# Ten Points for High-Quality Statistical Reporting and Data Presentation
## 1 Introduction  
Statistical reporting plays an important role in medical publications [1]. A high proportion of medical articles are essentially statistical in their presentation. For the reader, the main outward demonstration of a publication consists of statistical expressions that summarize the raw data used in the research. Regardless of the quality of the data and the variables chosen to express the results, the overt evidence of the research is produced as the lists of numbers, tables, plots, graphs, and other displays, i.e., the descriptive statistics. The communication of the descriptive statistics may also be combined with statistical inference procedures, such as test statistics and \(p\)-values [2]. The accurate communication of research results to the scientific community (i.e., other researchers) is essential providing reliable results [3; 4]. Failure to report analysis methods or inadequate data presentation could lead to inaccurate inferences, even if the statistical analyses were performed correctly. Several findings have demonstrated that a noteworthy percentage of articles, even those published in high-prestige journals, have flaws in their statistical reporting [3; 4; 5; 6; 7; 8]. Methodological and reporting problems have been reported over several decades, and despite continued efforts to improve the situation [9], the improvements have been far from satisfactory. One explanation is the inadequate assessment of statistical reporting during peer review [8]. Author instructions and editorials alone have been insufficient to change the quality of statistical reporting. Numerous reporting guidelines offer tools or checklists to evaluate the reporting of health research [10]. The EQUATOR Network listed 424 such guidelines in March 2020 [11]. What is often problematic in these checklists is their extent. They try to evaluate all possible aspects of analysis from study design, settings, participants, description of measurements and variables, sample sizes, data analysis methods, specific methods, descriptive data, outcome data, and ancillary analysis. Often it is impossible to evaluate all these points. When reviewing and editing health care and medical papers, I have noticed that a few points will reveal the quality of reporting of data analysis. There is no need to read the whole manuscript and check all the statistical details to ensure that the manuscript contains all the information that readers need to assess the study's methodology and validity of its findings. Editorial processes of medical manuscripts often fail to identify obvious indicators of good and poor data presentation and reporting of results. Editors, reviewers and readers need new tools to quickly identify studies with inadequate descriptions of statistical methods and poor quality of data presentation. I took on the challenge of compacting and refining the available quality criteria for statistical reporting and data presentation. I had three guiding starting points for assessing statistical reporting. The first key point was that if the data analysis methods are described with enough details, readers will be able to follow the flow of the analyses and to critically assess whether the data analyses provide reliable results. My second key point was the use of tables and figures in data presentation. Tables and figures are a fundamental means of scientific communications and they are included in most submitted and published medical and health care articles [12]. Most readers browse through tables and illustrations, but few read the whole article. Well-prepared tables and figures with proper titles, clear labeling, and optimally presented data will empower readers to scrutinize the data. I presume that the quality of tables and figures indicates the overall quality of data presentation. My third starting key point was that the new tool should be easy to use. I wanted to develop a short evaluation form with a low number of items.