Publications by Shamecca Marshall
TidyVerse CREATE assignment
In this assignment, you’ll practice collaborating around a code project with GitHub. You could consider our collective work as building out a book of examples on how to use TidyVerse functions. GitHub repository: https://github.com/peterkowalchuk/FALL2023TIDYVERSE FiveThirtyEight.com datasets. Kaggle datasets. Your task here is to Create an Examp...
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Data 607 - Sentiment Analysis
library(tidytext) library(textdata) library(janeaustenr) library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union library(stringr) library(tidyr) library(ggplot2) library(t...
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Lab 8 - Introduction to linear regression
The Human Freedom Index is a report that attempts to summarize the idea of “freedom” through a bunch of different variables for many countries around the globe. It serves as a rough objective measure for the relationships between the different types of freedom - whether it’s political, religious, economical or personal freedom - and other soc...
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Data 607 - Project 2 UPDATE
The goal of this assignment is to give you practice in preparing different datasets for downstream analysis work. Your task is to: (1) Choose any three of the “wide” datasets identified in the Week 5 Discussion items. (You may use your own dataset; please don’t use my Sample Post dataset, since that was used in your Week 6 assignment!) For ea...
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Data 606 - Lab 6: Inference for categorical data
Getting Started Load packages In this lab, we will explore and visualize the data using the tidyverse suite of packages, and perform statistical inference using infer. The data can be found in the companion package for OpenIntro resources, openintro. Let’s load the packages. library(tidyverse) library(openintro) library(infer) The data You will...
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Data 607 - Working with XML and JSON in R
Instructions Load libary library(DT) library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union library(htmltools) library(readr) library(aws.s3) library(jsonlite) library(RC...
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Data 607 - Project 2
The goal of this assignment is to give you practice in preparing different datasets for downstream analysis work. Your task is to: (1) Choose any three of the “wide” datasets identified in the Week 5 Discussion items. (You may use your own dataset; please don’t use my Sample Post dataset, since that was used in your Week 6 assignment!) For ea...
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Data 606 - Lab 5a
In this lab, you will investigate the ways in which the statistics from a random sample of data can serve as point estimates for population parameters. We’re interested in formulating a sampling distribution of our estimate in order to learn about the properties of the estimate, such as its distribution. Setting a seed: We will take some random ...
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Data 606 - Lab 5b
If you have access to data on an entire population, say the opinion of every adult in the United States on whether or not they think climate change is affecting their local community, it’s straightforward to answer questions like, “What percent of US adults think climate change is affecting their local community?”. Similarly, if you had demog...
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Data 606 - Lab 4
In this lab, you’ll investigate the probability distribution that is most central to statistics: the normal distribution. If you are confident that your data are nearly normal, that opens the door to many powerful statistical methods. Here we’ll use the graphical tools of R to assess the normality of our data and also learn how to generate rand...
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