Quickly understanding variables in a dataset can be time-consuming. In this course, Building Tables in R, you’ll learn to develop tables, proportions, and marginal frequencies in R. First, you’ll explore the table function with two- and three-way tables. Next, you’ll discover proportions for these tables. Finally, you’ll learn how to build a marginal frequency table. When you’re finished with this course, you’ll have the skills and knowledge of developing tables for data in R needed to understand customer data and prepare for advanced analysis.
Emilee has an M.S. in Business Statistics from Mercer University and currently works as a Data Scientist. She has worked with data for 5+ years, spending the majority of her time in financial industry. She created marketing solutions at an investment management firm, consulted with lenders on risk models at a credit bureau, and currently works in consumer banking. Through her love of data, she has always had a passion for teaching. Prior to grad school, she worked as a teacher.
Course Overview Hi, everyone. My name is Emilee McWilliams, and welcome to my course, Building Tables with R. I'm a data scientist in the financial industry, and I've seen a variety of data analysis projects. And many times in data, there's a need to quickly summarize tables and datasets with frequencies, including showing totals and percentages of data points. In this course, we're going to understand how frequency tables summarize data, how to build those tables in R, and then apply these to a business problem. Some of the major topics we will cover include understanding frequency tables, summarizing data points, building tables with R code, and discovering frequency tables, proportions, and marginal tables for data analysis. By the end of this course, you'll know how to create frequency tables in R, summarizing data necessary for a business audience. No prior knowledge of R is required. I hope you'll join me on this journey to learn R with the Building Tables with R course, in Pluralsight