Journal of Business Analytics and Data Visualization (e-ISSN: 2584-1637)

A Study of Bullion Market Behaviour with Special Reference to Gold and Silver

Meghna Jain — 2026-05-21

Investment in precious metals has always been considered important, and people make investments in gold and silver for the long term. Investment in precious metals acts as a safe form of investment, like safety against inflation till civil conflict. There are many reasons which have invested in precious metals as an important part of an investor’s portfolio. Gold and silver are considered to be precious metals, and during previous times, people used to invest in buying jewellery made up of these precious metals, and now they are investing in gold bars, gold and silver coins and even invest in electronic forms. The research design in this study is analytical in nature. The study has considered bullion commodities, i.e. gold and silver. The period in this study is 2021 to 2025. The study further compared gold with its variants and silver with its variants using ANOVA and identified differences in their trading behaviour.

Prediction of House Prices using Correlation and Simple Linear Regression

Dipali Tupe — 2026-06-10

Predicting house prices correctly is very important in real estate, city planning, and financial decision-making. This study uses simple statistical tools—correlation and multiple linear regression—to understand and estimate residential property prices. The main aim is to examine how different factors such as house size, number of bedrooms, building age, distance from the city centre, and neighbourhood quality affect the price of a house. First, correlation analysis is used to measure how strongly each factor is related to house prices. This helps identify which variables have a meaningful impact and which ones do not contribute much. The analysis shows that larger houses and better neighbourhoods are usually linked with higher prices. On the other hand, older houses and properties located farther from business areas tend to have lower prices. These results help us better understand what drives property values in the market. After identifying the important factors, a multiple linear regression model is developed to predict house prices. This model calculates how much each factor changes the price while keeping the other factors constant. The performance of the model is tested using measures such as R-squared and residual analysis to check how accurate and reliable the predictions are. Overall, the study shows that regression models, supported by correlation analysis, can explain a large portion of the differences in house prices. Even though linear regression cannot capture every complex market behaviour, it is simple, easy to understand, and efficient for estimating property values. The findings highlight that both property features and location play a major role in determining house prices and show how statistical methods can support better real estate decisions.

Bridging the Educational Divide: A Case Study of Kerala’s ‘Key to Entrance’ AI-Driven Coaching Initiative

AMAL GEORGE — 2026-06-18

This case study assesses the ‘Key to Entrance’ program, a historic project by Kerala Infrastructure and Technology for Education (KITE) inaugurated in February 2026. As India’s first state-led, massive-scale deployment of Artificial Intelligence (AI) for competitive exam tutoring, the program delivers free, high-quality preparation to approximately 800,000 students in public schools. The concept addresses a crucial "coaching divide," where high-cost private preparatory centers typically exclude children from poor backgrounds despite their academic prowess. By incorporating the Samagra AI Learning Room, the program changes from traditional passive instruction to a personalized, data-driven pedagogy. The AI system operates as a digital mentor, leveraging predictive analytics to track student performance and develop Personalized Study Plans (PSP) based on individual learning paces. A major element is Adaptive Testing, which provides questions across three difficulty tiers—Beginner, Intermediate, and Excellent—tailored to a student's unique aptitude. The curriculum encompasses Science, Commerce, and Humanities streams, encompassing subjects like Physics, Accountancy, and Political Science, with a second phase adding English and Reasoning. To ensure 100% inclusivity, KITE implements a multi-channel delivery approach, including the KITE VICTERS TV channel and mandates for school principals to provide digital facilities for students lacking personal devices. The system includes gamification through Activity Badges and offers teachers an Exam Statistics dashboard for targeted support. This effort serves as a global roadmap for Responsible EdTech, proving that state-managed AI may democratize access to professional higher education based on merit rather than socioeconomic position.