Product Image

Data Science Research Methods: R Edition

In this course, you will become familiar with the essentials of the exploration procedure—from developing a decent inquiry to designing great information assortment methodologies to putting outcomes in context.


Learning Style





18 Hours

Course Duration

Course Info

Download PDF


See Sample

About Individual Course:
  • Individual course plan gives you access to this course
/ Each
94 Learners Have Enrolled For This Course
When you subscribe, you get:
Learn Subscription plan gives you access to this course and over 836 other popular courses
On Sale!
Now Only $39.99 Regular Price $44.99
Now Only $39.99 Regular Price $44.99
/ Month
  • Buy 1-5 Enrollments And Save 0% ($39.99 monthly.)
  • Buy 6-9 Enrollments And Save 10% ($35.99 monthly.)
  • Buy 10-19 Enrollments And Save 20% ($31.99 monthly.)
  • Buy 20-above Enrollments And Save 30% ($27.99 monthly.)
94 Learners Have Enrolled For This Course

You have already taken demo for this course.

If you want to get access to demo again, feel free to contact our support at (855) 800-8240

In this course, you will become familiar with the essentials of the exploration procedure—from developing a decent inquiry to designing great information assortment methodologies to putting outcomes in context.

Course Information

About this course:

Data researchers are frequently trained in the examination of information. But, the objective of data science is to deliver a decent understanding of certain issues or thoughts and create valuable models on this understanding. In view of the principle of "trash in, trash out," it is essential that the data researcher realizes how to assess the nature of the information that comes into data examination. This is particularly the situation when information is gathered explicitly for some analysis (e.g., an overview).

In this course, you will become familiar with the essentials of the exploration procedure—from developing a decent inquiry to designing great information assortment methodologies to putting outcomes in context. In spite of the fact that the data researcher may frequently have a key impact on information investigation, the whole research process must work durably for legitimate insights to be gathered.

Created as a language in view of measurable analysis and modeling, R has become a basic device for doing genuine Data Science. With this version of Data Science Research Methods, the entirety of the labs are finished with R, while the videos are tool-agnostic. In the event that you lean toward your Data Science to be finished with Python, it would be ideal if you see Data Science Research Methods: Python Edition.

Course Objective:

  • Data science research design.
  • Data analysis and inference.
  • Survey Design and Measurement
  • Planning for Analysis
  • Power and Sample Size Planning
  • Reliability and Validity
  • Experimental data modeling and analysis.
  • Bivariate and Multivariate Designs
  • Between and Within Groups Experimental Designs
  • Factorial Designs
  • Knowledge Check


Data Analyst



  • Fundamental information on math
  • Some programming experience – R is liked.
  • A willingness to learn through self-guided investigation.


More Information

More Information
SubjectsApp Development
Lab AccessNo
Learning StyleSelf-Paced Learning
Learning TypeCourse
Course Duration18 Hours


Write Your Own Review
Only registered users can write reviews. Please Sign in or create an account

Course Expert:


Tom Robertson
(Data Science Enthusiast)

Tom is an innovator first, and then a Data Scientist & Software Architect. He has integrated expertise in business, product, technology and management. Tom has been involved in creating category defining new products in AI and big data for different industries, which generated more than hundred million revenue cumulatively, and served more than 10 million users.
As a Data Scientist and Software Architect Tom has extensive experience in data science, engineering, architecture and software development. To date Tom has accumulated over a decade of experience in R, Python & Linux Shell programming.

Tom has expertise on Python, SQL, and Spark. He has worked on several libraries including but not limited to Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, SciPy, NLTK, Keras, and Tensorflow.

This Subscription Includes:

Virtual instructor Led

Virtual Classroom Courses

Our virtual instructor-led courses give you access to live instructors training you with other live students in a virtual classroom environment.

< Play Video >
250+ Virtual Instructor-Led Courses

Online Self-Paced Courses

Take self-paced online courses at your convenience and own pace, with unlimited access to courses in various emerging technologies.

900+ Self-Paced Courses

E-books blogs, case studies, articles

As part of informal learning, our platform will recommend E-books, whitepapers, case studies, articles, and videos. This is AI curated content closely aligned with your learning objectives.

E-books, blogs, & case studies


Set yourself on the right path with self-assessments that allow you to gauge what you already know. Assessments then personalize your learning paths, and allow you to focus only on what you need to succeed.


Full Learning Dashboard & Analytics

Access all your enrolled, completed, course statistics, and community discussions from one centralized and intuitive learning dashboard with built in analytics, course tracking, time spent, and more.


QuickStart Discussions

Engage with other learners where you can directly chat, ask questions, and socialize with other learners experts and instructors on a course subject.

Community Access Community Access

Virtual Labs

Videos and lectures only go so far. Get real world, hands-on practice with virtual labs (not available for all courses).

Virtual Labs Virtual Labs
Live Instructor Support

Live Instructor Mentoring & Support

Get your IT problems solved through a community of mentors, experts and peers. Get live help from experts to answer questions on course material or guidance on a project.

Mentoring & Discussions Mentoring & Discussions

Career Paths

Start a learning pathway towards understanding and mastering your career. With QuickStart career paths, you can fully understanding and being the best in your field.

Learning Paths Learning Paths

Informal Learning

Access to AI curated content from various content publishers which can help in self-directed learning.

Informal Learning Informal Learning
click here