All articles by Priya Chetty

Executing cost DEA of banks using Data Envelopment Analysis Program (DEAP)

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). Cost efficiency test helps to improve in cost related performances of the organization and shows if the organization should lower or increase the inputs. Read more »

How to detect outliers in a dataset?

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.  They represent a large variation across a data set. Presence of an outlier in data sets confirms that one or more than one of all the observations starkly differs with other observations. Read more »

Solution for non-stationarity in time series analysis in STATA

The previous article based on the Dickey Fuller test established that GDP time series data is non-stationary. This prevented time series analysis from proceeding further. Therefore, in this article possible solution to non-stationarity is explained. Read more »

How to conduct generalized least squares test?

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. Ordinary Least Squares (OLS) method only estimates the parameters in linear regression model. Also, it seeks to minimize the sum of the squares of the differences between the observed responses in the given dataset and those predicted by a linear function. Read more »

How to apply linear discriminant analysis?

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.  Linear discriminant analysis allows researchers to separate two or more classes, objects and categories based on the characteristics of other variables. It is a classification technique like logistic regression. However the main difference between discriminant analysis and logistic regression is that instead of dichotomous variables, discriminant analysis involves variables with more than two classifications. Read more »

Malmquist productivity Index test of healthcare sector in India and interpretations

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. This article will present the interpretations of productivity index from Malmquist Data Envelopment Analysis (DEA). Read more »

How to perform cluster analysis?

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. Therefore, it tries to identify homogenous groups of cases. Read more »

How to apply logistic regression in a case?

Machine learning involves solutions to predict scenarios based on past data. Logistic regression offers probability functions based on inputs and their corresponding output. In short, the dependent variable is a classification variable.

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