Data Analysis 101 with R

Overview

Dive into the world of data analysis with our comprehensive learning path specifically designed for R. This course series is aimed at constructing a robust understanding of data analysis, allowing you to interpret, visualize, and communicate data effectively.

Syllabus

Course 1: Data Manipulation in R
Course 2: Statistical Analysis with R
Course 3: Data Cleaning and Preprocessing with R
Course 4: Advanced Data Transformation Techniques
Course 5: Hypothesis Testing in R
Course 6: Data Visualization with ggplot2

Courses

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2 hours
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Deep dive into data manipulation using dplyr in R. Understand and apply various dplyr functions for selecting, filtering, summarizing, and mutating data.
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3 hours
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Explore statistical analysis within R to perform descriptive and inferential statistics, understand probability distributions, and conduct hypothesis testing.
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2 hours
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Master the art of cleaning data using tidyr as part of the tidyverse ecosystem. Focus on techniques for dealing with missing values, reshaping data, and preparing datasets for analysis.
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3 hours
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Delve into advanced data transformation techniques with R to manage and manipulate complex datasets. Learn to merge datasets, create advanced visualizations, and optimize data processing.
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2 hours
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Gain proficiency in hypothesis testing within the R environment. Learn to formulate, execute, and interpret various statistical tests to make data-driven decisions.
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3 hours
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Discover the power of data visualization in R using the ggplot2 package. Learn how to craft clear, informative, and appealing visual representations of data.