Publications by Sherlyn Hilton
Extra Credit R & Rmarkdown
Mapping with R A cool thing I learned this summer was how to use R to do GIS analysis. This is a bit of code from a class assignment. We’ll look at data from countries around the world. The data is found in countries.shp, which is a global shapefile with various socio-economic indicators for different countries such as: Median GDP: (gdp_md_e...
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Lecture 4 - Regression
Regressions Part 1 Build a regression model that predicts income using height, weight, and age as the predictors. First step, is to load in the data and take a look at what we’re dealing with. #Load the packages library(rrcov) library(Hmisc)#makes the histograms library(corrplot) library(RColorBrewer) library(ggplot2) # load data from fi...
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Lecture 2 - Stat 6003
Penguins and T-tests #Install and load packages library(tidyverse) library(stats) library(rrcov) library(readxl)#Reads excel data Part 1. Use tidyverse to create a summary dataset that shows the average of bill_length_mm, bill_depth_mm, and flipper_length_mm by species df <- read_excel("homework_2_penguins.xlsx") # copy original data into ...
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Stat 6003 - Lab 1
Use the oswego.csv dataset to find the bad food served at the community lunch. The first step is to load the information into a dataframe, change the appropriate columns to categorical data, then do fourfold plots for all the different foods. library(stats) library(dplyr) oswego <- read.csv("homework_1_oswego.csv") # only use data about pat...
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GEOG 6680 - Project
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(ggplot2) library(gridExtra) ## ## Attaching package: 'gridExtra' ## The following object is masked f...
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Module 15
tmap package tmap is used for making nice maps that layer in ways similar to ggplot2. tmaps use spatial objects for the data, geometries and symbols are then layered on top. The first example is looking at data for Syracuse, NY. library(tmap) ## The legacy packages maptools, rgdal, and rgeos, underpinning this package ## will retire shortly. Ple...
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GEOG 6680 - Module 12
Exercise 1 In the zipfile countries.zip is a global shapefile with various socio-economic indicators for different countries. Load this file into R and make plots of any two of the following variables (the variable names are given in brackets). Try different color scales and transformations of the data to get the most informative maps Median GD...
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GEOG 6680 - Module 11
Read in the data using fread library(data.table) library(ggplot2) library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:data.table': ## ## between, first, last ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:ba...
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GEOG 6680 - Module 10
Exercises Read in the enrollment data. Look at the data structure library(ggplot2) unm <- read.csv("enrollmentForecast.csv") str(unm) ## 'data.frame': 29 obs. of 5 variables: ## $ YEAR : int 1 2 3 4 5 6 7 8 9 10 ... ## $ ROLL : int 5501 5945 6629 7556 8716 9369 9920 10167 11084 12504 ... ## $ UNEM : num 8.1 7 7.3 7.5 7 6.4 6.5 6.4 6....
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Module 9
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 Exercises Make up a vector of 50 random Legolas actors, with mean height of 195cm, and a standard deviation ...
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