tarball.tar.gz

R_lang

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

## Find the total age
In this exercise, you need to calculate the total age of the people in the final data frame produced as a result of the instructions below. We use the `infert` dataset in this exercise. Follow the instructions step by step to reach the result:
1. Call the dataset by typing `infert`.
2. Convert the data in the `case` column into logical data types.
3. Create a new column named `age_status`. Set the value in the new column as `BA` for every row in which the age of the person is below average. Otherwise, set the value as `AA`.
4. Filter all rows with the `age_status` column equal to `BA`, the `case` column equal to `TRUE`, and the `parity` column not less than 4. 
5. Select the age column of the filtered data.

Finally, sum up all the values, and name the outcome `result`.





# Find the total age
In this exercise, you need to calculate the total age of the people in the final data frame produced as a result of the instructions below. We use the `infert` dataset in this exercise. Follow the instructions step by step to reach the result:
1. Call the dataset by typing `infert`.
2. Convert the data in the `case` column into logical data types.
3. Create a new column named `age_status`. Set the value in the new column as `BA` for every row in which the age of the person is below average. Otherwise, set the value as `AA`.
4. Filter all rows with the `age_status` column equal to `BA`, the `case` column equal to `TRUE`, and the `parity` column not less than 4. 
5. Select the age column of the filtered data.

Finally, sum up all the values, and name the outcome `result`.





Follow the instructions to solve the challenge.

Getting Started

File Management

Data Structures

Data Cleaning

Statistical Analysis

Data Transformation

Data Visualization

Conclusion

Evaluation

Netflix Shows

Challenge: Clean Data

Find the total age