Use R to learn fundamental statistical topics such as descriptive statistics and modeling.
Starts on February 2, 2016
- Length: 6 weeks
- Effort: 3-6 hours/week
-
Price:
Free
Add a Verified Certificate for $49 - Institution: UTAustinX
- Subject: Math
- Level: Introductory
- Languages: English
- Video Transcripts: English
Prerequisites
- Basic math – arithmetic and algebra
- Students should be comfortable solving math problems such as: 25 = 15 + 2x
- Comfort with a computer and comfort using a novel computer software
About this course
In this first part of a two part course, we’ll walk
through the basics of statistical thinking – starting with an
interesting question. Then, we’ll learn the correct statistical tool to
help answer our question of interest – using R and hands-on Labs.
Finally, we’ll learn how to interpret our findings and develop a
meaningful conclusion.
This course will consist of:
Both parts of the course are intended to cover the same material as a typical introductory undergraduate statistics course, with an added twist of modeling. This course is also intentionally devised to be sequential, with each new piece building on the previous topics. Once completed, students should feel comfortable using basic statistical techniques to answer their own questions about their own data, using a widely available statistical software package (R).
Join us in learning how to look at the world around us. What are the questions? How can we answer them? And what do those answers tell us about the world we live in?
Want to learn more? Be sure to enroll in Foundations of Data Analysis - Part 2, starting March 22, 2016.
This course will consist of:
- Instructional videos for statistical concepts broken down into manageable topics.
- Guided questions to help your understanding of the topic.
- Weekly tutorial videos for using R Scaffolded learning with Pre-Labs (using R), followed by Labs where we will answer specific questions using real-world datasets.
- Weekly wrap-up questions challenging both topic and application knowledge.
Both parts of the course are intended to cover the same material as a typical introductory undergraduate statistics course, with an added twist of modeling. This course is also intentionally devised to be sequential, with each new piece building on the previous topics. Once completed, students should feel comfortable using basic statistical techniques to answer their own questions about their own data, using a widely available statistical software package (R).
Join us in learning how to look at the world around us. What are the questions? How can we answer them? And what do those answers tell us about the world we live in?
Want to learn more? Be sure to enroll in Foundations of Data Analysis - Part 2, starting March 22, 2016.
What you'll learn
- Descriptive Statistics
- How to visualize data
- Data structure and how to examine it
- Basic R programming (guided through tutorials)
- Simple modeling of linear, exponential, and logistic growth
Course Syllabus
Week One: Introduction to Data- Why study statistics?
- Variables and data
- Getting to know R and RStudio
- Graphs and distribution shapes
- Measures of center and spread
- The Normal distribution
- Z-scores
- The scatterplot
- Correlation
- Contingency tables
- Conditional probability
- Examining independence
- What is a function?
- Least squares
- The Linear function – regression
- Exponential data
- Logs
- The Logistic function model
- Picking a good mode
Meet the instructor
-
Michael J. MahometaLecturer and Senior Statistical Consultant University of Texas at Austin
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