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Se realiza un análisis estadístico descriptivo de datos obtenidos en 3 viñedos diferentes con el objetivo de encontrar diferencias y relaciones entre las variables medidas, para concluir las características del vino de cada viñedo.
This repository contains a project I completed for an NTU course titled CB4247 Statistics & Computational Inference to Big Data. In this project, I applied regression and machine learning techniques to predict house prices in India.
Here I have collected two scripts written in Python and SQL, designed for analyzing data related to physiological parameters derived from experimental measurements. These tools were created to expedite the statistical analysis process, extracting and sorting data from tabular-format datasets, in my specific case studies.
Explore multivariate statistics through hands-on university projects. Each project delves into real-world datasets, applying statistical techniques like ANOVA, two-factor analysis, and binary logistic regression. Understand data analysis, interpretation, and modeling with R.
The data, R programming, and outputs for the research paper testing glucose consumption and cognitive factors. I used R to clean, process, model, and visualize the data. The outputs folder contains the finished products. Link to paper pending.
Gain hands-on experience with ANOVA analysis, understanding its assumptions, and applying it to real-world datasets to understand differences among group means.
Executed Regression modelling, hypothesis testing and statistical analysis to predict factors affecting credit card balances in a firm. Tools & technologies: ANOVA, p-value, R square
Regression models for predicting customer acquisition costs (CAC) and the effectiveness of univariate and lasso feature selection techniques in improving the accuracy.