Publications by Ian VanWright
STA490_GroupProject2
class: center, middle, inverse, title-slide .title[ # Comparing Potential Sampling Plans. ] .author[ ### Kyle Weber and Ian Vanwright ] .institute[ ### West Chester University of Pennsylvania ] .date[ ### Prepared for STA490: Data Visualization Slides available at: https://rpubs.com/KW986324 AND https://github.com/Kyle-Weber/STA...
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STA490_Week6Homework
For this report, I will be analyzing bank loan default data. The goal of this analysis is to clean up this data set and do some exploratory data analysis. First, we load all of the data. This data set is split into 9 different files. loan01 <- read.csv("https://pengdsci.github.io/datasets/SBAloan/w06-SBAnational01.csv", header = TRUE)[, -1] loa...
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STA490_Week3Homework
class: center, middle, inverse, title-slide .title[ # Multiple Linear Regression ] .subtitle[ ## Model Building and Analysis of Flight Delay Times ] .author[ ### Ian Vanwright ] .institute[ ### West Chester University of Pennsylvania ] .date[ ### Prepared for STA490: Data Visualization ] --- class: top, center # Tabl...
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STA490_Week6Homework
For this report, I will be analyzing bank loan default data. The goal of this analysis is to clean up this data set and do some exploratory data analysis. First, we load all of the data. This data set is split into 9 different files. loan01 <- read.csv("https://pengdsci.github.io/datasets/SBAloan/w06-SBAnational01.csv", header = TRUE)[, -1] loa...
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STA490_Week7Homework
For this report, i will again be analyzing Bank Loan Default Data. The goal of this analysis is to demonstrate 4 types of sampling: Simplified Random, Stratified Random, Systematic Random, and cluster sampling. Again, the data is still split into 9 seperate files. I will combine all of them into 1 data set. loan01 <- read.csv("https://pengdsci....
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STA490_Week11And12Homework
For this report, I will be analyzing survey data about student satisfaction and engagement. The goal for this analysis is to measure validity in terms of work load. survey_raw <- read.csv("at-risk-survey-data.csv", header = TRUE) nrow(survey_raw) ## [1] 664 1 Cleaning and Extracting Data 1.1 Cleaning the Data This data set originally has 332...
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STA321_Week13Homework
1 Introduction For this report, I will be analayzing Monthly Natural Gas Prices. Specifically I will be analyzing gas prices from January 2008 to August of 2020 To do this, I will build a time series with the data and then build and then compare various smoothing models. 2 Time Series Analysis 2.1 Training and Testing Data To start, I will s...
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STA321 Week 3 Homework
1 Introduction For this report, I will be using a data set consisting of delayed flight times of various airlines. In this data set, there are 11 variables and 3593 observations. The variables are: Carrier (Categorical) - The airline that the flight is taken with Airport_Distance (Numeric) - The Distance between the airports in miles Number_of...
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STA321_Week5Homework
1 Introduction For this report, I will be using a data set consisting of delayed flight times of various airlines. In this data set, there are 11 variables and 3593 observations. The variables are: Carrier (Categorical) - The airline that the flight is taken with Airport_Distance (Numeric) - The Distance between the airports in miles Number_of...
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STA321_Week6Homework
1 Introduction For this report, I will be analyzing banks loans and whether or not a loan has been defaulted on. I will be using a data set that has documented 1000 loans and 16 variables. The variables in this data set are as follows: Checking_amount - Numeric Term (in months) - Numeric Credit_score - Numeric Gender - Categorical Marital_status...
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