Category: Learning modules

By Avishek Majumder & Priya Chetty on December 24, 2017 1 Comment

In the previous article, discussed and interpreted the findings of cost efficiency using constant returns to scale (CRS) Cost Data Envelopment Analysis (DEA).

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By Avishek Majumder & Priya Chetty on December 23, 2017 No Comments

The cost efficiency analysis or cost data envelopment analysis or cost DEA is evaluated when information on prices and costs are available from the source of the data collected for input and output variables (Cooper, Seiford, & Zhu, 2011).

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By Priya Chetty on December 23, 2017 1 Comment

Outliers are those data points which are distant from the other observations in the data set. They can be either because of the variability in the data set or due to measurement errors.

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By Divya Narang & Priya Chetty on December 20, 2017 17 Comments

The previous article based on the Dickey-Fuller test established that GDP time series data is non-stationary.

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By Riya Jain & Priya Chetty on December 17, 2017 1 Comment

In statistics, Generalized Least Squares (GLS) is one of the most popular methods for estimating unknown coefficients of a linear regression model when the independent variable is correlating with the residuals.

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By Priya Chetty on December 13, 2017 1 Comment

Linear discriminant model is a multivariate model. It is used for modeling the differences in groups. In this model a categorical variable can be predicted through continuous or binary dependent variable.

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By Avishek Majumder & Priya Chetty on December 6, 2017 No Comments

Malmquist productivity index evaluates the efficiency change over time as mentioned by Färe, Grosskopf, & Margaritis, (2011). However, Malmquist productivity index literature has been uneven with some authors assuming constant returns to scale and others allowing for variable returns to scale.

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By Priya Chetty on December 5, 2017 No Comments

While many statistical methods in machine learning are used either to predict or analyse trends in the data, cluster analysis is used for organizing the data. It is a process of grouping observations of similar kinds within a large population.

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