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This course delves into data manipulation, analysis, and visualization with R. It demonstrates the power of R as open-source statistical software, unlocking valuable insights for decision-making across diverse fields.

You'll begin by mastering the basics of R programming, fundamental data structures in R, and file management. You will learn fundamental statistical concepts such as hypothesis testing and regression analysis. You will also learn to leverage well-structured data for creating insightful visualizations using R's robust graphics libraries.

After completing this course, you'll confidently approach data-driven challenges. With proficiency in R, you can efficiently manipulate and analyze data, positioning yourself as a sought-after asset in data-centric roles. Your ability to interpret statistical results and create compelling data visualizations will empower improved decision-making, paving the way for new opportunities for career growth and success across various industries.

Introduction to Data Analysis and Visualization with R

## Features 
We use a histogram to graphically represent the distribution of a dataset and visualize how the data is spread across a range of values. The histogram shows the count or frequency of observations in each interval or bin of the data.


# Features 
We use a histogram to graphically represent the distribution of a dataset and visualize how the data is spread across a range of values. The histogram shows the count or frequency of observations in each interval or bin of the data.


Learn about the use cases for histogram charts and how to create and modify them.

Getting Started

File Management

Data Structures

Data Cleaning

Statistical Analysis

Data Transformation

Data Visualization

Conclusion

Evaluation

Netflix Shows

Histograms

Features