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Make-Up Residency Individual Effort Project A data visualization project Last updated August 2021 For this project, use the data consolidated by Texas A & M University (n.d.)11 Texas A & M University. (n.d.) Housing activity report [data set and code book]. Real Estate Center. Retrieved August 4, 2021, from https://www.recenter.tamu.edu/data/housing-activity/#!/activity/State/Texas to answer the following research question: What relationships exist between the number of months a property remains in inventory, the number of monthly sales, the monetary volume of the monthly sales, and the total number of listings?

Make-Up Residency Individual Effort Project

A data visualization project

Last updated August 2021

For this project, use the data consolidated by Texas A & M University (n.d.)11 Texas A & M University. (n.d.) Housing activity report [data set and code book]. Real Estate Center. Retrieved August 4, 2021, from https://www.recenter.tamu.edu/data/housing-activity/#!/activity/State/Texas to answer the following research question:

What relationships exist between the number of months a property remains in inventory, the number of monthly sales, the monetary volume of the monthly sales, and the total number of listings?

Table 1 The Data Dictionary

Fields

Description

Date

The month the the real estate values represent.

Sales

The number of real estate properties sold for the month.

Dollar Volume

The total US dollar volume of the monthly sales.

Total Listings

The total number of properties that are listed.

Months in Inventory

The average number of months a property remains unsold at the current pace of sales.

Note. The information in the the data dictionary is based on the information provided by Texas A & M University (n.d.).22 Texas A & M University. (n.d.) Housing activity report [data set and code book]. Real Estate Center. Retrieved August 4, 2021, from https://www.recenter.tamu.edu/data/housing-activity/#!/activity/State/Texas

Click here to download the data. (texas_housing.RData)

For your paper and presentation, you will use the data provided in these instructions and R to develop an R script, write a paper, create slides, and present your findings using the data visualization process outlined in the course textbook. Your exploration will include both non-visual and visual analysis. This is an individual assignment, NOT a group assignment.

Using the lessons Unit 1 through Unit 5, the data provided, collect, clean, and explore the data. Document the programming in an R script file. As you explore the data, look at any key findings from multiple perspectives.33 A different perspective may be found by using different geometry or a different subgroup. Subgrouping can be done with a filter() or you can group_by() fields and summarise() the data for the visualization. Only key findings should be presented in your paper and presentation.

Your paper and presentation lose points if you include R programming code, R programming language, or insignificant findings in your paper or presentation.

There are three different files you will submit for this project: presentation slides, the report as a paper formatted per APA 7, and an R script file. Submit the R script with your presentation slides.

Good to know

Presentation and Report

You must credit the source of the data and any other external sources used, formatted per APA 7.44 If there are false sources or missing sources in the submission, every group member will earn zero points for the work.

You must include no less than five informative visualizations depicting different55 different in this context means that the information learned from the visualization is different for each information.66 You can include multiple visualizations with different perspectives of the same information, if they serve a purpose. However, the additional visualizations are not considered one of the five required.

You must provide an interpretation of each visualization and describe the implications of each visualization. An interpretation is the relationship that the visualization suggests; the implication is what that relationship suggests in terms of the objective of the analysis.77 In formal research, the former is known as the results, the latter is known as the discussion.

In your report, include evidence by referring to the figure number.88 For example, at the beginning of a sentence: As shown in Figure 1 or at the end of a sentence: (see Figure 1).

Your figures must be formatted per APA 7.99 You can format the plots per APA 7 within R. Alternatively, you can add the title, subtitle, and caption in the slides or paper.

Figures must be labeled sequentially in order of their appearance.

In the report, the figures must be left-aligned. Additionally, they are placed between complete paragraphs, not within a paragraph.

Figures are not limited to graphs. For the most part, anything that is not a table or text is a figure, per APA 7. If you add pictures from any external source you must include the reference for that image and the copyright information.

Do not include programming code or images of programming code in the presentation or report. This project is not a ‘how-to’ in R.

The report must be documented as a student paper, per APA 7, demonstrating graduate-level writing.

Script file

The programming must include the questions you posed to yourself that led your visualizations in the comments.

You will have visualizations in your programming then the presentation or report.

This file should contain everything needed to run the file, including, but not limited to loading the data and calling the libraries.1010 All libraries should called together, near the top of the script file, after the leading comments required in every script file.

Any information derived from the data in the presentation or the report must be derived from the programming in your R script.

Your programming code must reflect that presented graphs were valid by looking at the data from different perspectives. Include comments in the programming to identify the plots included versus excluded.

When you submit

This is an individual assignment. Sharing your work with others is not acceptable.

You will receive an warning when you submit an R file. This warning indicates that R script files are not checked by SafeAssign. This does not you from submitting the work.

Consider the guidelines, suggestions, and other tips provided in previous assignments. All of that still applies here. If you have any questions, please send me an email.

When you document this information, do not write the information as if it were a blog, a casual conversation among friends, or a short answer paper. Demonstrate professionalism in all of your work. Whether it is a presentation or a report, include an introduction, a topic sentence or overall objective, supporting ideas, and a conclusion.

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