Gain insights into data manipulation, analysis, and visualization with R. Learn statistical concepts, create insightful visualizations, and empower decision-making to excel in data-centric roles.

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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

## The concept of regression
**Regression analysis** is a statistical method for examining the relationships between a dependent variable and one or more independent variables. Regression calculates the amount of change in the dependent variable when the independent variable moves one unit. 
It aims to prove the relationship statistically.

To do that, regression analysis tries to formulate the relationship between the variables as much as possible 
by using a linear line which is called the **regression line**.

For example, the chart below shows the locations of the data points across the axes. Can we claim that there is a relationship between the variables?



# The concept of regression
**Regression analysis** is a statistical method for examining the relationships between a dependent variable and one or more independent variables. Regression calculates the amount of change in the dependent variable when the independent variable moves one unit. 
It aims to prove the relationship statistically.

To do that, regression analysis tries to formulate the relationship between the variables as much as possible 
by using a linear line which is called the **regression line**.

For example, the chart below shows the locations of the data points across the axes. Can we claim that there is a relationship between the variables?



Learn about regression analysis and the implementation of linear models in R.

Getting Started

File Management

Data Structures

Data Cleaning

Statistical Analysis

Data Transformation

Data Visualization

Conclusion

Evaluation

Netflix Shows

Regression Analysis

The concept of regression