Stat 427: R Programming
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Lectures
Schedule
Module 1: Getting Started
Module 2: R Scripts
Module 3: Functions
Module 4: Basic Graphs
Module 5: Data Input and Output
Module 6: Iterative Data Processing
Module 7: Logic and Control
Module 8: R Markdown and Packages
Module 9: Mathematical Functions
Module 10: Data Validation, Cleaning, Combining Datasets
Module 11: Matrix Arithmetic
Module 12: Systems of Linear Equations
Module 13: Advanced Graphs
Module 14: Probability and Simulation
Module 15: Introductory Inferential Methods
Supplemental Topics
>
Module 16: Real World Examples
Module 17: Fitting Models to Data
Review
>
Intro Class lectures
Coursework
Instructions
Labs
Project
R
Code
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Learning Outcomes
Learn some commonly used math functions, often used for transformations in data analyses. While they are not the only functions used with data, they are some of the most commonly used.
Key Concepts
Quadratic functions
Trigonometric functions
Exponential and Logarithmic functions
Lecture
pdf
Links
Quick-R
Home
Course Logistics
Syllabus
Contact
Dates
Links
Lectures
Schedule
Module 1: Getting Started
Module 2: R Scripts
Module 3: Functions
Module 4: Basic Graphs
Module 5: Data Input and Output
Module 6: Iterative Data Processing
Module 7: Logic and Control
Module 8: R Markdown and Packages
Module 9: Mathematical Functions
Module 10: Data Validation, Cleaning, Combining Datasets
Module 11: Matrix Arithmetic
Module 12: Systems of Linear Equations
Module 13: Advanced Graphs
Module 14: Probability and Simulation
Module 15: Introductory Inferential Methods
Supplemental Topics
>
Module 16: Real World Examples
Module 17: Fitting Models to Data
Review
>
Intro Class lectures
Coursework
Instructions
Labs
Project
R
Code
Information