Statistics in R - The R Language for Statistical Analysis
Statistics made easy with the open source R language. Learn about Regression, Hypothesis tests, R Commander ...
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What You'll Learn in This Course
Master key concepts and practical skills through structured learning modules. By completing this curriculum, you'll gain valuable expertise applicable to real-world scenarios.
Learning Outcome 1
know which statistical test to use for a given question
Learning Outcome 2
know how to perform the most important statistical tests in R
Learning Outcome 3
know how to perform regression modeling in R
Learning Outcome 4
have a very good understand of statistical testing and regressions
Learning Outcome 5
use R Commander as alternative to RStudio
Skills You'll Develop
This comprehensive Statistics in R - The R Language for Statistical Analysis curriculum is designed to take you from foundational concepts to advanced implementation. Each module builds upon the previous, ensuring a structured learning path that maximizes knowledge retention and practical application.
Course Requirements & Target Audience
Understand what you need to succeed in this course and determine if it's the right fit for your learning goals
Prerequisites & Requirements
What you need before starting this Statistics in R - The R Language for Statistical Analysis course:
- solid understanding of R programming - up to my "R Level 1" course
- R and R Studio ready on your computer
- basic understanding of statistics (descriptive, inferential, regression)
- high interest in data analysis
Who This Course Is For
This course is perfect for:
- Motivated learners at any level
- Self-paced students
- Anyone interested in the subject
This course might not be suitable if:
- • You're looking for a quick tutorial rather than comprehensive learning
- • You prefer learning without structured curriculum
- • You need highly specialized or niche content
Course Information & Details
Everything you need to know about this online course, from duration to certification
Course Instructor
R-Tutorials Training
Expert instructor with industry experience
Course Language
English
All materials in English
Start Your Learning Journey Today
This online course offers comprehensive training with expert instruction, practical exercises, and a certificate of completion. Join thousands of students advancing their careers through quality online education.
Course Enrollment
Professional Course
Investment around $54.99
Pricing may vary. Check the course provider for current promotions and exact pricing.
What's Included
- 3.5 hours on-demand video
- 2 downloadable resources
- 4 articles
- Access on mobile and TV
- Certificate of Completion
- Full lifetime access
Affiliate disclosure: if you enroll through links on this page, the course provider may pay us a commission. This comes at no extra cost to you and does not influence how we describe courses.
- ✓Instant access after enrollment
- ✓Learn at your own pace
- ✓Direct enrollment with Udemy
Where this course fits
Certifications in this area
- Microsoft Certified: Azure Data Fundamentals · Foundational
- Microsoft Certified: Azure AI Fundamentals · Foundational
- AWS Certified AI Practitioner · Foundational
- Microsoft Certified: Fabric Data Engineer Associate · Associate
- Microsoft Certified: Power BI Data Analyst Associate · Associate
- Databricks Certified Data Engineer Associate · Associate
Concepts behind this area
Computer Vision
Computer vision is the branch of artificial intelligence that turns images and video into structured answers: what is in the frame, where it sits, which pixels belong to it, and where it moves next.
Agentic AI
Agentic AI is software that wraps a language model in a loop where it can request actions from real tools, read what each action returns, and choose the next move until the job is finished or a rule stops it.
MLOps
MLOps is the engineering practice of keeping a trained model useful in production: recording what produced it, serving it, watching for the day its answers stop matching the world, and retraining or reverting before anyone downstream is harmed by the gap.
Data Analysis
Data analysis is the practice of interrogating data to answer a specific question, and of establishing how much weight the answer can bear.
Data Wrangling
Data wrangling is the work of repairing and reshaping real records, and of deciding what their gaps and inconsistencies mean, until a table can be trusted with the question being asked of it.
Data Visualization
Data visualisation is the practice of encoding numbers as position, length and colour so that a comparison a reader would otherwise have to calculate becomes something they can simply see.
The field, explained: Artificial Intelligence & Machine Learning · Data & Analytics
Wider context: the fields we cover, the glossary and certification exams, all written by us rather than pulled from a provider feed.
