Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
8 Hour(s) 34 Minute(s)
Language
English
Taught by
Syed Mohiuddin
Rating
1 views
Course Overview
Data Analysis & Data Science using R : Descriptive & Inferential Statistics, Data Visualization, Hypothesis Testing
Welcome to this course of R for Data Analysis, Statistics, and Data Science, and become an R Professional which is one of the most favored skills, that employers need.
Whether you are new to statistics and data analysis or have never programmed before in R Language, this course is for you! This course covers the Statistical Data Analysis Using R programming language. This course is self-paced. There is no need to rush, you can learn on your own schedule.
This course will help anyone who wants to start a саrееr as a Data Analyst or Data Scientist.
This course begins with the introduction to R that will help you write R code in no time. This course will provide you with everything you need to know about Statistics.
In this course we will cover the following topics:
· R Programming Fundamentals
· Vectors, Matrices & Lists in R
· Data Frames
· Importing Data in Data Frame
· Data Wrangling using dplyr package
· Qualitative and Quantitative Data
· Descriptive and Inferential Statistics
· Hypothesis Testing
· Probability Distribution
This course teaches Data Analysis and Statistics in a practical manner with hands-on experience with coding screen-cast.
Once you complete this course, you will be able to perform Data Analysis to solve any complex Analysis with ease.
Course Content
- 10 section(s)
- 85 lecture(s)
- Section 1 Introduction
- Section 2 Basic R Programming Fundamentals
- Section 3 Vectors, Matrices, Lists and Dataframes
- Section 4 Data Handling using dplyr Package
- Section 5 Data Visualization in R
- Section 6 Qualitative and Quantitative Data
- Section 7 Descriptive Statistics
- Section 8 Bivariate and Multivariate Data
- Section 9 Probability Distributions
- Section 10 Inferential Statistics - Hypothesis Testing
What You’ll Learn
- About Qualitative, Quantitative, Bivariate and Multivariate Data
- Descriptive Statistics ie of Mean, Median, Quartiles, Quantiles, Variance and Standard Deviation
- Correlation and Covariance
- Applications of Descriptive Statistics on Stock Price Data
- Probability Distributions
- Inferential Statistics - Hypothesis Testing
- Fundamentals of R Programming & Work with RStudio
- Use Vectors, Matrices, Lists, Data Frames
- Importing and Handling CSV files
- Using dplyr Package for Data Wrangling or Handling
- Data Visualization in R
Skills covered in this course
Reviews
-
AAnita Ambrosi
Completissimo e dettagliato! Per un neofita necessita di essere seguito con grande attenzione (o, come nel mio caso, essere riascoltato più volte).
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MMayur Bhoir
Good content..
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PPranati Swain
this isn't upto the mark. I was expecting more learning on data science approach.
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SSlobodanka Kojic
Very detailed and well explained foundation . Expected more complexity in the end of the course.
