Once data collection has been completed and imported into the R environment, it is finally time to start the analysis process. This is what a novice might think; conversely, we must first proceed to the preparation of data (data wrangling). This is a laborious process that can take a long time, in some cases about 80 percent of the entire data analysis process. However, it is a fundamental prerequisite for the rest of the data analysis workflow, so it is essential to acquire the best practices in such techniques.
Before submitting our data to any regression algorithm, we must be able to evaluate the quality and accuracy of our observations. If we cannot access the data stored in R correctly, or if we do not know how to switch from raw data to something that can be analyzed, we cannot go ahead.
