Publications by Dell
Story 3 D608
Story 3 DATA 608 The rate of firearm mortality varies tremendously between states. Several factors have been proposed to explain this public health disparity, from regulations in the given state, socioeconomic conditions like poverty, or cultural factors surrounding gun ownership. Your task in this data story is to make visualizations that inve...
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Assignment5 D624
Homework 5 Do exercises 8.1, 8.5, 8.6, 8.7, 8.8, 8.9 in Hyndman. Please submit both the link to your Rpubs and the .pdf file with your run code 8.1) #Consider the the number of pigs slaughtered in Victoria, available in the aus_livestock dataset. library(dplyr) ## Warning: package 'dplyr' was built under R version 4.4.2 ## ## Attaching package...
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Homework 4 D624
Homework 4 Do problems 3.1 and 3.2 in the Kuhn and Johnson book Applied Predictive Modeling. Please submit your Rpubs link along with your .pdf for your run code. 3.1) The UC Irvine Machine Learning Repository6 contains a data set related to glass identification. The data consist of 214 glass samples labeled as one of seven class categories. T...
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Assignment 1 D622
Assignment 1 This assignment focuses on one of the most important aspects of data science, Exploratory Data Analysis (EDA). Many surveys show that data scientists spend 60-80% of their time on data preparation. EDA allows you to identify data gaps & data imbalances, improve data quality, create better features and gain a deep understanding of y...
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Story 2 D608
Story 2 The Federal Reserve’s mandate from Congress is to control inflation and to maintain low unemployment. You can read about it here: Dual Mandate. These seem to be contradictory objectives- see this wikipedia article on the Phillips Curve. Another good but short news article which focuses on the specific context of recessions is here: So...
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Homework 3 D624
Homework 3 Instructions Do exercises 5.1, 5.2, 5.3, 5.4 and 5.7 in the Hyndman book. Please submit your Rpubs link as well as your .pdf file showing your run code. 5.1) #Produce forecasts for the following series using whichever of NAIVE(y), SNAIVE(y) or RW(y ~ drift()) is more appropriate in each case: Australian Population (global_economy), ...
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Assignment2 D624
Homework 2 Do exercises 3.1, 3.2, 3.3, 3.4, 3.5, 3.7, 3.8 and 3.9 from the online Hyndman book. Please include your Rpubs link along with.pdf file of your run code 3.1) Consider the GDP information in global_economy. Plot the GDP per capita for each country over time. Which country has the highest GDP per capita? How has this changed over time...
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Homework 1 DATA624
R Markdown The chuck below contains the required libraries for this assignment. if (!require("fpp3")) { install.packages("fpp3") } ## Loading required package: fpp3 ## Warning: package 'fpp3' was built under R version 4.4.2 ## Registered S3 method overwritten by 'tsibble': ## method from ## as_tibble.grouped_df dplyr ##...
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ELO calculations
This is a continuation of my first project of Chess tournament, the chunks below are essential for the next part of this project where the data is loaded, cleaned and tidying to move for the ELO calculations and make a comparison between the rates of chess players. # List of packages to install packages <- c("RCurl", "knitr", "kableExtra", "tid...
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NobelPrize
##Introduction Working with the two JSON files available through the API at nobelprize.org, ask and answer 4 interesting questions, e.g. “Which country “lost” the most nobel laureates (who were born there but received their Nobel prize as a citizen of a different country)?” #Preparing the dataset Loading Required Packages: The code s...
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