Scatter plot in R | R Programming Certification Training | R Tutorial | Uplatz

In this tutorial, we dive into the essentials of creating a scatter plot in R. Whether you’re just starting or brushing up on your R programming skills, learning how to use the scatter plot function is crucial. Scatter plots are a foundational tool in data visualization, helping you understand the relationship between two variables. By using the plot function in R, you can easily generate scatter plots to visualize data points, assess correlations, and identify patterns. This video will guide you through the syntax and usage of this function, showing you how to customize your plots with different options.

Scatter Plot in R | R Programming Certification Training | R Tutorial will help you master the basics of creating and customizing scatter plots in R. We’ll cover key topics such as adding titles, labels, and colors to make your plots more informative and visually appealing. This training is designed to be straightforward and practical, so you can start applying these techniques to your own data sets right away. Scatter Plot in R | R Programming Certification Training | R Tutorial is perfect for anyone looking to enhance their data visualization skills. Don’t forget to subscribe and share if you find the video helpful!

R is a programming language and environment used for statistical computing, graphics and data analytics. R is simple and well-developed programming which includes, condition, loops, user-defined recursive function, input & output facilities, data handling, storage facility, etc. R is one of the widely used programming languages and supported by world’s data scientist, as it provides operators for calculating arrays, list and vectors. It provides tools and graphical facility for data analysis and its display. R is widely used by researcher, marketer and data analyst to retrieve, analyse and visualise the data.One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control.

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Syllabus

1. Understanding of R System
2. Installation and configuration of R-Environment and R-Studio
3. Understanding R Packages, their installation and management
4. Understanding of nuts and bolts of R:
a. R program Structure
b. R Data Type, Command Syntax and Control Structures
c. File Operations in R
5. Application of R Programming in Daily life problems
6. Preparing Data in R
a. Data Cleaning
b. Data imputation
c. Data conversion
7. Visualizing data using R with different type of graphs and charts
8. Applying R Advance features to solve complex problems and finetuning R Processes

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