Proposal Review

Reviewer: Professor Baker Date: 03/14/2022

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: For our final project, we have decided to investigate medal counts, specifically comparing First World vs Third World countries. This question will allow us to investigate how funding affects performance at the Olympics.
Is the general research question clear? If it is not clear, what questions do you have?

Chenemi had some great feedback about how first world/third world is based on GDP. You might want to use low income/high income to distinguish.

Section 2 - Data:

[X] Is the data in the /data folder?
[ ] Does the README include the dimensions and codebook for the data set? (Found it here, but you will want to include it in the data folder readme)
[ ] Does the proposal include the output of glimpse() or skim() of the data frame.

Data suitability:

[X] Does the dataset have at least 50 observations and between 10 to 20 variables (exceptions can be made).
[X] Does the data set include a mix of categorical variables, discrete numerical variables, and continuous numerical variables.
[ ] What variables does the data include (list below):
- You'll want to add this to the codebook
- You might consider looking at and including variables from the gap minder dataset.
- You might also consider information about the climate (e.g. temperature)
- You will also want to include population (the population of a country influences the pool of athletes that country can draw from).
- It might be interesting to look at what countries punch above their weight.

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.
You will need to get income to be able to distinguish between high and low-income countries.

Do the outcome and predictor variables and/or comparison groups make sense in the context of the question? Why or Why not?

See above for other variables you will want to consider, especially for the Winter Olympics.

[ ] 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.)
I think you could explore this using a linear model, you could also compare the ratio of medals to population.
[ ] Do they include what results from these specific statistical methods that are needed to support their hypothesized answer?
The variables that have a positive slope associated with them would indicate that they increase the medal count. You might want to narrow your dataset down to those countries that receive more than 5 medals.

Reflections

What was something you found interesting about the project?
- I'm interested to see how temperature influences the data and to see which countries have a surprising number of medals!
What ideas/feedback do you have for other things they may explore?
- See above.
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?
- Map
- Stacked bar plot.
Any additional feedback you'd like to give the other group:
- Your proposal is missing some initial data exploration and analysis. Make sure to reach out for help and get started on the project early.
- Finding actual funding to athletes might be tricky to pass down. You might want to consider this as part of the limitations of the data.

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 does funding affect olympic medals gained by countries? Specifically first world vs third world? Is the general research question clear? If it is not clear, what questions do you have?

yes the general research question is clear. One question we have is how does average yearly temperature per country affect participation in winter/summer olympics. ... ... Section 2 - Data: Is the data in the /data folder? - Yes Does the README include the dimensions and codebook for the data set? - No, not yet but they are trying their best :) Does the proposal include the output of glimpse() or skim() of the data frame. - No. Data suitability: Does the dataset have at least 50 observations and between 10 to 20 variables (exceptions can be made). Yes Does the data set include a mix of categorical variables, discrete numerical variables, and continuous numerical variables. - -Yes What variables does the data include (list below):
Country
Medal Count
Teams
Athletes
Entries by Discipline.

Section 3 - Data analysis plan: 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.

Yes, the X variable is economic status of the country, while the Y variable is medal count. Do the outcome and predictor variables and/or comparison groups make sense in the context of the question? Why or Why not? yes they make sense, as a country gets richer, the hypothesis is that the country will win more medals.

...

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.) -- No. 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.) -- No, but they have verbally suggested that they will take average GDP to determine economic status per country.

Do they include what results from these specific statistical methods that are needed to support their hypothesized answer? -- No.

Reflections What was something you found interesting about the project? -- Something we found interesting is that the Athlete's origin country may not be the country they compete for, which may lead to some outliers in the data. ... What ideas/feedback do you have for other things they may explore? One idea we have is to look at the average temperature of each country in the dataset and filter for winter/summer olympics. ... 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? Some ideas for plots are stacked bar plots representing gold, silver, and bronze as well as a scatter or line plot looking at number of medals and GDP. ... ... Any additional feedback you'd like to give the other group: we are excited to see what you guys come up with!

DCS-210 / w2022-project-olympics2022