[ COVER OF THE WEEK ]
Fake data Source
[ NEWS BYTES]
[ FEATURED COURSE]
This course is an introduction to statistical data analysis. Topics are chosen from applied probability, sampling, estimation, hypothesis testing, linear regression, analysis of variance, categorical data analysis, and n… more
[ FEATURED READ]
Ray Kurzweil is arguably today’s most influentialÂand often controversialÂfuturist. In How to Create a Mind, Kurzweil presents a provocative exploration of the most important project in human-machine civilizationÂreverse… more
[ TIPS & TRICKS OF THE WEEK]
Data Analytics Success Starts with Empowerment
Being Data Driven is not as much of a tech challenge as it is an adoption challenge. Adoption has it’s root in cultural DNA of any organization. Great data driven organizations rungs the data driven culture into the corporate DNA. A culture of connection, interactions, sharing and collaboration is what it takes to be data driven. Its about being empowered more than its about being educated.
[ DATA SCIENCE Q&A]
Q:What is: lift, KPI, robustness, model fitting, design of experiments, 80/20 rule?
ItÂs measure of performance of a targeting model (or a rule) at predicting or classifying cases as having an enhanced response (with respect to the population as a whole), measured against a random choice targeting model. Lift is simply: target response/average response.
Suppose a population has an average response rate of 5% (mailing for instance). A certain model (or rule) has identified a segment with a response rate of 20%, then lift=20/5=4
Typically, the modeler seeks to divide the population into quantiles, and rank the quantiles by lift. He can then consider each quantile, and by weighing the predicted response rate against the cost, he can decide to market that quantile or not.
Âif we use the probability scores on customers, we can get 60% of the total responders weÂd get mailing randomly by only mailing the top 30% of the scored customersÂ.
– Key performance indicator
– A type of performance measurement
– Examples: 0 defects, 10/10 customer satisfaction
– Relies upon a good understanding of what is important to the organization
Marketing & Sales:
– New customers acquisition
– Customer attrition
– Revenue (turnover) generated by segments of the customer population
– Often done with a data management platform
– Mean time between failure
– Mean time to repair
– Statistics with good performance even if the underlying distribution is not normal
– Statistics that are not affected by outliers
– A learning algorithm that can reduce the chance of fitting noise is called robust
– Median is a robust measure of central tendency, while mean is not
– Median absolute deviation is also more robust than the standard deviation
– How well a statistical model fits a set of observations
– Examples: AIC, R2, Kolmogorov-Smirnov test, Chi 2, deviance (glm)
Design of experiments:
The design of any task that aims to describe or explain the variation of information under conditions that are hypothesized to reflect the variation.
In its simplest form, an experiment aims at predicting the outcome by changing the preconditions, the predictors.
– Selection of the suitable predictors and outcomes
– Delivery of the experiment under statistically optimal conditions
– Blocking: an experiment may be conducted with the same equipment to avoid any unwanted variations in the input
– Replication: performing the same combination run more than once, in order to get an estimate for the amount of random error that could be part of the process
– Interaction: when an experiment has 3 or more variables, the situation in which the interaction of two variables on a third is not additive
– Pareto principle
– 80% of the effects come from 20% of the causes
– 80% of your sales come from 20% of your clients
– 80% of a company complaints come from 20% of its customers
[ VIDEO OF THE WEEK]
Subscribe to Youtube
[ QUOTE OF THE WEEK]
Everybody gets so much information all day long that they lose their common sense. Â Gertrude Stein
[ PODCAST OF THE WEEK]
[ FACT OF THE WEEK]
We are seeing a massive growth in video and photo data, where every minute up to 300 hours of video are uploaded to YouTube alone.