aswingler1
commented
4 years ago Data Preparation and Modeling (17 out of 20%)
The data wasn't messy when I found it but I did a good job of cleaning it I'd say. I think my analysis and interpretation of the models could be a bit better but some of the results get kinda complicated and I didn't want to mess anything up and interpret the data wrong.
Validation and Operationalization (18 out of 20%)
I compared my data in p3 to the one in p2 with a new model with more variables and validated it. I think I did a very good job of coming up with ideas to operationalize the data. I thought of several directions to take the project in the future and also what can be done with the results as is.
R Proficiency (18 out of 20%)
Aside from the code in p2 where I was changing values manually I think my R shows that I learned a lot. I spent hours and hours trying to do that bit the right way but I was wasting so much time and not getting anywhere so I had to do it the ugly way. I imported data from multiple sources using scraping and other methods, I pushed what I thought I could do with ggplot, and I also used several models to analyze my data and I think that shows good proficiency especially since this is my first time working in R.
Communication (19 out of 20%)
I think I did a good job with my visualizations and explaining what they mean to the reader. I really like my graph in P1 where the Republicans are red and the Democrats are blue, I think that shows the data even better than FiveThirtyEight did. I also think my ideas for where to take this project based off what I found would interest the reader into continuing reading this project if I were to work more on it. I think I did a good job communicating what I found out about how politicians generation affects their votes in P2.
Critical Thinking (19 out of 20%)
I would have liked to explore more than just the generation in the project such as age or other demographics but I didn't have the time. I think politics are a very important topic and I am glad for my own sake that I looked into it. I think it helped me have a better understanding of our political system while I was doing my research and analysis. I would like to have had the time to look into some of the possible directions to take the project that I listed in the conclusion to find out other ways to predict and evaluate politicians. This topic has so much potential.
Summary
This portfolio goes into the issue of politics to see the outcome of what politicians do oppose to what they say they will be doing. Some insights that i found interesting was the agree percentage of the generation of people. The author of this portfolio found that third generation people are most likely to vote/agree with Trump. The plan for this project is to help people understand that politician don't actually do what they are going to say they are. They give a speech mainly for votes. so this project will help educate people choose the correct decision when voting for politicians.
Data Preparation
Tables that have been given are votes relate to trump predictions of how future voting would be like. Also he provided another table he scrap from a website about congressmen of immigrants. The data does seem to be tidy and clean but helping the viewers understand the second data set more would really help.
Modeling
A linear regression predictive model that i found interesting was the agree percentage. The dependent variable is the predicted agree and the visualizations did a wonderful job at showing what the model is saying.
Validation
The model has been cross-validated and provided a good explanation of why the model was important.
R Proficiency
Yes the R code is understandable but the naming of variable can be confusing at times. Such as agree_pct.
Communication
The portfolio does a good job at providing summary of what have been done especially after a visualization. I think that was one of the strength in this portfolio. A weakness in the last portfolio was giving summary after the visualizations. Although it was explained in deliverable 2 i think restating the purpose of them is important here so the viewers don't have to go back and forth between the 2 deliverable.
Critical Thinking
The portfolio did a wonderful job at critically thinking of what this project can provide for people. Also the social implication was very interesting analysis of their work on this portfolio.