Learn how to harness data to drive success with this introduction to data visualization. The course will first ask you to consider what data is and what questions can be answered using data, and then moves into how to develop a research question describe variables and relationships between variables, basic statistics, and how to present results. Lastly you will learn how to use SAS or Python to manage and visualize your data.
Learn how to use relational databases in business analysis with this introductory course. You will learn how relational databases work, how to use entity-relationship diagrams, and understand how to collect data in different business contexts. This course will ultimately equip you with the skills you need to properly collect data and gain insights into the best ways to improve business performance, as well provide you with hands on practice with real databases and a portfolio you can show future employers.
Get started with linear regression models with this Duke University course. Learn about the underlying theory, as well as how to fit, examine, and utilize regression models to analyze the relationship between multiple variables. Apply what you learn to data examples using R and RStudio.
This beginner level course serves as an introduction to sampling and exploring data, basic probability theory, and Bayes rule. Explore various types of sampling methods and learn exploratory data analysis techniques such as numeric summary statistics and basic data visualization. In addition, you will also learn to use R and RStudio for lab exercises and a final project.
Learn all the necessary skills to get started with Tableau. The Consumer Learning Path covers Tableau basics such as navigating the interface, foundational data literacy concepts, using Tableau Online and Server, and how different user types engage with web content.
An introductory course to SPSS and basic statistics used in the social sciences. The tutorials will guide you, step-by-step, through the basics of SPSS, as well as how to produce commonly used statistics. No prior experience with SPSS necessary.
10am-8pm
8am-10pm
Closed
This virtual hands-on workshop will introduce a few selected R packages (available in RStudio) for creating simple maps. The topics covered include installing R packages, writing and running commands from R Script, plotting data, plus adding headers, labels and a legend to creating a map layout for export. This workshop is most suitable for novice to experienced R users who have never used the software before for mapping data. (This is NOT an "Introduction to R" workshop)