Project 4 Instructions

.pdf

School

Johns Hopkins University *

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Course

220.620

Subject

Computer Science

Date

Dec 6, 2023

Type

pdf

Pages

2

Uploaded by HighnessComputerPigeon16

12/2/23, 9:27 PM Project 4 Instructions https://courses.edx.org/asset-v1:UTAustinX+DataSci.322+2T2023+type@asset+block/project4_instructions.html 1/2 Project 4 Instructions Please use the project template R Markdown document to complete your project. The knitted R Markdown document (as a PDF) and the raw R Markdown file (as .Rmd) must be submitted to edX by the posted deadline. To upload your code, you must first compress it as a .zip file. These two documents will be graded jointly, so they must be consistent (as in, don’t change the R Markdown file without also updating the knitted document!). All results presented must have corresponding code. Any answers/results given without the corresponding R code that generated the result will be considered absent. To be clear: if you do calculations by hand instead of using R and then report the results from the calculations, you will not receive credit for those calculations. All code reported in your final project document should work properly. Please do not include any extraneous code or code which produces error messages. (Code which produces warnings is acceptable, as long as you understand what the warnings mean.) For this project, you will be working with a dataset containing information lemurs housed at the Duke Lemur Center, such as their weight, gender, number of offspring, etc. The dataset includes life history records for all individuals that lived at the Duke Lemur Center from 1966 to 2014, and is an important resources for lemur conservation. More information about the dataset can be found here: https://github.com/rfordatascience/tidytuesday/tree/master/data/2021/2021-08-24 (https://github.com/rfordatascience/tidytuesday/tree/master/data/2021/2021-08-24) and https://www.nature.com/articles/sdata201419 (https://www.nature.com/articles/sdata201419). This project should be structured as follows: Introduction (1–2 paragraphs) Approach (1–2 paragraphs) Analysis (2–3 code blocks, either 1 computed table and 1 figure or 2 figures, text/code comments as needed) Discussion (1–3 paragraphs) We encourage you to be concise. A paragraph should typically not be longer than 5 sentences. Overall Project Instructions Your analysis must contain some of the material discussed in classes 19 through 22, i.e., some statistical modeling or dimension reduction. All plots must be of different types. Specific Instructions For Project 4, we provide you with the dataset and you define a specific question to answer. In the Introduction section, write a brief introduction to the dataset, the question, and what parts of the dataset are necessary to answer the question. You may repeat some of the information about the dataset provided above, paraphrasing on your own terms. Imagine that your project is a standalone document and the grader has no prior knowledge of the dataset. Important: You must describe the data columns you are going to use.
12/2/23, 9:27 PM Project 4 Instructions https://courses.edx.org/asset-v1:UTAustinX+DataSci.322+2T2023+type@asset+block/project4_instructions.html 2/2 In the Approach section, describe what type of data analysis you will perform and what kind of plot(s) you will generate to address your question. Provide a clear explanation as to why your chosen analysis is best for providing the information you are asking about. In the Analysis section, provide the code that performs your analysis and generates your visualization. In your plot, use scale functions to provide nice axis labels and guides. Also, use theme functions to customize the appearance of your plot. All plots must be made with ggplot2. Do not use base R plotting functions. In the Discussion section, interpret the results of your analysis. Identify any trends revealed (or not revealed) by your analysis. Speculate about why the data looks the way it does.
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