Data Analysis Project Planning: Best Practices for Updating Your Plan

Considerations for Updating Your Plan

Update the plan For this week’s objective, you will update the plan and add information about the status of the project, after you work with the data. Consider all of the questions that you did when you made the original plan. What needs to change? What can be clarify better? Don’t write about what is different, only write about the current state of the project. If I want to know what is different, I can reread your Part 1 submission. Formulating the brief answers these questions Why is this interesting or important? What about it is important? What requires clarification? What pitfalls could cause the analysis to be incomplete or incorrect? Who is the audience? What do you think the audience expects? How much time do you have to complete the project? What are the project conditions? What tools do you have access to? Or, as is the case in this course, what are you limited to, regarding software? Can the evidence be summarized in one visualization? Two? Several? Will the results of this analysis be an exhibit (evidence), an explanation (presentation), or an exploration (audience interaction)? Working with data When you work with the data, whether cleaning, investigating, or exploring, ask yourself questions as you progress through the process. These questions may include Are the right data types assigned? How many observations are associated with the state I’m assigned? How do I filter for the complaints specific to the analysis I’m assigned? Which fields apply to this analysis? What is the range of the median household income, the population, and the delay between receiving and forwarding customer complaints? Should no or zero delay observations be separated? (Is management more interested in the overall or what or how the response times can be improved?) Are there fields of data that would add to the data story that are outside the scope? Does the scope need to be modified? Perhaps you identified that a specific product or company was associated with all of the delays exceeding 50 days. That could be very useful information to the management team. Another possibility might be that there is one type of company response to the customer that has the higher delay time. Perhaps focusing on the delays exceeding a certain number of days offers very different insight than no or only a few days of delay? Yet another possibility? Perhaps the time of year, like a particular season, coincides with the length of the delay? Submission requirements When you document this information, you will need to write it as a paper. This is not a blog, a discussion, or a short answer paper. You will need to include an introduction, a topic sentence, supporting paragraphs, and a conclusion. Not great at writing? Go to Start Here in the main menu and look at the resources available to you. Make sure that you document your work using the standards of APA 7. To help with formatting use the APA 7 Student Paper template. Your work with R in RStudio must be documented in a .r script file. You must submit a paper and a script file for this assignment. Your paper is still about the project and project planning. The functions, libraries, or other elements specific to R are not appropriate content for the paper.