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Deb2024

Debashis2024

Recently Published

Resampling and Latent-Variable Computation in R (Bootstrap, jackknife, EM)
Bayesian Statistical Inference for Basic Science:part 0
Statistical Inference and Hypothesis Testing for Basic-Science Data Science
Bayesian Statistical Inference: Probability, Posterior Thinking, Simulation Verification, and Astronomical Applications Part 2
Bayesian Statistical Inference: Probability, Posterior Thinking, Simulation Verification, and Astronomical Applications
From Simple Game Theory to Decentralized GW Follow-up Scheduling
Operations Research and Game Theory for Electromagnetic Follow-up of Gravitational-Wave Events
particle filter 2
pARTICLE FILTER 1
Measure-Theoretic Probability, Entropy, Maximum-Entropy Models, and the Philosophy of Bayesian Inference
Measure-Theoretic Probability, Entropy, Maximum-Entropy Models, and the Philosophy of Bayesian Inference
Statistical Inference and Data Science for Basic Sciences: basics & Motivation 1
Statistical Inference and Data Science for Basic Sciences: basics & Motivation 1
Bayesian + ML for Scientific Data Science, Part 2
Bayesian Inference Meets AI/ML in Natural-Science Data
Multiple Linear Regression: Theory, Geometry, Computation and Diagnostics
TIME SERIES PRACTICAL + ASSIGNMENTS 8 QUESTIONS
SQC Practical Chart Only (set AB+Theory)
SQC Practical set AA (easy version) 2026
SQC Practical Set A easy 2026
SQC Practical Set A
Time Series Practical part 2
Time Series Practical Part 1
Modelling Dynamic Processes under the Confluence of Statistics, Data Science and Machine Learning
parametric Bootstrap with Boot
Jackknife Bootstrap practical
Monte Carlo, Gibbs, MH & MCMC Basics practical part 1
Monte Carlo to MCMC Part 1
Understanding Gibbs
MCMC Methods: Gibbs Sampling & Metropolis–Hastings
Contingency Tables, GLMs, Logistic/Poisson, Log–Linear, and EM 1
Paleoclimate Inferences (Real Data 1: Greenland Summit Firn‑Air Case Study)
Quantitative Paleoclimatology: Advanced Statistics & Machine‑Learning Hands‑On(part 1)
deciphering the paleoclimatic condition using statistics Part 1
ML Techniques with R part 3: Cluster Analysis
ML Techniques with R Part 2
ML Techniques with R Part 2: Lazy Learning: k-Nearest Neighbors (k-NN)
ML Techniques with R Part 1
Another Recap of Parametric Hypothesis Tests & Why Non-Parametric Tests?
Recap of Parametric Hypothesis Tests & Why Non-Parametric Tests 2025
Kruskal-Wallis Test: Nonparametric Statistical Tests 2025
Mann-Whitney U Test (Nonparametric Statistical tests 2025 )
Wilcoxon Signed-Rank Test: Non-Parametric Hypothesis Test:
Sign test (Nonparametric Hypothesis test) lecture Note 2025
Practical (Nonparametric Hypothesis test )(Spearmans rank Correlation based Test)2025
Nonparametric Hypothesis test Lecture note 2025 (Chi Square test)
'Geostatistics with R: Directional Statistical Preliminaries with R'
'Geostatistics with R: Directional Statistical Preliminaries with R'
Geostatistics with R: Clustering part 2 (Advanced Clustering)
Geostatistics with R: Clustering part 2 (Advanced Clustering)
Geostatistics with R: Clustering Technique Part 1 (K Means)
Geostatistics with R: Spatial Data Fundamentals with R
Geostatistics with R: Spatial Data Fundamentals with R
Paleo doc 1