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is project undertaken to fulfil the internship requirement as Data Science Intern at Institute of Data Engineering, Analytics and Science Foundation - Technology Innovation Hub, Indian Statistical Institute

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samyaroy/Multivariate_Analysis_of_Career_Preference_in_Kolkata

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Multivariate_Analysis_of_Career_Preference_OP07

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Abstract

This project investigates the factors shaping academic and career preferences of college students in Kolkata, a critical issue in India’s evolving education-to-employment landscape shaped by the Fourth Industrial Revolution. The study is based on a primary dataset of 186 valid survey responses, capturing demographic, academic, financial, familial, and perceptual attributes of students aged 18–25. Exploratory Data Analysis revealed a predominance of middle-income households, balanced gender representation, and strong clustering of students in science and technology disciplines. Bivariate and multivariate analyses highlighted clear associations between degree choice and expected salary, moderate intergenerational effects of parental occupation on sectoral preferences, and consistent academic performance across school levels. Multicollinearity among academic indicators was diagnosed through VIF and resolved via Principal Component Analysis, while non-normality in perceptual variables was addressed with non-parametric approaches such as Kruskal–Wallis and Dunn’s post-hoc tests. Findings demonstrate that structural academic trajectories and parental sectoral backgrounds exert greater influence on career expectations than gender or income, while external influences such as peers and social media remain relatively uniform across groups. The study thus underscores the need for data-informed counselling and policy frameworks that strengthen student agency in academic decision-making and reduce institutional imbalances.

License: CC BY-NC 4.0

This project is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).

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Full license text: https://creativecommons.org/licenses/by-nc/4.0/legalcode

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is project undertaken to fulfil the internship requirement as Data Science Intern at Institute of Data Engineering, Analytics and Science Foundation - Technology Innovation Hub, Indian Statistical Institute

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