Category: Learning modules

By Avishek Majumder & Priya Chetty on October 25, 2018 No Comments

This article focuses on the application and interpretation of non-metric Multidimensional Scaling (MDS) method Michigan-Nijmegen Integrated Smallest Space Analysis (MINISSA) in Hamlet II.

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By Avishek Majumder & Priya Chetty on October 25, 2018 No Comments

Non-hierarchical cluster analysis is the next step to a hierarchical cluster model. It allows the partitioning of the similar matrices into equal numbers of clusters. It also creates a list of the partitions from the similar matrix generated in the hierarchical cluster.

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By Avishek Majumder & Priya Chetty on October 24, 2018 No Comments

Hamlet II is an approach to quantitative text-based analytical software. This article reviews the difference between them and Hamlet II. The table below presents various text-based analytical software available commercially.

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The problem of multicollinearity arises when one explanatory variable in a multiple regression model highly correlates with one or more than one of other explanatory variables. It is a problem because it underestimates the statistical significance of an explanatory variable (Allen, 1997).

 
By Avishek Majumder & Priya Chetty on October 24, 2018 No Comments

This article talks about the application of Singular Value Decomposition (SVD) technique MDPREF using Hamlet II. It is performed on the same matrix of profiles or context units saved while performing joint frequency analysis.

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By Rashmi Sajwan & Priya Chetty on October 22, 2018 7 Comments

This article shows a testing serial correlation of errors or time series autocorrelation in STATA. Autocorrelation problem arises when error terms in a regression model correlate over time or are dependent on each other.

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By Avishek Majumder & Priya Chetty on October 22, 2018 No Comments

Correspondence analysis is a diagnostic tool which helps to present the content of a single text or the context unit profiles containing the joint frequency.

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By Avishek Majumder & Priya Chetty on October 22, 2018 No Comments

Hierarchical clustering uses methods to segregate the texts according to the similar vocabularies and then similar words or context are clustered together.

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