3.6 KiB
3.6 KiB
#rs/discussion #rs/class/ad450
- Ask Phase Reflection:
- Describe a time when you had to define a problem or understand stakeholder expectations in a project or study. How did you approach this task, and what challenges did you face?
- One time that I had to define a problem and use the data analysis process was when I worked on creating an analysis tool for my high school robotics team. There is a website that publishes data about competitions and team performance and I wanted to use this data to create custom metrics about team performance and do some analysis. This project was largely for myself but I set the goal of creating a metric that could perform similarly to some of the others that exist such as offensive power rating or estimated points added.
- Prepare Phase Experience:
- Share an instance where you had to collect and prepare data for analysis. What types of data did you use, and how did you ensure its relevance and objectivity?
- The data that I used came from thebluealliance.com which is a site that publishes all match data from First Robotics competitions. This data is published directly from competitions and is the primary source of match data for teams and districts. While it can be inaccurate sometimes the inaccuracies come from how the matches were scored at events and not the data entered into the system and the website will always reflect match results.
- Process Phase Challenges:
- Reflect on a situation where you had to clean or process data. What difficulties did you encounter, and how did you overcome them?
- I pulled the data from an api so it was pretty well structured. The processing that I had to do on the data was largely ensuring that I was pulling from the correct matches and events rather than having to clean the data.
- Analyze Phase Insights:
- Discuss your experience with analyzing data. What tools or methods did you use, and how did you interpret the results?
- One of the things that I did to analyze the data was to try and calculate a strength of schedule metric for teams at an event based on who they faced in their qualification matches. I did this by looking at how strong the teams that they were facing were and used data from after the event like match scores to give a metric of how challenging their schedule was. This wasn't the most helpful since it could only be used after an event but in the future I might expand it to predict the strength of a schedule before the matches have happened.
- Share Phase Application:
- Recall a time when you had to present your data findings. How did you communicate your insights, and what techniques did you use to make your presentation effective?
- I didn't present much of my findings since I didn't get to a point where I was finished but if I did I would likely give examples and show some manual verification to communicate accuracy. I would also probably go through my methods for calculating the metric to show others what I was doing and how I was getting the numbers I was getting.
- Act Phase Impact:
- Think about an occasion where your data analysis led to actionable insights. What were the outcomes, and how did your analysis influence decision-making?
- I didn't apply my findings much but the data could lead to better strategy decisions at or after competitions since you can look at the strength of the schedule of other teams at the event and determine if they might be ranked higher than they should be or lower than they should be. This is important in the review phase for an event or when making decisions of what teams to pick at the event.