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Spring 2022 Workshops

  • Introduction to Stata II (2nd of the two workshop series)
    • February 27-28
    • Location and registration by attending prior Stata workshops or instructor permission
    • Using a dataset on county demographics, presidential voting, and deaths of despair, this workshop covers how to use Stata to examine some simple hypotheses. We will cover googling code, examining distributions of data, calculating probabilities from a normal distribution, standard errors & confidence intervals, and t-tests.
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  • Visualizing Regression Surfaces in R

    • Register at https://tinyurl.com/3d-regressions-S22

    • Sections: Tuesday 3/15 7-9pm OR Wednesday 3/16 12:30-2:30pm

    • Multiple regressions, are commonly discussed but uncommonly visualized. A new package for Directional Regression Analysis (DiRA) allows you to create interactive 3D graphics of regression surfaces. This workshop will cover visualizing a regression surface, marginal effects, interaction terms, and intersectionality in R. No prior R experience is required

  • Manipulating and Analyzing Data in Excel
    • After break, times TBA. Register here to receive an email when the times are announced.
    • This workshop will demonstrate how to use Excel to
      • organize & sort data
      • create numeric summaries & bar charts of data using pivot tables
      • create scatterplots and maps
    • We'll also discuss the complexity data wrangling, or the process of turning raw data into useable data.
  • Preparing for a Data Scientist's Job Interview: Data Analytics in Stata/R
    • After break, times TBA. Register here to receive an email when times for this and the subsequent workshop are announced.
    • It is common to receive a take home assignment as part of a data science/data analysis interview. We cover many common requirements of such an assignment using a dataset from IMDB. This includes simple data wrangling skills, such as importing data and recoding variables. The fun part comes in the analytics; thinking critically about your data, visualizing your data, and creating regressions. We discuss how to present your results and code. Some experience with Stata is required for the Stata version of the workshop, and some experience with R is required for the R version of the workshop.
  • Preparing for a Data Scientist's Job Interview: Data Wrangling in Stata OR R
    • After break, times TBA. After break, times TBA. Register here to receive an email when times for this and the previous workshop are announced.
    • Data wrangling, or turning your raw data into something usable, is a common task in data scientist job interviews. We will discuss common data wrangling issues, from data structures you import to using different tools to clean your data.  We will also cover (1) the importance of the unit of observation for understanding how to wrangle your data, (2) merging multiple datasets, (3) reshaping data to change the unit of observation, and (4) collapsing data to a higher unit of observation. Some experience with Stata is required for the Stata version of the workshop, and some experience with R is required for the R version of the workshop. Attendance of the Data Analytics workshop (above) is strongly encouraged.
  • Introduction to Stata III (3rd of the two workshop series)
    • After break, times TBA
    • Location and registration by attending prior Stata workshops or instructor permission
    • Using a dataset on county demographics, presidential voting, and deaths of despair, this workshop covers how to use Stata to run and interpret regressions.

______ THE WORKSHOPS LISTED BELOW HAVE ALREADY FINISHED_________

 

  • How to Read Quantitative Papers in the Social Sciences
    • COMPLETED
    • Sections: Wednesday 2/9 12:30-2:30pm, Thursday 2/10 7-9pm, Sunday 2/13 4-6pm
    • The first hour of this session focuses on reading and interpreting quantitative papers. This includes skimming techniques as well as examining regression tables, connecting them to scatterplots and regressions lines, and interpreting other common statistical summaries. The second will overview common issues in regression analysis and some complexities of correlation and causation.
  • Introduction to R
    • COMPLETED February 15-16.
    • This introductory session is based on a survey conducted on workshop participants. We cover the basics of opening files, running commands, creating summary statistics and graphics, dealing with outliers, manipulating variables, and labeling variables. We also work through how to deal with errors (which are inevitable, but manageable, in any statistical package). This will be hands on, practical experience: each participant will be using the program in real time.