Our lab specializes in advanced data analysis, optimization techniques, and statistical modeling. We utilize cutting-edge methods in decision-making, predictive analytics, and optimization to solve real-world problems efficiently.
Lab Admin Team
Lab Incharge:
Chandrasekar Raja, Core Scientist
Lab Staff:
Ramya Sharma, Associate Scientist
Nathiya Murali, Associate Scientist
Data Analysis Techniques Conducted in Our Lab
MCDM Techniques
Weight Allocation Methods:
Mean Weight Method, Standard Deviation Method, Entropy Method, AHP Method, CRITIC Method, Best-Worst Method.
Other MCDM Methods:
Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Complex Proportional Assessment (COPRAS), Evaluation Based on Distance from Average Solution (EDAS), Elimination and Choice Expressing Reality (ELECTRE), Decision-Making Trial and Evaluation Laboratory (DEMATEL), Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE), Vise Kriterijumska Optimizacija i Kompromisno Resenje (VIKOR), Grey Relational Analysis (GRA), Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA), Additive Ratio Assessment Method (ARAS), Weighted Product Method (WPM), Weighted Sum Method (WSM), Weighted Aggregated Sum Product Assessment (WASPAS), Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS), and Fuzzy Additive Ratio Assessment Method (Fuzzy ARAS).
SPSS (Statistical Package for the Social Sciences)
Descriptive Statistics:
Frequency Distribution, Measures of Central Tendency (Mean, Median, Mode), Measures of Dispersion (Variance, Standard Deviation, Range), Crosstabs.
Inferential Statistics:
t-Test (Independent, Paired), ANOVA (One-Way, Two-Way, MANOVA), Chi-Square Test (χ² Test), Correlation (Pearson, Spearman), Regression Analysis (Linear, Multiple, Logistic).
Non-Parametric Tests:
Mann-Whitney U Test, Wilcoxon Signed-Rank Test, Kruskal-Wallis Test, Friedman Test.
Factor and Reliability Analysis:
Principal Component Analysis (PCA), Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), Reliability Testing (Cronbach's Alpha).
Multivariate Analysis:
Cluster Analysis, Discriminant Analysis, Multidimensional Scaling (MDS), Structural Equation Modeling (SEM).
Time Series & Forecasting:
ARIMA, Exponential Smoothing, Trend Analysis.
Data Reduction & Transformation:
Data Imputation, Normalization & Standardization, Dummy Variable Creation.
Optimization Techniques (in Jupyter Notebook)
Algorithms:
OLS Regression, Polynomial Regression with Ridge Regularization, Lasso Regression, Elastic Net, Bayesian Ridge Regression, Decision Tree Regressor, Random Forest Regression, Gradient Boosting Regressor, XGBoost Regressor, AdaBoost Regression, Support Vector Machines, Gaussian Process Regressor, MLP Regressor, Multivariate Polynomial Regression.
A Glimpse into Our Lab
