Publications by Vanessa
BanaDwHw
Diagnostics Check On Multiple Linear Regression Output The following graph displays a simple “sanity check” measure on how well is the output on a multiple linear regression model meeting one of the underlying statistical assumptions. Users of linear regression require not only to be able to interpet a model’s output but also a way to measu...
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Vanessa Murillo's Data Analytics Student Bio
A Data Analytics Student’s Profile Intro Bilingual analytics professional with comprehensive risk management experience, extensive background in data analytics. A current Master of Science in Business Analytics from the University of Cincinnati candidate. Fascinated by statistical research in Macro Economic topics and public-private business v...
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Document
Q1 Import the data First I will set up the working directory using the below code. setwd("/Users/vanessamurillo/Desktop/BANA HW/week 1") Now, the code below imports the dataset into R. We see the first 10 rows from each column with the function that follows. data <- read.csv("/Users/vanessamurillo/Desktop/BANA HW/week 1/week1_cincy_crimes.csv") h...
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Forecasting Methods Assignment 2
Model Selection The following analyses will look further into the best time series modeling for the uni variate data set that lists Afghan displacements(migration) over the years. The first code will list all the libraries required to run the rest of the insights. The loading data set code will follow that. library(readxl) library(TSstudio) libra...
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Afghanistan Displacement Forecasting Model
Introducing the Topic and the Data Generating Process In the following paper, I will be discussing data insights regarding Afghanistan’s conflict-based displacements for the years 1990-2020. Afghanistan underwent a political takeover by the Taliban on August 15, 2021 after the U.S. retreated its presence out of the country & the then standing p...
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New data and assignment 3
Afg_Ref_Pop <- read_excel("Revised_Refugee_Pop_Afg.xlsx") Afg_Ref_Pop$Year <- as.Date(as.character(Afg_Ref_Pop$Year), format ="%Y") names(Afg_Ref_Pop)[2] <- 'Ref_Population' sapply(Afg_Ref_Pop, class) ## Year Ref_Population ## "Date" "numeric" #Std deviation plot Afg_Ref_Pop %>% mutate(Refugee_Pop_Rolling_StdDev = zoo::r...
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