integrate into your classes. Some are more applicable to teaching statistics: This vid...

Aarti Shahani's "How will the next president protect our digital lives?"

I think that it is so, so important to introduce statistics students to the big picture of how data is used in their every day lives. Even with all of the material that we are charged with covering in introduction to statistics, I think it is still important to touch on topics like Big Data and Data Mining in order to emphasize to our students how ubiquitous statistics are in our lives.  In my honors section, I assign multiple readings (news stories, TED talks, NPR stories) prior to a day of discussion devoted to this topic. In my non-honors sections of statistics and my online sections, I've used electronic discussion boards to introduce the topic via news stories. I also have a manuscript in press that describes a way to introduce very basic data mining techniques in the Introduction to Statistics classroom. That's why I think this NPR news story is worth sharing. Shahani describes and provides data (from Pew) to argue that Americans are worried about the security of...

One article (Kramer, Guillory, & Hancock, 2014), three stats/research methodology lessons

The original idea for using this article this way comes from Dr. Susan Nolan 's presentation at NITOP 2015, entitled " Thinking Like a Scientist: Critical Thinking in Introductory Psychology."  I think that Dr. Nolan's idea is worth sharing, and I'll reflect a bit on how I've used this resource in the classroom. (For more good ideas from Dr. Nolan, check out her books, Psychology , Statistics for the Behavioral Sciences , and The Horse that Won't Go Away (about critical thinking)). Last summer, the National Academy of Sciences Proceedings published an article entitled "Experimental evidence of massive-scale emotional contagion through social networks ." The gist: Facebook manipulated participants' Newsfeeds to increase the number of positive or negative status updates that each participant viewed. The researchers subsequently measured the number of positive and negative words that the participants used in their own status updates. They fou...

TED talks about statistics and research methods

There are a number of TED talks that apply to research methods and statistics classes. First, there is this TED playlist entitled The Dark Side of Data . This one may not be applicable to a basic stats class but does address broader ethical issues of big data, widespread data collection, and data mining. These videos are also a good way of conveying how data collection (and, by extension, statistics) are a routine and invisible part of everyday life. This talk by Peter Donnelly discusses the use of statistics in court cases, and the importance of explaining statistics in a manner that laypeople can understand. I like this one as I teach my students how to create APA results sections for all of their statistical analyses. This video helps to explain WHY we need to learn to report statistics, not just perform statistics. Hans Rosling has a number of talks (and he has been mentioned previously on this blog, but bears being mentioned again). He is a physician and conveys his passion...

Nell Greenfieldboyce's "Big Data peeks at your medical records to find drug problems"

NPR's Nell Greenfieldboyce (I know, I thought it would be hyphenated as well) reports on Mini-Sentinel , an effort by the government to detect adverse side effects associated with prescription drugs as quickly as possible. Specifically, instead of waiting for doctors to voluntarily report adverse effects, they are mining data from insurance companies in order to detect side effects and illnesses being experienced by people on prescription drugs. Topics covered by this story that may apply to your teaching: 1) Big data 2) Big data solving health problems 3) Data and privacy issues 4) Conflict of interest 5) An example of the federal government pouring lots of money into statistics to make the world a little safer 6) An example of a data and statistics being used in not-explicitly-statsy-data fields and occupations