Publications by spemurphy
Capstone_Milestone_Report
library(stopwords) library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union library(tidytext) library(ggplot2) library(tidytext) library(stringr) library(textclean) library(...
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Using xG to predict a players points per game
Using xG to predict a players points per game spemurphy 2024-12-16 Build your Premier League Fantasy Team with this app! Using statistics to win your fantasy football league… Why use this app? xG is the number one metric used to track the quality of chances that a player has during their time on the pitch It is a key predictor in player perf...
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Testing Plotly to build data products
2024-12-14 R Markdown Thanks for watching!...
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"Say Cheese!" - Smiling in campaign posters for the Irish general election
Introduction The hypothesis being tested in this analysis is whether politicians who smile in election posters receive more votes than those who do not smile. For the purposes of this analysis, smile is defined as both the corners of the mouth turned up and the teeth showing, which is consistent with the Oxford Dictionary definition. The analysis c...
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Human-activity-recognition-modelling project
Data Loading Loading data getwd() ## [1] "/Users/seanmurphy/Desktop/DS_coursera/Human-Activity-Recognition-Modelling" if (!file.exists("data")){dir.create("data")} trainUrl <- "https://d396qusza40orc.cloudfront.net/predmachlearn/pml-training.csv" testUrl <- "https://d396qusza40orc.cloudfront.net/predmachlearn/pml-testing.csv" download.file(trainUr...
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Simulation exercise comparing theoretical mean to sample mean
Setting up the data and all variables needed. set.seed(2000) # for reproducability library(ggplot2) # for use later-on nosim <- 1000 # number of simulations n <- 40 # number of exponentials ld <- 0.2 # lambda parameter df <- matrix(rexp(n * nosim, ld), nosim) # simulation of random variables sampleMean <- rowMeans(df) # sample of each row 1. Show...
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An exploratory analysis on the affects of extreme weather events on public health and the economy from 1950-2011 in the United States of America.
Synopsis Analysis was completed based on the parameters of the project. Data was downloaded from the web and then processed using the dplyr package. This allowed for the creation of new variables and the subsequent filtering of other variables. Columns were created that combined fatalities and injuries to create a new column for “public health da...
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