Distributional Characteristics of Short-Term 2022 20-Meter Sequential Matched WSPRDaemon Noise Observations

Understanding the characteristics and structure of one's data is critical for effective data analysis. Currently, WSPRDaemon data are being used in background noise level, HF propagation, Doppler shift, and correlational studies. Here we use Exploratory Data Analysis (EDA) on short-term (2-minute), sequential observations of WSPRDaemon observations to gain insights into the distributional characteristics of the data prior to more advanced modeling or analytical procedures. Our findings uncovered data outliers and puzzling distributional characteristics.  While consistent in their presence, these anomalies were unique from one receiving station to the next. These findings warrant further consideration and explanation before researchers invest time attempting more complex analytic procedures.  They also strongly suggest that a parallel data base of meta-data for the receiving stations would be extremely helpful for future studies.