### 11. Concluding Thoughts You should now be armed with an approach that you can apply to your data analyses. Although each data set is its own unique organism and each analysis has its own specific issues to contend with, tackling each step with the epicycle framework is useful for any analysis. As you work through developing your question, exploring your data, modeling your data, interpreting your results, and communicating your results, remember to always set expectations and then compare the result of your action to your expectations. If they don鈥檛 match, identify whether the problem is with the result of your action or your expectations and fix the problem so that they do match. If you can鈥檛 identify the problem, seek input from others, and then when you鈥檝e fixed the problem, move on to the next action. This epicycle framework will help to keep you on a course that will end at a useful answer to your question. In addition to the epicycle framework, there are also activities of data analysis that we discussed throughout the book. Although all of the analysis activities are important, if we had to identify the ones that are most important for ensuring that your data analysis provides a valid, meaningful, and interpretable answer to your question, we would include the following: 1. Be thoughtful about developing your question and use the question to guide you throughout all of the analysis steps. 1. Follow the ABCs: 1. Always be checking 1. Always be challenging 1. Always be communicating The best way for the epicycle framework and these activities to become second nature is to do a lot of data analysis, so we encourage you to take advantage of the data analysis opportunities that come your way. Although with practice, many of these principles will become second nature to you, we have found that revisiting these principles has helped to resolve a range of issues we鈥檝e faced in our own analyses. We hope, then, that the book continues to serve as a useful resource after you鈥檙e done reading it when you hit the stumbling blocks that occur in every analysis.