IntroductionHuman Resource Management (HRM) is a strategic and systematic approach to managing an organization’s most valuable asset—its people. The primary objective of HRM is to optimize employee performance in alignment with the organization’s overall goals. It encompasses a broad spectrum of functions, including recruitment, training, compensation, performance evaluation, and employee relations, all designed to ensure…
Linear programming (LP) is a mathematical technique used to optimize a linear objective function, subject to a set of linear constraints. Two primary methods for solving LP problems are the graphical method and the simplex method. While both aim to determine the optimal solution, they differ significantly in terms of applicability, scalability, and methodological approach.…
IntroductionInterval estimation is a statistical technique used to estimate population parameters—such as the mean or proportion—by providing a range of values, called a confidence interval, within which the true parameter is expected to lie with a specified level of confidence. For large sample sizes (generally n≥30n \geq 30n≥30), the normal distribution (z-distribution) is employed to…
Introduction Statistical estimation methods are broadly categorized into point and interval estimation. While point estimation provides a single value as an estimate of a population parameter, interval estimation offers a range of plausible values, allowing for more informed and reliable inferences. Within this context, confidence intervals serve as a widely used and informative form of…
IntroductionEstimation is a fundamental aspect of inferential statistics, involving the use of sample data to make informed inferences about unknown population parameters. This process enables researchers to draw conclusions about entire populations based on the analysis of smaller, representative samples. Within this framework, key concepts include estimators, estimates, and point estimates. 1. EstimationEstimation refers to…
IntroductionOption valuation in the field of probability and statistics involves determining the fair value of an option contract using mathematical models. These models incorporate various parameters such as the underlying asset’s price, strike price, time to expiration, volatility, and prevailing interest rates. Grounded in probability theory, these methodologies estimate the likelihood of an option expiring…
IntroductionValue at Risk (VaR) and Conditional Value at Risk (CVaR) are fundamental statistical tools employed in the field of finance for the measurement and management of risk. These metrics are particularly significant in evaluating credit risk and valuing financial derivatives such as options. While VaR estimates the potential maximum loss over a specific time horizon…
In the study of probability and statistics, the Binomial, Poisson, and Normal distributions represent three fundamental types of probability distributions, each serving distinct purposes based on the nature of the random variable being modeled. Understanding these distributions is essential for analyzing various types of data and for making predictions under uncertainty. Binomial Distribution The Binomial…
In the field of probability and statistics, the expected value (also known as the mean) and the standard deviation are fundamental concepts used to describe the behavior of a random variable. While the expected value indicates the central tendency or the average outcome over numerous trials, the standard deviation measures the degree of variability or…
The Reserve Bank of India (RBI) has periodically issued comprehensive guidelines and instructions to banks to promote the flow of credit to Scheduled Castes (SCs) and Scheduled Tribes (STs). In order to facilitate greater participation of SC/ST beneficiaries in availing credit facilities, it is imperative to enhance awareness of various schemes through effective communication strategies…