Category: Projects

See below for some instructions about the two projects–both are due this Friday (Dec 18), but the linear regression project is optional and will be counted as extra credit:

• Commute time project: this project is required. Either print out your spreadsheet to hand in Wednesday with the final, or email me a link to your spreadsheet before Friday (if you’re using Google, it’s best to use the “Share” button to make sure I can view it with the link; if you’re using Excel, you can email it as an attachment). Look at this post for what your commute time spreadsheet should include (including a link to a sample project spreadsheet I created).

• Linear regression project: this project will count as extra credit.  Again, you can either print out a hardcopy to hand in, or email me your spreadsheet.  Your project should include the following:
  • a scatterplot of your paired data set, including the “trendline” (i.e., the linear regression line)
  • the correlation coefficient and the linear regression parameters (slope and y-intercept)
  • a brief written description (1-2 paragraphs) about the scatterplot and statistics (e.g., how strongly are the variables correlated? is the linear regression line a good model? are there any outliers?)
  • you can refer to the solutions to the exam questions about paired data sets and linear regression for examples of how to write about these topics (Exam #1, Question #4 & Exam #2, Question #5)

Yesterday in class, I introduced the 2nd project for the semester (please remember to continue collecting your commute time data for that project!)

This project will involve:

• finding a paired data set on a topic you’re interested in
• creating a scatterplot with the linear regression trendline
• computing the correlation coefficient and linear regression parameters
• writing up a short (1-2pp) discussion of the data and your findings.

Here is a timeline for the first steps for this project:

• by Mon Nov 25: decide whether you want to work on this project individually or together with a partner
  • if the latter, find a research partner in the class!
• by Wed Nov 27: decide on a topic (broadly speaking) that you’re interested in studying statistically
  • some examples: economics, sports, public health, law/crime, business, finance, entertainment (movies, music, etc), demographics (population, race, gender, etc), politics/elections, transit/transportation, weather, environment, energy, …
  • here are some websites you can browse for ideas for topics: Our World in Data, GapMinder, NYC OpenData, FlowingData, The Guardian’s Datablog, FiveThirtyEight, NYT’s Upshot
• by Wed Dec 4: decide on a specific topic & find an appropriate paired data set (we will spend some class time on this during which I will help you individually!)