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Tyler Muffly's Projects

sales-force-alignment-clustering- icon sales-force-alignment-clustering-

Define and align the most effective and balanced sales territories based on geography and physician prescribing habits, in order to maximize promotion of new medications. Pharmaceutical companies spend millions of dollars annually on their sales force in order to promote recently discovered medications, thereby increasing their company’s revenue. The sales force is aligned with geographical territories that are defined to maximize representative effectiveness and reach, and minimize travel time, while providing “fair” and approximately equal sales potential for each representative.

sentiment-analysis-of-jw-marriot-hotel-reviews icon sentiment-analysis-of-jw-marriot-hotel-reviews

implemented a web scraper to fetch live hotel reviews from TripAdvisor website. Conducted data pre-processing and cleaning by removing stop words, punctuation, special characters, numbers, and white-spaces from reviews. Performed tokenization and stemming of reviews, and built a corpus out of it. Calculated the sentiment score of each review by comparing it's tokens with positive and negative lexicon and the overall sentiment score of the hotel depending on the number of positive and negative reviews it received.

shinymod icon shinymod

A R package of shiny modules and helper functions for making shiny apps or flexdashboards

sliced icon sliced

Scripts used for SLICED! Season 1 episode 01. (I almost won)

sliced-1 icon sliced-1

My Code from the Sliced Data competition and practices

svm-r-markdown-templates icon svm-r-markdown-templates

I have a suite of R Markdown templates for academic manuscripts, beamer presentations, and syllabi. I share them here.

tannous icon tannous

Tannous Project looking at geographic disparities in potential accessibility to OBGYNS in the United States

tyler icon tyler

Common Functions For Mystery Caller Or Audit Studies Evaluating Patient Access to Care.

us-potus-model icon us-potus-model

Code for a dynamic multilevel Bayesian model to predict US presidential elections. Written in R and Stan.

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