The statistical significance of the N-S asymmetry of solar activity revisited

TL;DR

This study reviews the challenges in statistically assessing the North-South asymmetry of solar activity, emphasizing the influence of data types, binning, units, and test selection on the significance results.

Contribution

It highlights the complexities and limitations in current statistical methods for evaluating solar activity asymmetry, urging cautious interpretation of previous findings.

Findings

Statistical significance depends on data type and units.

Data binning and grouping significantly affect results.

Absolute significance assessment is inherently difficult.

Abstract

The main aim of this study is to point out the difficulties found when trying to assess the statistical significance of the North-South asymmetry (hereafter SSNSA) of the most usually considered time series of solar activity. First of all, we distinguish between solar activity time series composed by integer or non-integer and dimensionless data, or composed by non-integer and dimensional data. For each of these cases, we discuss the most suitable statistical tests which can be applied and highlight the difficulties to obtain valid information about the statistical significance of solar activity time series. Our results suggest that, apart from the need to apply the suitable statistical tests, other effects such as the data binning, the considered units and the need, in some tests, to consider groups of data, affect substantially the determination of the statistical significance of the asymmetry. Our main conclusion is that the assessment of the statistical significance of the N-S asymmetry of solar activity is a difficult matter and that an absolute answer cannot be given, since many different effects influence the results given by the statistical tests. In summary, the quantitative results about the statistical significance of the N-S asymmetry of solar activity provided by different authors, as well as the studies about its behaviour, must be considered with care because they depend from the chosen values of different parameters or from the considered units.