[ COVER OF THE WEEK ]
Tour of Accounting Source
[ AnalyticsWeek BYTES]
[ NEWS BYTES]
[ FEATURED COURSE]
Data that has relevance for managerial decisions is accumulating at an incredible rate due to a host of technological advances. Electronic data capture has become inexpensive and ubiquitous as a by-product of innovations… more
[ FEATURED READ]
The human brain has some capabilities that the brains of other animals lack. It is to these distinctive capabilities that our species owes its dominant position. Other animals have stronger muscles or sharper claws, but … more
[ TIPS & TRICKS OF THE WEEK]
Finding a success in your data science ? Find a mentor
Yes, most of us dont feel a need but most of us really could use one. As most of data science professionals work in their own isolations, getting an unbiased perspective is not easy. Many times, it is also not easy to understand how the data science progression is going to be. Getting a network of mentors address these issues easily, it gives data professionals an outside perspective and unbiased ally. It’s extremely important for successful data science professionals to build a mentor network and use it through their success.
[ DATA SCIENCE Q&A]
Q:What is root cause analysis? How to identify a cause vs. a correlation? Give examples
A: Root cause analysis:
– Method of problem solving used for identifying the root causes or faults of a problem
– A factor is considered a root cause if removal of it prevents the final undesirable event from recurring
Identify a cause vs. a correlation:
– Correlation: statistical measure that describes the size and direction of a relationship between two or more variables. A correlation between two variables doesnt imply that the change in one variable is the cause of the change in the values of the other variable
– Causation: indicates that one event is the result of the occurrence of the other event; there is a causal relationship between the two events
– Differences between the two types of relationships are easy to identify, but establishing a cause and effect is difficult
Example: sleeping with ones shoes on is strongly correlated with waking up with a headache. Correlation-implies-causation fallacy: therefore, sleeping with ones shoes causes headache.
More plausible explanation: both are caused by a third factor: going to bed drunk.
Identify a cause Vs a correlation: use of a controlled study
– In medical research, one group may receive a placebo (control) while the other receives a treatment If the two groups have noticeably different outcomes, the different experiences may have caused the different outcomes
[ VIDEO OF THE WEEK]
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[ QUOTE OF THE WEEK]
Data that is loved tends to survive. Kurt Bollacker, Data Scientist, Freebase/Infochimps
[ PODCAST OF THE WEEK]
[ FACT OF THE WEEK]
Every second we create new data. For example, we perform 40,000 search queries every second (on Google alone), which makes it 3.5 searches per day and 1.2 trillion searches per year.In Aug 2015, over 1 billion people used Facebook FB +0.54% in a single day.