R Programming for Statistics and Data Science - What Does this Course Cover?

This video tutorial introduces a course on statistics and data science using R. The instructor, with a background in cognitive science, emphasizes the importance of R for data analysis and visualization. The course covers R and RStudio setup, basic and advanced R programming, data manipulation, tidy data principles, data visualization with ggplot2, and statistical analysis. Each section includes hands-on projects and resources to enhance learning. The course aims to equip learners with the skills to make data-driven decisions and interpret data patterns effectively.

What is the primary reason the instructor prefers using R for data science?

• It is the most popular programming language.

• It is the fastest way to carry out complex statistical analysis.

• It has the best user interface.

• It is the easiest language to learn.

Which of the following is NOT a basic data type in R?

• Matrix

• Array

• Vector

• Graph

What is the purpose of using 'spread' and 'gather' functions in data manipulation?

• To create predictive models

• To perform statistical tests

• To tidy data sets

• To visualize data

Which package is used for creating visualizations that tell a story in R?

• dplyr

• tidyr

• ggplot2

• stringr

What is the role of regression analysis in data science?

• To clean data

• To visualize data

• To perform data manipulation

• To build predictive models