Tigramite is a time series analysis python module for linear and information-theoretic causal inference. Version 3.0 described in http://arxiv.org/abs/1702.07007 is available at https://github.com/jakobrunge/tigramite!
Less than 4% of women believe they are beautiful, according to a 2011 Dove study. Beauty standards are set by unrealistic portrayals of women in the media. We are designing an experiment to determine if changing the models shown in an advertisement will cause a change in how beauty is perceived.
This is for Econometrics and other Economics related materials
Survey design, causality study and statistical analysis
MATLAB module for assessing the causal links between time series
Mendelian Randomization with Biomarker Associations for Causality with Outcomes
Causal Analysis Experiment of Academic Paper's Title length on Number of Citation
In this project, the causal effect of working overtime on attrition for a sample of IBM employees has been analyzed
This project contains the implementation of the Dimensional Causality method proposed in Bayesian inference of causal relations between dynamical systems (Benkő, Zsigmond ; Zlatniczki, Ádám* ; Stippinger, Marcell* ; Fabó, Dániel ; Sólyom, András ; Erőss, Loránd ; Telcs, András** ; Somogyvári, Zoltán; https://doi.org/10.1016/j.chaos.2024.115142)
Causal Relation Extraction and Identification using Conditional Random Fields
Conducted an experiment to assess the impact of music on cognitive function through the performance of activities that require logical reasoning
💊 Comparing causality methods in a fair and just way.
IT Security Algorithm Bias Analysis
Predicting whether Insurance claims will accepted or rejected for online Travel Agencies
Is cigarette smoked per day a factor in determining whether a patient suffers from Coronary Heart Disease? In this analytical study, we can conclude the consistent evidence supporting a causal role of smoking in causing coronary heart disease. Thus establishing a causal relationship between the two.
Causal Inference Using Quasi-Experimental Methods
Causal analysis and inference using observational and interventional dataset. It contains tools for graph structure recovery.
Conducting one-factor analysis of variance and its assumptions (normality and homogeneity of variance) with R if two groups of data show statistically different behavior. Visualizing data with boxplots to understand if the given state of the fly (fed/starved) affects the feeding and resting pattern.
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