[ COVER OF THE WEEK ]
[ LOCAL EVENTS & SESSIONS]
- Dec 10, 2017 #WEB Certified KPI Professional and Practitioner – Dubai December 2017
- Nov 22, 2017 #WEB SEO Insights & Analytics toâBoostâyourâRankiÂng
- Nov 30, 2017 #WEB ITIL Foundation- 2 days Classroom Training in Raliegh,NC
[ AnalyticsWeek BYTES]
[ NEWS BYTES]
[ FEATURED COURSE]
[ FEATURED READ]
What are the jobs of the future? How many will there be? And who will have them? As technology continues to accelerate and machines begin taking care of themselves, fewer people will be necessary. Artificial intelligence… more
[ TIPS & TRICKS OF THE WEEK]
Keeping Biases Checked during the last mile of decision making
Today a data driven leader, a data scientist or a data driven expert is always put to test by helping his team solve a problem using his skills and expertise. Believe it or not but a part of that decision tree is derived from the intuition that adds a bias in our judgement that makes the suggestions tainted. Most skilled professionals do understand and handle the biases well, but in few cases, we give into tiny traps and could find ourselves trapped in those biases which impairs the judgement. So, it is important that we keep the intuition bias in check when working on a data problem.
[ DATA SCIENCE Q&A]
Q:You have data on the durations of calls to a call center. Generate a plan for how you would code and analyze these data. Explain a plausible scenario for what the distribution of these durations might look like. How could you test, even graphically, whether your expectations are borne out?
A: 1. Exploratory data analysis
* Histogram of durations
* histogram of durations per service type, per day of week, per hours of day (durations can be systematically longer from 10am to 1pm for instance), per employee
2. Distribution: lognormal?
3. Test graphically with QQ plot: sample quantiles of log(durations)log?(durations) Vs normal quantiles
[ VIDEO OF THE WEEK]
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[ QUOTE OF THE WEEK]
In God we trust. All others must bring data. W. Edwards Deming
[ PODCAST OF THE WEEK]
[ FACT OF THE WEEK]
Retailers who leverage the full power of big data could increase their operating margins by as much as 60%.