List three specific types of EDA you could perform on a dataset regarding different types of medical marijuana usage
1. Descriptive statistics: This type of EDA involves calculating and summarizing key statistics such as the mean, median, mode, range, and standard deviation of various variables related to medical marijuana usage. This can help provide an overall picture of the dataset and identify any notable trends or patterns.
2. Correlation analysis: This type of EDA involves examining the relationships between different variables related to medical marijuana usage, such as dosage, frequency of use, and reported benefits or side effects. By calculating correlation coefficients and creating scatter plots, you can determine whether there are any significant associations between these variables.
3. Cluster analysis: This type of EDA involves grouping similar observations together based on patterns identified in the dataset. In the context of medical marijuana usage, you could use cluster analysis to identify distinct subgroups of patients based on their reported symptoms, treatment goals, or preferred methods of administration. This can help guide further research or personalized treatment approaches.