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The Structural and Functional Interrelationship between Human Resource Management and Human Resource Development

Introduction Human Resource Management (HRM) and Human Resource Development (HRD) are two distinct yet closely interconnected domains within an organization. While HRM emphasizes the strategic and operational management of the workforce—encompassing areas such as recruitment, compensation, and performance management—HRD is primarily concerned with enhancing employees’ skills, knowledge, and capabilities through structured learning and development initiatives.…

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Foundations of Human Resource Management

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…

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Comparative Analysis of the Graphical and Simplex Methods for Solving Linear Programming Problems

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.…

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Interval Estimation of the Mean and Proportion from Large Samples

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…

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Understanding Interval Estimation and Confidence Intervals in Statistical Inference

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…

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Understanding Estimation in Statistics: Estimators and Point Estimates

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…

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