Interpreting Data Using Descriptive Statistics with R

Learn how to compute and interpret some of the most powerful statistical measures across a variety of industries. From mean, median and mode to variance and percentiles, make an impact efficiently in businesses and organizations.
Course info
Level
Beginner
Updated
Aug 13, 2019
Duration
1h 24m
Table of contents
Description
Course info
Level
Beginner
Updated
Aug 13, 2019
Duration
1h 24m
Description

Interpreting statistics can be confusing or time consuming. In this course, Interpreting Data using Descriptive Statistics with R, you will learn foundational knowledge to efficiently describe a data set using R. First, you will learn how to calculate mean, median, and mode. Next, you will discover variance and standard deviation. Finally, you will explore how to compare datasets using these statistics. When you’re finished with this course, you will have the skills and knowledge of computing these statistics needed to explain a dataset.

About the author
About the author

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.

Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
Hi everyone, my name is Emilee McWilliams, and welcome to my course, Interpreting Data Using Descriptive Statistics with R. I'm a data scientist in the financial industry with experience starting from investment management, and I've seen a variety of business problems, and many times in finance, the simple summary statistics on a large dataset can provide impactful insight to executives and clients with a business mindset. In this course, we are going to interpret those descriptive statistics for a dataset of loan applicants. Some of the major topics that we will cover include central tendency, variance, percentiles and confidence intervals, and how to find and apply these quickly in R. By the end of this course, you'll know how to find insights into a dataset quickly and easily. Before beginning the course, you should be familiar with simple R functions. I hope you'll join me on this journey to learn R, with the Interpreting Data Using Descriptive Statistics with R course, at Pluralsight.