Course Report
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Course Features
Duration
4 hours
Delivery Method
Online
Available on
Limited Access
Accessibility
Mobile, Desktop, Laptop
Language
English
Subtitles
English
Level
Intermediate
Teaching Type
Self Paced
Video Content
4 hours
Course Description
Highlights
Pedagogy
Top 10 Percentile
Rating & Reviews
Top 30 Percentile
Parameters
Pedagogy
Acquire all major R Programming skills in this course for seamless integration into your daily life. Develop a versatile skill set, allowing you to confidently apply what you've learned in various practical scenarios, enhancing your daily experiences and overall proficiency. An exceptional course in R Programming, this stands out for its Self Paced learning approach. Learners have the flexibility to progress at their own speed, tailoring the experience to their individual needs.
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Rating & Reviews
This highly acclaimed course is among the top-rated in R Programming, boasting a rating greater than 4 and an overall rating of 5.0. Its exceptional quality sets it apart, making it an excellent choice for individuals seeking top-notch learning experience in R Programming.
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Course Overview
Virtual Labs
International Faculty
Post Course Interactions
Hands-On Training,Instructor-Moderated Discussions
Skills You Will Gain
Prerequisites/Requirements
Foundations of Inference
Intermediate Regression in R
What You Will Learn
You will learn how to create interval estimates for the effect size as well as how to determine if the effect is significant
Throughout the course, you'll gain more practice with the dplyr and ggplot2 packages, and you will learn about the broom package for tidying models; all three packages are invaluable in data science
In the first chapter, you will understand how and why to perform inferential (instead of descriptive only) analysis on a regression model
In this chapter you will learn about the ideas of the sampling distribution using simulation methods for regression models
In this chapter you will learn about how to use the t-distribution to perform inference in linear regression models
Additionally, you will consider the technical conditions that are important when using linear models to make claims about a larger population
Course Instructors
Course Reviews
Average Rating Based on 3 reviews
100%