Publications by Betsy Rosalen

NYSED 2H2 Presentation for COSDI

11.10.2023

Timeline - Data Entry Due in early August Instructions often not available till mid July! Data must be entered in CUNYfirst by June 30th (or the last work day in June) Central IR Office (Biana) locks data on or shortly after July 1st Information entered after June 30 will not be included in the report Central IR Office (Betsy) runs the calculation...

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DATA 71000 Final Presentation

04.05.2023

2023-05-04 NASA Exoplanet Archive 5,300 observations as of March 14th and growing… Exoplanet Archive:exoplanetarchive.ipac.caltech.edu Data:Planetary Systems Composite Parameters table Data Dictionary:exoplanetarchive.ipac.caltech.edu/docs/API_PS_columns.html The Planetary Systems table contains one row per planet per reference. Planetary Syst...

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Chi-Square Visualizations Comparison

16.03.2023

knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE) setwd("~/OneDrive/CUNY GC MS DA+DV/DATA 71000 - Data Analysis Methods/Final Project") # install.packages("kableExtra") # install.packages("gplots") # install.packages('corrplot') # install.packages("ggstatsplot") # install.packages("vcd") # install.packages("ggmosaic") library(tidyv...

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GitHub for Beginners

17.11.2022

Git and GitHub for Beginners CUNY OAREDA Training Betsy Rosalen November 17, 2022 Agenda Slide Presentation What are Git and GitHub Basics of working in GitHub on the web and with GitHub Desktop 2 short videos of basic workflows in GitHub and GitHub Desktop Demo Basic navigation and workflows on the GitHub website and in GitHub Desktop How t...

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CUNY MSDS DATA624 Project 1

13.05.2020

Part A – ATM Forecast Files: ATM624Data.xlsx In part A, I want you to forecast how much cash is taken out of 4 different ATM machines for May 2010. The data is given in a single file. The variable ‘Cash’ is provided in hundreds of dollars, other than that it is straight forward. I am being somewhat ambiguous on purpose to make this have a l...

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CUNY MSDS DATA624 Project 2 - Non-Technical Report

11.05.2020

Project Description This report contains the findings of the data analysis undertaken by the data science team, lead by Zach Herold, Anthony Pagan, and Betsy Rosalen at ABC Beverage Company in order to better understand the impact of manufacturing processes on the pH level in our products and to comply with new federal regulations. The report has...

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CUNY MSDS DATA624 Project 2 Technical Report

11.05.2020

Project Description The data science team at ABC Beverage has been asked to provide an analysis of our manufacturing process, the predictive factors, and a predictive model of PH in order to comply with new regulations. This report details the steps taken in our analysis, including the assumptions made, the methodology used, the models tested, th...

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CUNY MSDS DATA624 HW9

04.05.2020

Exercise 8.1 Recreate the simulated data from Exercise 7.2: library(mlbench) set.seed(200) simulated <- mlbench.friedman1(200, sd = 1) simulated <- cbind(simulated$x, simulated$y) simulated <- as.data.frame(simulated) colnames(simulated)[ncol(simulated)] <- "y" Part (a) Fit a random forest model to all of the predictors, then estimate the variab...

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CUNY MSDS DATA624 HW7

26.04.2020

Exercise 6.2 Developing a model to predict permeability (see Sect. 1.4) could save significant resources for a pharmaceutical company, while at the same time more rapidly identifying molecules that have a sufficient permeability to become a drug: Part (a) Start R and use these commands to load the data: library(AppliedPredictiveModeling) data(pe...

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CUNY MSDS DATA624 HW6

06.04.2020

Exercise 8.1 Figure 8.31 shows the ACFs for 36 random numbers, 360 random numbers and 1,000 random numbers. Left: ACF for a white noise series of 36 numbers. Middle: ACF for a white noise series of 360 numbers. Right: ACF for a white noise series of 1,000 numbers. a. Explain the differences among these figures. Do they all indicate that the dat...

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