开始时间: 04/22/2022 持续时间: 6 weeks
所在平台: EdxArchive 课程类别: 其他类别 大学或机构: UTAustinX 授课老师: Michael J. Mahometa |
课程主页: https://www.edx.org/archive/foundations-data-analysis-part-1-utaustinx-ut-7-10x
课程评论:没有评论
In a world that’s full of data, we have many questions: How long do animals in a shelter have to wait until they are adopted? Can we predict the growth of Internet usage in a country? Do films with a higher adult rating make more money that other rated films? Luckily, the world is also full of data to help us answer those questions.
This course will 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:
In this first of a two part course, we will cover basic Descriptive Statistics – learning about visualizing and summarizing data, followed by a “Modeling” investigation where we’ll learn about linear, exponential, and logistic functions. We will learn how to interpret and use those functions with basic Pre-Calculus. These two “units” will set the learner up nicely for the second part of the course: Inferential Statistics with a multiple regression cap.
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?
Use R to learn fundamental statistical topics such as descriptive statistics and modeling.