answer these questions about (data analytics course, using Rstudio);

1. what are the similarities and differences between classification, clustering and linear regression?
2. Given a dataset, how to know which analytical technique (linear regression, classification or clustering) is appropriate for analyzing it
3. What are the signs or the conditions that allow you to decide if an analytical solution/model produced using classification, linear regression or clustering is a good fit or a good solution?
4. What are the techniques used to help decide for the optimal number of clusters to produce?
5. What are the techniques/statistical measures to use to select the best variables/attributes to retain formaking an optimal decision trees for classification and a good fit linear equation for linear regression?