If your software tool doesn’t have any alternatives, then you’re either stuck with the first choice or you’ll have to switch to another tool.įor example, if you have a statistical model and you want to find the optimal parameter values, you’ll be using a likelihood function and an optimization technique. Often, you’ll find that the method you chose doesn’t quite work as well as you’d hoped, and what you learned in the process leads you to believe that a different method might work better. In addition to being able to perform the main statistical analysis, it’s often helpful if a statistical tool can perform some related methods. It might be helpful to read the documentation or some examples that are like the analysis you want to do. Make sure that the programming language and the package can do exactly what you intend. If you decide to go with a programming language, remember that not all packages or libraries are created equal.

Otherwise, you’ll choose a different statistical method. If Excel doesn’t, then maybe the mid-level tools do, and if they don’t, you’re probably going to have to write a program.

If Excel has it, then most likely every other tool does, too. Code that’s been used by many people is usually relatively error-free compared to code that you wrote in a day and used only once or twice.ĭepending on your ability to program and your familiarity with various statistical tools, there may be a readily-available implementation in one of your favorite tools that you could use quickly. You can code the methods yourself, but if you’re using a common method, there are many tools that already have an implementation, and it’s probably better to use one of those. Does the tool have an implementation of the methods? In choosing software tools, there are various things to consider and some general rules that I follow. You can compare methods or models with the software options available to implement them, and arrive at a good option or two. A broad range of tools are available to implement statistical methods.

Mlb statistical tools for data analysis