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IT: Programming & Software Development
Foundations of Data Analysis in R
Curriculum
1 Section
26 Lessons
30 hours
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Unit 1 — Foundations of Data Analysis in R
26
1.1
The Statistical (and Related) Ideas You Just Have to Know
20 mins
1.2
Installing Packages
20 mins
1.3
Finding Patterns
20 mins
1.4
Means: The Lure of Averages
20 mins
1.5
Measuring Variation
20 mins
1.6
Catching Some Zs
20 mins
1.7
How Many?
20 mins
1.8
Hitting the Curve
20 mins
1.9
Understanding Sampling Distributions
20 mins
1.10
Hypotheses, Tests, and Errors
20 mins
1.11
Hypotheses Built for Two
20 mins
1.12
The UCI (University of California-Irvine) ML Repository
20 mins
1.13
Decision Tree Components
20 mins
1.14
Growing a Random Forest
20 mins
1.15
Some Data to Work With
20 mins
1.16
How It Works
20 mins
1.17
Networks in the Nervous System
20 mins
1.18
Analyzing Retail Data
20 mins
1.19
Examining the Data Set
20 mins
1.20
Getting Your Shine On
20 mins
1.21
The shinydashboard Package
20 mins
1.22
Getting R
20 mins
1.23
Examining Data
20 mins
1.24
Doing the Basics: Base R Graphics, That Is
20 mins
1.25
Calculating the Mean
20 mins
1.26
Back to the Roots: Standard Deviation
20 mins
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