RStudio Bootcamp- for Data Management, Statistics & graphics
RStudio Bootcamp- for Data Management, Statistics & graphics, available at $64.99, has an average rating of 4.6, with 35 lectures, 7 quizzes, based on 16 reviews, and has 82 subscribers.
You will learn about Primary goal is to provide users with an easy way to learn how to perform an analytics task in RStudio. Includes many common tasks, including data management, descriptive summaries, inferential procedures, regression analysis, multivariate methods and graphics. Includes some complex applications such as Simulation Tried to provide a simple classroom type approach that is easy to understand for a new user, and supplied several solutions where deemed necessary. This course is ideal for individuals who are If you intend to be a professional analyst, who use multiple statistical packages daily, this course is for you ! or Useful for statisticians, epidemiologists, economists, engineers, physicians, sociologists and others engaged in data analysis. or This course intends to bolster the analytic abilities of a new user as well It is particularly useful for If you intend to be a professional analyst, who use multiple statistical packages daily, this course is for you ! or Useful for statisticians, epidemiologists, economists, engineers, physicians, sociologists and others engaged in data analysis. or This course intends to bolster the analytic abilities of a new user as well.
Enroll now: RStudio Bootcamp- for Data Management, Statistics & graphics
Summary
Title: RStudio Bootcamp- for Data Management, Statistics & graphics
Price: $64.99
Average Rating: 4.6
Number of Lectures: 35
Number of Quizzes: 7
Number of Published Lectures: 35
Number of Published Quizzes: 7
Number of Curriculum Items: 42
Number of Published Curriculum Objects: 42
Original Price: ₹799
Quality Status: approved
Status: Live
What You Will Learn
- Primary goal is to provide users with an easy way to learn how to perform an analytics task in RStudio.
- Includes many common tasks, including data management, descriptive summaries, inferential procedures, regression analysis, multivariate methods and graphics.
- Includes some complex applications such as Simulation
- Tried to provide a simple classroom type approach that is easy to understand for a new user, and supplied several solutions where deemed necessary.
Who Should Attend
- If you intend to be a professional analyst, who use multiple statistical packages daily, this course is for you !
- Useful for statisticians, epidemiologists, economists, engineers, physicians, sociologists and others engaged in data analysis.
- This course intends to bolster the analytic abilities of a new user as well
Target Audiences
- If you intend to be a professional analyst, who use multiple statistical packages daily, this course is for you !
- Useful for statisticians, epidemiologists, economists, engineers, physicians, sociologists and others engaged in data analysis.
- This course intends to bolster the analytic abilities of a new user as well
R is a general purpose statistical software package used in many fields of research. It is licensed for free – an open source software. It has large user and growing developer base.
I have developed this course for users of R. My primary goal is to provide an easy way to learn how to perform an analytic task in this system, without having to go through complex documentations. This course will give you a classroom like training experience and covers vast topics such as data management, descriptive summaries. inferential procedures, regression analysis, time series analysis, multivariate methods, simulation and graphics.
Therefore this course not only teaches you to clean and analyze data, it also gives you a pavement to develop colorful reports for the purpose of management communication.
I did not attempt to complicate things in as many ways as possible to keep the understanding sweet and simple. I have given a simple approach that is easy to understand for a new user, and have tried to provide several solutions where deemed possible.
I request you to watch the lectures at your own pace and practice the codes one by one with the given and new datasets. This will enhance your learning even more.
Course Curriculum
Chapter 1: Installation and Introduction to R Studio
Lecture 1: Course Introduction
Lecture 2: How to install R Studio ?
Lecture 3: Introduction To R Studio
Chapter 2: Inputs and Outputs
Lecture 1: Input Techniques
Lecture 2: Output Techniques
Chapter 3: Data Management
Lecture 1: Structure and Metadata
Lecture 2: Derived Variables and Data Manipulation
Lecture 3: Merging, Combining and Subsetting Datasets
Lecture 4: Date and Time Variables
Chapter 4: Statistical and Mathematical Functions
Lecture 1: Probability Distribution and Random Number Generation
Lecture 2: Mathematical Functions
Lecture 3: Matrix Operations
Chapter 5: Programming and Operating System (OS) Interface
Lecture 1: Programming and OS interface
Chapter 6: Common Statistical Procedures
Lecture 1: Summary Statistics
Lecture 2: Bivariate Statistics and Tests for Continuous Variables
Chapter 7: Linear Regression and ANOVA
Lecture 1: Regression Basics
Lecture 2: Linear Regression and ANOVA
Lecture 3: Residuals and Diagnostic Plots
Chapter 8: Regression Generalizations and Modeling
Lecture 1: Binary Logistic Regression – Basics
Lecture 2: Binary Logistic Regression – R Studio
Lecture 3: Poisson Regression – R Studio
Lecture 4: Factor Analysis Using R Studio
Lecture 5: Survival Analysis in R – Using Kaplan-Meier Plot
Lecture 6: Survival Analysis in R – Cox Hazard Regression
Chapter 9: Graphical Compendium
Lecture 1: Univariate Plots
Lecture 2: Bivariate Plots
Lecture 3: Some Special Purpose Plots – Maps and Interaction Plots
Lecture 4: Some Special Purpose Plots – Circular and Normal Q-Q Plots
Lecture 5: ROC Curve
Chapter 10: Graphical Options and Configurations
Lecture 1: Graphical Options in Detail
Lecture 2: Options and Paramters
Chapter 11: Time Series Analysis
Lecture 1: Time Series Analysis Using R – Part I
Lecture 2: Time Series Analysis Using R – Part II
Chapter 12: Simulation
Lecture 1: Simulation Part I – Categorical Data, tTest & Logistic Regression Simulation
Lecture 2: Simulation Part II – Monty Hall Simulation
Instructors
-
Soumyajit Halder
Operations Manager
Rating Distribution
- 1 stars: 1 votes
- 2 stars: 0 votes
- 3 stars: 0 votes
- 4 stars: 0 votes
- 5 stars: 15 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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