{"id":11413,"date":"2014-12-05T16:21:00","date_gmt":"2014-12-06T00:21:00","guid":{"rendered":"http:\/\/www.questionpro.com\/?p=11413"},"modified":"2014-12-05T16:21:00","modified_gmt":"2014-12-06T00:21:00","slug":"uxs-future-6-billion-tweets-personal-data-qual-defined-the-origin-of-stats-thats-todays-fridayfive","status":"publish","type":"post","link":"https:\/\/www.questionpro.com\/blog\/uxs-future-6-billion-tweets-personal-data-qual-defined-the-origin-of-stats-thats-todays-fridayfive\/","title":{"rendered":"UX’s Future; 6 Billion Tweets; Personal Data; Qual Defined; the Origin of Stats. That’s Today’s #FridayFive!"},"content":{"rendered":"

\"FridayFive\"<\/a>Once again we’ve scoured the web to provide the best, most relevant light reading for your Friday.
\nThis week we’re going to predict the future of UX, show you what 6 billion tweets looks like, solve the debate over whether sharing personal data is good or bad, define qualitative research, and share the origin of statistics. *Phew!*<\/p>\n

<\/p>\n

The future of UX: Perspective from a teacher of next generation\u2019s pros<\/a> — TryMyUI<\/p>\n

Insightful Q&A from Professor Guiseppe Getto of East Carolina University answers 5 questions about what he teaches UX students.<\/p>\n

Here’s What 6 Billion Tweets Looks Like Mapped<\/a> — Forbes<\/p>\n

We’re big fans of data here at QuestionPro, we’ve even been known to data-geek-out once or twice. So when we saw what had been done with 3 terabytes of geotagged tweet data, ‘natch’ it caught our curiosity.<\/p>\n

Personal Data: A Threat Or An Opportunity For Our Industry<\/a> — Green Book Blog<\/p>\n

The debate over the pros and cons of so much personal data out there rages on – and it doesn’t look like it’s slowing down any time soon…<\/p>\n

How do we define qualitative research in a new MR world?<\/a> — New MR<\/p>\n

As the market research industry evolves, some of the terms by which it’s defined must evolve too. Here’s a dive into what we call qualitative research.<\/p>\n

Daddy, where do statistics come from? #MRX<\/a> — The LoveStats Blog<\/p>\n

Want to know where probability sampling and p-values and margins of error come from? Well, Happy Friday!<\/p>\n","protected":false},"excerpt":{"rendered":"

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