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65 articles for “statistically robust”
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A Critical Review of the Limitations of the Arithmetic Mean and the Robustness of the Median in Statistical Analysis
Abstract: Arithmetic mean is an extremely popular measure of central tendency used in statistical analyses, primarily because it is so easy to calculate and has many positive mathematical characteristics. However, when there are outliers, skewed distributions or heterogeneous spread of data, the reliability of the arithmetic mean diminishes greatly. This paper includes a critical review of the limitations of the arithmetic mean and an assessment of the robustness of the median …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 16, Issue 2, 2026 · pp. 21–29 Read article
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Some Aspects of the Vagaries in the Pattern of Meteorological Parameters in the State of Rajasthan in Association with the LULC Change
Abstract: Present work examined the role of the change in land use and land cover (LULC) in altering the rainfall and temperature pattern over the western part of the Rajasthan, India. For this purpose, the high-resolution gridded rainfall and surface temperature data sets prepared by IMD (India Meteorological Department) and Climatological Research Unit Time Series (CRU TS 3.21) have been utilized. An increase in surface temperature and decrease in rainfall for …
Published in Journal of Remote Sensing & GIS · Vol. 8, Issue 1, 2017 · pp. 53–65 Read article
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Robust Quadratic Discriminant Rule using Comedian
Abstract: Discriminant analysis aims to get rules that separate the groups of observations. Moreover, it can be used to classify new observations into one of the known groups. The classical discriminant techniques are based on the classical estimates of mean vector and variance covariance matrix. Unfortunately, these classical estimates are highly influenced by the extreme observations and hence any analysis based on these estimates will provide misleading results when the data …
Published in Research & Reviews : Journal of Statistics · Vol. 8, Issue 2, 2019 · pp. 41–47 Read article
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A Comprehensive Review of Statistical Analysis Techniques in Economic Data Studies
Abstract: Statistical analysis plays a key role in the field of economics, enabling scientists to extract meaningful information from large and complex data sets. It is essential for forming policies, comprehending market movements, and forecasting future economic scenarios. Choosing the right statistical analysis tools is crucial for gaining useful insights from economic data in this era of expanding data availability. Robust statistical analysis methods further increase the credibility and reliability of …
Published in Research & Reviews : Journal of Statistics · Vol. 12, Issue 2, 2023 · pp. 42–48 Read article
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Robust Regression Models for Identifying Outliers in Medical Data
Abstract: Before applying any multivariate statistical analysis, it is important to determine whether outliers are present in the dataset. In regression analysis, the presence of outliers in the dataset can strongly mislead the classical least squares estimator and lead to unreliable results. In this paper, we prove the minimum covariance determinant estimator, which is commonly applied in a robust statistic to estimate location parameters and multivariate scales. These ideas can be …
Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 1, 2018 · pp. 69s–76s Read article
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Stock Market Analysis Using Data Science
Abstract: Stock market prediction using data science has become a popular area of research and application in recent years. This is because the stock market is a complex system with many variables and factors that affect its behavior, making it difficult to predict with certainty. The stock market has always been the aggression of buyers and sellers of stocks, therefore in the global finance market, stock trading is one of the …
Published in E-Commerce for Future & Trends · Vol. 11, Issue 1, 2024 · pp. 1–4 Read article
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Principal Component Analysis for Outlier Detection
Abstract: Principal Components Analysis (PCA) is one of the well-known and frequently used multivariate exploratory data analyses. PCA is concerned with analyzing and understanding data in high dimensions, that is to say, PCA method analyzes data sets that represent observations which are identified by several dependent variables that are inter-correlated. Multidimensional scaling (MDS) is a technique that makes a map displaying the comparative attitudes of a number of objects or cases, …
Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 1, 2018 · pp. 62s–68s Read article
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Structure–Property Modeling of Cement-Based Multi-Component Composites Using Ensemble Machine Learning and Explainable Feature Attribution
Abstract: Accurate prediction of compressive strength is central to structure–property optimization, quality control, and sustainability-driven design in cement-based composite materials. Cementitious systems represent heterogeneous multi-phase composites composed of reactive binder matrices and dispersed aggregate phases, whose macroscopic mechanical performance emerges from complex nonlinear interactions among constituents and curing-dependent microstructural evolution. This study develops a data-driven structure–property modeling framework to quantify the nonlinear dependence of compressive strength on multi-component composite composition and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 112–131 Read article
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Enhancing Secure Communication Through Hybrid Steganography and Public Key Cryptography
Abstract: This research pioneers an innovative paradigm in secure data communication by seamlessly merging Public Key Digital Image Steganography with public key cryptography. The proposed method leverages the formidable strength of the RSA algorithm, employing a robust 1024-bit key size for secure data encryption. In parallel, the imperceptibility of the F5 steganographic technique is harnessed to clandestinely embed the encrypted message within a cover image. Unlike conventional methods, our scheme introduces …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 10, Issue 3, 2023 · pp. 38–46 Read article
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Statistical and AI Approaches to Measure Sustainability Performance of Enterprises
Abstract: Measuring sustainability performance has become a critical priority for enterprises facing increasing regulatory pressure, stakeholder expectations, and global sustainability challenges. Traditional assessment methods, largely based on static indicators and manual reporting, often struggle to capture the multidimensional, dynamic, and data-intensive nature of sustainability. This study explores the integration of statistical and artificial intelligence (AI) approaches to evaluate and enhance the sustainability performance of enterprises in a more robust, accurate, and …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 30–36 Read article
