The Quantitative Reasoning (QR) Center offers workshops on various quantitative topics each semester. In the past, we have offered workshops on Microsoft Excel, PowerBI, and MaxQDA. These workshops are open to students, facutly, & staff. For the fall 2024 semester, we are hosting three different sets of workshops, which are described below. All workshops will take place in the Data & Scientific Reasoning Lab. If you plan to attend any of these workshops, please RSVP here.
| Title | Dates/Times | Description |
|---|---|---|
| Introduction to Pivot Tables | Oct. 3rd 12:00 OR* Oct. 4th 12:00 pm | This workshop will introduce participants to using pivot tables in Microsoft Excel. Participants should have basic Excel skills to attend this workshop. Pivot tables are commonly used in industries related to data, finance, business, and accounting to sort, reorganize, pivot, collapse, and compare data sets. In this workshop, participants will be introduced to a variety of tips and tricks for creating and using pivot tables. |
| Introduction to GIS (Part 1) | Oct. 23rd 12:00 pm | This workshop is the first in a two-part series. Participants will be introduced to ESRI ArcGIS Pro and an overview of GIS will be provided. The session will introduce types of data, loading shapefiles, changing coordinate systems, and creating a map. No background in GIS is necessary to attend this workshop. |
| GIS Aesthetics and Analyses (Part 2) | Oct. 30th 12:00 pm | This workshop is the second in a two-part series. If participants have no background in GIS, then it is highly recommended that they attend the first session, too. This workshop will use the maps from the previous workshop to explore types of maps, colors, symbology, and how to make the map your own. We will also begin to explore data manipulation and built-in analytical tools. |
| Introduction to R | Nov. 6th 12:00 pm OR* Nov. 7th 3:00 pm | This workshop is designed to give participants an introduction to programming in R. Some background in coding is helpful, but no prior R experience is needed. This session will use select R packages (dplyr, tidyr, tidyverse, ggplot2) to begin to import, clean, analyze, and visualize data. Some coverage of troubleshooting and crowdsourcing will also be provided. |
*workshop repeats -- choose only one session to attend
If you have any questions, please contact Jackie Campbell at campbeja@dickinson.edu.