Interpreting Data Using Descriptive Statistics with R

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Emilee McWilliams

1:24:07

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00. Course Overview

00. Course Overview.mp4

01:20

01. Understanding Types of Variables and Measurement Scales

00. Introduction and Data Types.mp4

02:33

01. Measurement Scales.mp4

03:04

02. Demo.mp4

02:41

03. Summary.mp4

01:30

02. Interpreting Measures of Location within R

00. Intro and Topic Outline.mp4

00:54

01. Central Tendency.mp4

02:05

02. How to Use Mean .mp4

01:16

03. Demo - Mean.mp4

01:59

04. When to Use Median .mp4

03:51

05. Demo - Median.mp4

03:09

06. Mode with Two Data Types.mp4

01:17

07. Demo - Mode.mp4

02:21

08. Percentiles and Quartiles .mp4

02:36

09. Demo - Percentiles and Quartiles.mp4

01:55

10. Summary.mp4

02:21

03. Measuring Variance with Descriptive Statistics

00. Intro and Topic Outline.mp4

00:50

01. Variance for Population and Sample.mp4

04:59

02. Demo - Variance Applied to Home Loans.mp4

02:39

03. Standard Deviation for Population and Sample.mp4

02:26

04. Demo - Standard Deviation.mp4

03:52

05. Range, Interquartile Range, and Box and Whisker Plot.mp4

03:24

06. Demo - Range, Interquartile Range, and Box and Whisker Plot.mp4

02:58

07. Coefficient of Variation.mp4

01:25

08. Demo - Coefficient of Variation.mp4

02:47

09. Summary.mp4

00:43

04. Creating Credit Application Summary for Month over Month Data

00. Introduction and Topics Covered.mp4

01:24

01. Dataset and Goal of Analysis.mp4

01:36

02. Demo - Importing and Converting Data Types.mp4

03:20

03. Demo - Library(dplyr) Package for Summary Statistics of Entire Dataset.mp4

02:45

04. Demo - Best Function for Summary Statistics by Group.mp4

02:00

05. Demo - Analyze and Interpret Month over Month Summary Statistics.mp4

05:12

05. Applying Standard Error and Confidence Estimates to a Sample Mean

00. Intro and Course Outline.mp4

00:43

01. Standard Error and Confidence Interval.mp4

03:36

02. Demo.mp4

02:08

03. Summary.mp4

00:28

Description

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.

What You'll Learn?

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.

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Data Science

R Programming

Emilee McWilliams

Instructor's Courses

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 finance. 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 and enjoys simplifying complex topics and helping students learn.

Pluralsight

View courses Pluralsight

Pluralsight, LLC is an American privately held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 7,000 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.