DataScience
Repository for R Shiny app: https://katerina-pap.shinyapps.io/MA-cont-prepostES/
My portfolio of algorithms I used to analysize various shapes and forms of data with statistical and machine learning tools.
Time Series Model, Simple Linear Regression Model, Multiple Linear Regression Model, Polynomial Regression Model,Logistic Regression Model
Anova and Ancova with Kruskal-Wallis test to check the relationship between independent and dependent variables on bike rental history..
Models parcel prices across Pittsburgh to isolate the effect of location by controlling for parcel characteristics. Uses WLS regression and ANCOVA to estimate adjusted prices, then links price variation to crime, school quality, and geography.
Exploratory and Statistical analysis of FIFA-19 Football player's wage
Project files for randomized block design analysis with ANCOVA.
Efficacité d'une thérapie cognitivo-comportementale dans le traitement du syndrome de Gilles de la Tourette avec symptomatologie TDAH comorbide
This contains the schoolwork of statistical data analysis at HKU, including Boston Housing Price Analysis and a condensed R code for the course materials
Endotype-aware GWAS pipeline using ANCOVA to detect subtype-specific genetic variants. Discovery in CAMP and validation in GACRS childhood asthma cohorts.
A literature review of all the papers on how (not) to measure changes from a baseline or other comparison in a pre-post design.
Wine dataset statistical analysis using Hypothesis testing (F-test, T-test, ANOVA, ANCOVA). Using machine learning to predict wine quality. Using regularization with 10 fold cross validation to overcome overfitting. Created different visualizations on the dataset.
This repository contains the R code done in the laboratories during the first course of statistical models.
Curso de Regression Models do Coursera
Associação entre artrose e alteração de ângulos espino-pélvicos em pacientes com impacto femoroacetabular
Analysis of survey data collected by M. Weisend in the Thar Desert, India. Includes example analysis using stepwise regression and ANCOVA.
solving problems with data analysis, hypotheses and the most used statistical tests in ecology
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