Heart disease prediction with logistic regression using SAS Studio. The dataset is taken from UCI Machine Learning about heart disease.

A credit scoring model to predict credit worthiness of an individual based on demographics, loan size and credit history using logistic regression.

Loan eligibility prediction in Lasiandra Finance Inc. (LFI) using SAS studio.

Performed statistical analysis and modelling using Linear Regression, Logistic Regression and ANOVA on short-term property rentals data set with SAS

Classified the restaurants into two tiers based on their user ratings. Used Random Forest to predict the Important Attributes which contribute to the success rate of a Restaurant. Used logistic regression to predict which tier has better success rate based on certain attributes using SAS.

logistic model to predict whether an individual’s annual income is above 50000

Used R package kmlshape to create novel cluster analysis which monitors and examines omicron curve peaks in LTC facilities. Conducted bootstrapping to account for instability. Then used logistic regression to assess the association between high and low peak COVID infection clusters

This code uses SAS for exploration of data and to identify possibility of back orders in supply chain using Logistic Regression

Testing carpet samples for chemical compounds to determine their age using SAS. Dataset can be found in the README file.

KeepCoding Bootcamp Big Data & Machine Learning - Práctica Advanced Data Mining

Performed Logistic Regression on two different (Movie's Rating and Insurance claim) dataset. Explored statistical significance of various variables with respect to the target variable.

My senior honors project investigating the rise of authoritarianism in the 21st century

Study based on segmentation, linear regression and logistics regression using SAS and R.

Worked on building a predictive model by considering multi collinearity and applying regression technique as well as other machine learning concepts related to  factors or variables using SAS programming. 

SAS code for prediction of development of Coronary Heart Disease

Developing an unbiased probability model that deems profitable to a mobile app creator in terms of identifying right customers who would install the app while minimizing advertising costs

A Predictive Analysis of H1B Dataset using both supervised and unsupervised learning

Marketing in a Digital World - Implications of Internet Core Trends for TV Advertising

This is my 3rd year Statistics Project which required us to perform analysis on a given dataset and report the results. The main research question was to identify which factors are good indicator of a high usage day for bike rentals. Working in a team of 3 members, i was responsible for the performing the analysis and conclusion.