Statistics
Analytics
Business Analytics and Hollywood: Smarter ways to win Oscars
My favorite acceptance speeches are from Oscar recipients in science and technology. In contrast to actors, directors and writers, these winners love pushing the envelope in fields like animation, special effects, costume desig...
Analytics
Lavastorm Analytics empowers Visual Analytic capabilities with R
Lavastorm Analytics, a leading global analytics software company, announced today that the award-winning Lavastorm Analytics Platform and its core Lavastorm Analytics Engine can now directly support statistical and predictive d...
Analytics
Online Analytics Training Program from Aryng
Aryng, a Silicon Valley based Analytics training and consulting company has launched a series of online courses to address the training needs of business professionals, especially for individuals from marketing and product func...
Analytics
Genetic Algorithm Applications
The advantage of the GA approach is the ease with which it can handle arbitrary kinds of constraints and objectives; all such things can be handled as weighted components of the fitness function, making it easy to adapt the GA ...
Analytics
Conjoint Analysis: Simple but Crucial
The main objective behind using conjoint analysis is to find out what combination of a limited number of attributes influences decision making most. It is tested by marketing research companies directly on people.
Analytics
Correlation is not causation :Essential Dose
"just because two things correlate does not necessarily mean that one causes the other... correlation is not causation"
Analytics
Logistic regression
Logistic regression is used when the measure on the predicted variable is dichotomous. Logistic regression is the more flexible technique because it makes no assumptions about the nature of the relationship between the independ...
Analytics
A Brief Encounter with Principal Components Analysis
Principal Components Analysis is a method that reduces data dimensionality by performing a covariance analysis between factors. As such, it is suitable for data sets in multiple dimensions. PCA is recommended as an exploratory ...
Analytics
Structural Equation Modelling: How much is fit enough?
There are some major indicators which determine the fitness of a SEM. Main indices are: goodness-of-fit index (GFI), adjusted goodness-of-fit index (AGFI), root mean squared residual (RMR) and root mean squared error of approxi...
Analytics
Structural Equation Modeling:What does it mean to be fit?
Technically speaking model fit determines the degree to which the sample variance covariance data fit the structural equation model. Model fit criteria commonly used are chi-square (x2), the goodness-of-fit index (GFI), the adj...
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