Statistics for Data Analysis Using R
What you'll learn
- You will first learn the basic statistical concepts, followed by application of these concepts using R Studio. This course is a nice combination of theory and practice.
- Descriptive Statistics - Mean, Mode, Median, Skew, Kurtosis
- Inferential Statistics - One and two sample z, t, Chi Square, F Tests, ANOVA, TukeyHSD and more.
- Probability Distributions - Normal, Binomial and Poisson
- You will learn R programming from the beginning level.
Course content
- Preview01:31
- 06:04Installing R and R Studio (Windows)
- Preview11:40
- 06:43The First Look at the Functions in R
- 06:14Saving the R Script File
- 04:45Data Types in R
- 02:11Simple Mathematical Operations
- 00:06Download - Section 1 Notes and Codes
- 00:04Section 1 - Practice Assignment
Requirements
- Basic school level mathematics will be helpful.
- You will need to download and install R and R Studio on your PC or laptop. Both R and R Studio are for Free Software.
Description
Perform simple or complex statistical calculations using R Programming! - You don't need to be a programmer for this :)
Learn statistics, and apply these concepts in your workplace using R.
The course will teach you the basic concepts related to Statistics and Data Analysis, and help you in applying these concepts. Various examples and data-sets are used to explain the application.
I will explain the basic theory first, and then I will show you how to use R to perform these calculations.
Following areas of statistics are covered:
Descriptive Statistics - Mean, Mode, Median, Quartile, Range, Inter Quartile Range, Standard Deviation. (Using base R function and the psych package)
Data Visualization - 3 commonly used charts: Histogram, Box and Whisker Plot and Scatter Plot (using base R commands)
Probability - Basic Concepts, Permutations, Combinations (Basic theory only)
Population and Sampling - Basic concepts (theory only)
Probability Distributions - Normal, Binomial and Poisson Distributions (Base R functions and the visualize package)
Hypothesis Testing - One Sample and Two Samples - z Test, t-Test, F Test, Chi-Square Test
ANOVA - Perform Analysis of Variance (ANOVA) step by step doing the manual calculation and by using R.
Who this course is for:
- Anyone who want to use statistics to make fact based decisions.
- Anyone who wants to learn R and R Studio for career in data science.
- Anyone who thinks Statistics is confusing and wants to learn it in plain and simple language.
Featured review
![Kipchumba Brian](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
Instructor
- 4.5 Instructor Rating
- 30,121 Reviews
- 146,828 Students
- 25 Courses
PMI-PMP, IRCA Registered Lead Auditor, ASQ - CSSBB, CQA, CQE, CMQ/OE, IIA - CIA
Sandeep Kumar has more than 35 years of Quality Management experience. He has worked as Quality Manager/Director on a number of projects, including Power, Oil and Gas and Infrastructure projects.
In addition, he provides consulting services to implement Lean Six Sigma to improve performance.
His areas of specialization include Quality Assurance, ISO 9001:2015, Lean, Six Sigma, Risk Management, QMS Audits, Supplier Quality Surveillance, Supplier Pre-qualification, Construction Quality, Mechanical Inspection and Quality Training.
Professional Qualifications:
His professional qualification/certifications include:
• ASQ-CSSBB, Certified Six Sigma Black Belt
• ASQ-CMQ/OE Certified Manager of Quality/Organizational Excellence
• PMI-PMP Certified Project Management Professional
• IRCA Registered Lead Auditor (QMS-2015)
• IIA-CIA Certified Internal Auditor
• ASQ-CSSGB, Certified Six Sigma Green Belt
• ASQ-CQA Certified Quality Auditor
• ASQ-CQE Certified Quality Engineer