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An Alternative Robust Measure of Outlier Detection in Univariate Data Sets
Abstract: A univariate outlier is a data point that consists of an extreme value on one variable. Here we applied two types of outlier detection methods: one is graphical and another is analytical. This paper presents graphical methods for different statistical outlier detection such as scatter diagram, box plot and normal probability plot. Furthermore, the quantitative methods for outlier detection in this paper are the IQR method, SD method, Z-score method, …
Published in Research & Reviews : Journal of Statistics · Vol. 8, Issue 1, 2019 · pp. 1–11 Read article
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Evaluating an ai-supported experiential learning intervention: a quasi-experimental study of the joyful saturday model for student engagement and holistic development
Abstract: Student disengagement, declining academic motivation, and passive classroom participation remain major challenges in modern higher education systems. Traditional lecture-based teaching methods often fail to accommodate diverse learning styles and do not sufficiently promote active participation or collaborative learning. To address these challenges, the present study evaluates the effectiveness of Joyful Saturday, a structured experiential learning initiative designed to improve student engagement, motivation, and holistic development through interactive academic activities supported …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 79–88 Read article
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A Statistical Approach Noise Tolerant Texture Classification
Abstract: A simple, efficient, yet robust multi resolution approach to texture classification binary rotation invariant and noise tolerant. The proposed approach is very fast to build and very compact while remaining robust to illumination variations, rotation changes, and noise. We have developed a novel and simple strategy to compute a local binary descriptor based on the conventional local binary pattern (LBP) approach, preserving the advantageous characteristics of uniform LBP. Points are …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 3, Issue 2, 2016 · pp. 14–19 Read article
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A Robust Automatic Algorithm for Extraction of Blood Vasculatures from Retinal Images
Abstract: AbstractIn this proposed algorithm, an efficient method for extraction and segmentation of blood vasculatures from the retinal eye images is proposed. For finding the features and abnormalities like Fovea, macula, Red lesions and exudates, blood vasculature extraction is one of the most important steps. The proposed algorithm uses tactical combination of Green, L and Y channel of Retinal image, which gives a more accurate and efficient result than the single …
Published in Recent Trends in Programming languages · Vol. 6, Issue 2, 2019 · pp. 1–7 Read article
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QSAR Studies of 3-(4-(3-(Substitutedphenyl) Acryloyl) Phenyl)-2-Substituted phenyl/Phenylthiazolidin-4-ones for Anticancer Activity
Abstract: Both, Chalcone and 4-thiazolidinone, are therapeutically significant organic moieties with anticancer activities. QSAR (Quantitative structure–activity relationship) studies of ten synthesized chalcone-thiazolidinone hybrids have been described for anticancer activity against three cancer cell lines: A-549 (Human lung adenocarcinoma), U-87 MG (Human glioblastoma cancer cells) and COLO-205 (Human colon cancer cells). The developed linear QSAR models have significant statistical quality showing good fitting ability and robustness. The Q2 and R2 values of …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 3, Issue 3, 2016 · pp. 16–22 Read article
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QSAR Studies on Schiff Bases of Pyrrole-2-Carboxaldehyde for Antimicrobial Activity
Abstract: Pyrrole and Schiff bases are therapeutically significant organic moieties. QSAR (Quantitative structure-activity relationship) studies of thirteen pyrrole-2-carboxyaldehyde Schiff bases have been described for antimicrobial activity against S. epidermidis, E. coli and S. aureus. Described 2D QSAR models are statistically significant models with good fitting ability and robustness. The Q2 value is more than 0.5 for all discussed models which confirms the internal predictive power of the derived QSAR equations. Molecular …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 3, Issue 3, 2016 · pp. 1–8 Read article
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A Review on Parametric Optimization of WEDM Technique for OHNS Steel
Abstract: In this study, the Wire Electrical Discharge Machining (WEDM) process for OHNS (Oil Hardened Non-Shrinking) steel, a high-performance material frequently used in the production of dies, punches, and precision tooling components, is optimized parametrically and validated experimentally. A continuously moving wire electrode and a sequence of electrical discharges are used in WEDM, a non-traditional machining method, to erode material and produce intricate and precise profiles, particularly in materials that are …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 29–35 Read article
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Reducing the Uncertainty of Marine Accidents Failure Rate in Harsh Environment; Using Bayesian Theory
Abstract: The interest in arctic activities is strong, but has not led to significant quantifying analysis over the fact of finding rescannable failure rate. To attract investors and promote the development of a marine industry, a clear concept of project risk is paramount; in particular, issues relating to human role in operation are critical. In the public domain, reliability of information is often scarce or inappropriate for such environment. Also, an …
Published in Journal of Industrial Safety Engineering · Vol. 3, Issue 2, 2016 · pp. 30–39 Read article
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Statistical Modeling for Weld Quality Assessment using AI SAW Welding of Mild Steel
Abstract: The main issue to the industries that apply Submerged Arc Welding (SAW) is quality assurance since the structural integrity dictates safety and the performance of the industry. The existing system of checking manuals is not only time consuming but also has human errors that make it mandatory to deploy automated intelligent systems. This study carries out an extensive comparison of the leading approaches based on the use of Artificial Intelligence …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 892–907 Read article
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Statistical Methods in Law: Analysing Trends and Patterns in Judicial Outcomes
Abstract: The research paper explores the integration of statistical techniques within the domain of legal science, emphasizing their role in assessing and interpreting ongoing trends. By employing methods such as descriptive statistics, inferential statistics, and multivariate analysis, the study highlights how empirical data can effectively uncover disparities in areas like sentencing practices, risk assessments, and the evaluation of policy outcomes. These statistical tools enable researchers and legal professionals to identify patterns, …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 32–36 Read article