Data Analysis and Reporting: Presenting Your Best Face

Scientific studies typically generate a large amount of data that needs to be analyzed, interpreted, and communicated. The values of scientific measurements and observations vary due to the natural variability of the world. A good understanding of statistics is critical to the proper design and interpretation of most scientific studies. The proper use of statistics leads to results that are more accurate and precise. We therefore recommend becoming familiar with the most important statistical concepts relevant to your field of study. You should be aware that your results are always prone to experimental errors for many different reasons, including blunders, random errors, and systematic errors. It is important to carefully consider all the possible sources of errors in your studies and eliminate or reduce them. Representing your scientific findings in a clear and concise manner that is visually appealing to readers will also increase the impact of your research. Wherever possible, we strongly recommend that you try to interpret your results using fundamental scientific principles (such as physics, chemistry, and biology), rather than simply developing correlations (black-box approach). The black-box approach produces new knowledge about the world, but the fundamental approach creates new understanding. This chapter introduces various important statistical concepts that are commonly used in designing and interpreting experiments. It also highlights the importance of choosing the correct format for presenting your results in a clear, accurate, and compelling way.