From the very beginning, R is designed for statistical computing and data visualization and is widely used by academia and industry. For most data analysis purposes, correctness is more important than performance. In other words, getting a correct result in 1 minute should be better than getting an incorrect one in 20 seconds. A result that is three times faster is not automatically three times more valid than a slow but correct result. Therefore, performance should not be a concern before you are sure about the correctness of your code.
Let's assume that you are 100 percent sure that your code is correct but it runs a bit slowly. Now, is it necessary for you to optimize the code so that it can run faster. Well, it depends. Before making a decision, it is helpful to divide the time of problem solving into three parts: time of development, execution, and future maintenance.
Suppose we have been working on a problem for an hour. Since we didn't take performance...
