mlclayton6
commented
2 years ago Proposal Review
Reviewers Team Name: Ethan, Matt, and Annie Date: 10/13/2021
Section 1 - Introduction:
The introduction should introduce your general research question and your data (where it came from, how it was collected, what are the cases, what are the variables, etc.).
What is their general research question: How have COVID-19 infection rates and deaths changed over time in the United States? Is the general research question clear? If it is not clear, what questions do you have?
- The overall research question is very clear. Their sub-questions are also very helpful in terms of conceptualizing how the data will be explored.
- Is there any data available regarding masking in the United States? That seems like an important explanatory variable if the outcome variable measured is infection rate and/or total deaths.
Section 2 - Data:
- [X] Is the data in the /data folder?
- [X] Does the README include the dimensions and codebook for the data set?
- [X] Does the proposal include the output of glimpse() or skim() of the data frame.
Data suitability:
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[X] Does the dataset have at least 50 observations and between 10 to 20 variables (exceptions can be made).
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[X] Does the data set include a mix of categorical variables, discrete numerical variables, and continuous numerical variables.
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[X] What variables does the data include (list below):
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Key Variables in the data: total cases, total deaths, new cases, new deaths, date, total number of x vaccinations administered (x = type of vaccine)
Section 3 - Data analysis plan:
- [x] Does the proposal include outcome (response, Y) and predictor (explanatory, X) variables they will use to answer your question? And/or the comparison groups they will use, if applicable.
Do the outcome and predictor variables and/or comparison groups make sense in the context of the question? Why or Why not?
- Yes! The predictor/outcome variables line up nicely with the questions asked in the beginning of the proposal.
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[X] Does the proposal include some very preliminary exploratory data analysis, including some summary statistics and visualizations, along with some explanation on how they help you learn more about your data. (They can add to these later as they work on their project.)
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[X] Does the proposal include the statistical method(s) that they believe will be useful in answering your question(s). (They can update these later as they work on their project.)
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[X] Do they include what results from these specific statistical methods that are needed to support their hypothesized answer?
Reflections
What was something you found interesting about the project?
- This is a topic that we hear about every day in the news, but we have never explored the data ourselves and have been forced to trust what others have told us about vaccinations and infection/death rates. It will be interesting to see what this group comes up with on their own.
What ideas/feedback do you have for other things they may explore?
- It would be interesting to search for data that could inform a discussion on the effectiveness of masking.
**What kinds of plots should they consider to complete the project goal to create some kind of compelling visualization(s) of this data in R?
- Line plots (time series visualizations)
- Stacked bar charts or faceted plots (distinguish data by season)
Any additional feedback you'd like to give the other group:
- Good luck! We're excited to see what you come up with!
Proposal Review
Reviewers Team Name: Date:
Section 1 - Introduction:
The introduction should introduce your general research question and your data (where it came from, how it was collected, what are the cases, what are the variables, etc.).
What is their general research question: __ Is the general research question clear? If it is not clear, what questions do you have?
Section 2 - Data:
Data suitability:
Section 3 - Data analysis plan:
Do the outcome and predictor variables and/or comparison groups make sense in the context of the question? Why or Why not?
[ ] Does the proposal include some very preliminary exploratory data analysis, including some summary statistics and visualizations, along with some explanation on how they help you learn more about your data. (They can add to these later as they work on their project.)
[ ] Does the proposal include the statistical method(s) that they believe will be useful in answering your question(s). (They can update these later as they work on their project.)
[ ] Do they include what results from these specific statistical methods that are needed to support their hypothesized answer?
Reflections
What was something you found interesting about the project?
**What kinds of plots should they consider to complete the project goal to create some kind of compelling visualization(s) of this data in R?
Any additional feedback you'd like to give the other group: