Mastering Data Analysis with R [Video]

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Mastering Data Analysis with R [Video]

Dr. Bharatendra Rai

Master R's advanced techniques to solve real-world problems in data analysis and gain valuable insights from your data
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Video Details

ISBN 139781787125100
Course Length3 hours and 43 minutes

Video Description

With its popularity as a statistical programming language rapidly increasing with each passing day, R is increasingly becoming the preferred tool of choice for data analysts and data scientists who want to make sense of large amounts of data as quickly as possible. R has a rich set of libraries that can be used for basic as well as advanced data analysis tasks. If you have a basic understanding of data analysis concepts and want to take your skills to the next level, this video is for you. Spanning over four hours, it contains carefully selected advanced data analysis concepts such as: cluster analysis; time-series analysis; Association mining; PCA (Principal Component Analysis); handling missing data; sentiment analysis; spatial data analysis with R and QGIS; advanced data visualization with R and ggplot2.

Throughout the video, readers will use the various topics they've learned about to analyze real-world datasets from various industry sectors. By the end of the tutorial, readers will have a thorough understanding of advanced data analysis concepts and how to implement them in R.

Style and Approach

This course supplies in-depth content balanced with tutorials that put the theory into practice. This video course is a practical tutorial to help you get beyond the basics of data analysis with R, using real-world datasets and examples.

Table of Contents

Data Visualization with R/RStudio
The Course Overview
Getting Started and Data Exploration with R/RStudio
Introduction to Visualization
Interactive Visualization
Geographic Plots
Advanced Visualization
Data Partitioning, Multiple Linear Regression, and Multicollinearity
Getting Introductory Concepts
Data Partitioning with R
Multiple Linear Regression with R
Multicollinearity Issues
Logistic Regression
Logistic Regression with Categorical Response Variables at two Levels
Logistic Regression Model and Interpretation
Misclassification Error and Confusion Matrix
ROC Curves
Prediction and Model Assessment
Multinomial Logistic Regression
Multinomial Logistic Regression with Categorical Response Variables at 3Levels
Multinomial Logistic Regression Model and Its Interpretation
Misclassification Error and Confusion Matrix
Prediction and Model Assessment
Ordinal Logistic Regression
Ordinal Logistic Regression with R
Ordinal Logistic Regression Model and Interpretation
The Misclassification Error and Confusion Matrix
Prediction and Model Assessment

What You Will Learn

  • Delve into data visualization and regression-based methods with R/RStudio. 
  • Conduct independent data analyses. 
  • Tackle multiple linear regression with R
  • Learn the essentials of ROC curves
  • Explore multinomial logistic regression with categorical response variables at three levels
  • Master prediction and model assessment.

Authors

Table of Contents

Data Visualization with R/RStudio
The Course Overview
Getting Started and Data Exploration with R/RStudio
Introduction to Visualization
Interactive Visualization
Geographic Plots
Advanced Visualization
Data Partitioning, Multiple Linear Regression, and Multicollinearity
Getting Introductory Concepts
Data Partitioning with R
Multiple Linear Regression with R
Multicollinearity Issues
Logistic Regression
Logistic Regression with Categorical Response Variables at two Levels
Logistic Regression Model and Interpretation
Misclassification Error and Confusion Matrix
ROC Curves
Prediction and Model Assessment
Multinomial Logistic Regression
Multinomial Logistic Regression with Categorical Response Variables at 3Levels
Multinomial Logistic Regression Model and Its Interpretation
Misclassification Error and Confusion Matrix
Prediction and Model Assessment
Ordinal Logistic Regression
Ordinal Logistic Regression with R
Ordinal Logistic Regression Model and Interpretation
The Misclassification Error and Confusion Matrix
Prediction and Model Assessment

Video Details

ISBN 139781787125100
Course Length3 hours and 43 minutes
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