Publications by Kelly Templeton
STA 112 Project 2
Section 1: Data Visualizaiton / EDA In order to understand what the relationship between budget and the gross of a film is, we begin by exploring the data visually. Budget and gross are both numeric variables, meaning that the value is a number. In this case, the numeric variables are the amount of money spent on making the film and the amount of...
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STA 112 Lab 3
Question 1 Question 2 Fish age and length have a moderate concave down curve relationship that begins increasing and then decreases, with two apparent outliers. These outliers occur around (5, 190) and (5.5, 190). Question 3 Question 4 Based on the scatterplot, I would select the length minimum to be 155 cm. The dotted line indicates the separ...
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STA 112 Project 1 KAT
Section 1: Introduction Broadway shows are legendary for their high production value, popularity, and ability to showcase the talents of many artists over long periods of time. The more popular a Broadway show, the more people are likely to come and the more money it is likely to make. The data set I will be investigating contains points about Br...
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STA 112 Project 1
Section 1 Broadway shows are legendary for their high production value, popularity, and ability to showcase the talents of many artists over long periods of time. The more popular a Broadway show, the more people are likely to come and the more money it is likely to make. The data set I will be investigating contains points about Broadways shows ...
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STA 112 Lab 4
load(url("http://www.openintro.org/stat/data/evals.RData")) library(ggplot2) Question 1: Create a scatter plot to explore the relationship between X = beauty score and Y = evaluation score. Make sure to label your axes! ggplot(evals, aes(x=bty_avg, y = score)) + geom_point() + labs(title="Figure 1", x = "Beauty Score", y = "Evaluation Score") Q...
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STA 112 Project 3
Abstract Examining the factors which influence the sale price of a home is important in order to learn how to price homes, what selling points to bring up to potential buyers, and overall understand the value of a home. In this report, we explore and discuss what the key factors of a home are associated with higher sale prices. Data was collected...
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STA 112 Project 3 Code Appendix
houseprices <- read.csv("~/Downloads/houseprices.csv") houseprices$KitchenQual <- as.factor(houseprices$KitchenQual) houseprices$GarageFinish <- as.factor(houseprices$GarageFinish) houseprices$Neighborhood <- as.factor(houseprices$Neighborhood) library(ggplot2) ggplot(houseprices, aes(x=LotArea)) + geom_freqpoly(color= 'blue', bins=30) + labs(tit...
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STA 112 Lab 5
Question 1: Which variable do think might be most highly associated an email being spam? Why? I think that the variable most highly associated with an email being spam may be the “winner” variable. Many spam emails may attempt to entice people by claiming that they won some price, and often include a link where they can then “claim their pr...
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