Calculating and understanding the value of any type of match evidence when there are potential testing errors

It is well known that Bayes’ theorem (with likelihood ratios) can be used to calculate the impact of evidence, such as a ‘match’ of some feature of a person. Typically the feature of interest is the DNA profile, but the method applies in principle to any feature of a person or object, including not just DNA, fingerprints, or footprints, but also more basic features such as skin colour, height, hair colour or even name. Notwithstanding concerns about the extensiveness of databases of such features, a serious challenge to the use of Bayes in such legal contexts is that its standard formulaic representations are not readily understandable to non-statisticians. Attempts to get round this problem usually involve representations based around some variation of an event tree. While this approach works well in explaining the most trivial instance of Bayes’ theorem (involving a single hypothesis and a single piece of evidence) it does not scale up to realistic situations. In particular, even with a single piece of match evidence, if we wish to incorporate the possibility that there are potential errors (both false positives and false negatives) introduced at any stage in the investigative process, matters become very complex. As a result we have observed expert witnesses (in different areas of speciality) routinely ignore the possibility of errors when presenting their evidence. To counter this, we produce what we believe is the first full probabilistic solution of the simple case of generic match evidence incorporating both classes of testing errors. Unfortunately, the resultant event tree solution is too complex for intuitive comprehension. And, crucially, the event tree also fails to represent the causal information that underpins the argument. In contrast, we also present a simple-to-construct graphical Bayesian Network (BN) solution that automatically performs the calculations and may also be intuitively simpler to understand. Although there have been multiple previous applications of BNs for analysing forensic evidence—including very detailed models for the DNA matching problem, these models have not widely penetrated the expert witness community. Nor have they addressed the basic generic match problem incorporating the two types of testing error. Hence we believe our basic BN solution provides an important mechanism for convincing experts—and eventually the legal community—that it is possible to rigorously analyse and communicate the full impact of match evidence on a case, in the presence of possible error

Evolution of statistical analysis in empirical software engineering research: Current state and steps forward

Software engineering research is evolving and papers are increasingly based on empirical data from a multitude of sources, using statistical tests to determine if and to what degree empirical evidence supports their hypotheses. To investigate the practices and trends of statistical analysis in empirical software engineering (ESE), this paper presents a review of a large pool of papers from top-ranked software engineering journals. First, we manually reviewed 161 papers and in the second phase of our method, we conducted a more extensive semi-automatic classification of papers spanning the years 2001--2015 and 5,196 papers. Results from both review steps was used to: i) identify and analyze the predominant practices in ESE (e.g., using t-test or ANOVA), as well as relevant trends in usage of specific statistical methods (e.g., nonparametric tests and effect size measures) and, ii) develop a conceptual model for a statistical analysis workflow with suggestions on how to apply different statistical methods as well as guidelines to avoid pitfalls. Lastly, we confirm existing claims that current ESE practices lack a standard to report practical significance of results. We illustrate how practical significance can be discussed in terms of both the statistical analysis and in the practitioner's context.Comment: journal submission, 34 pages, 8 figure

The Rate of Type Ia Supernovae at High Redshift

We derive the rates of Type Ia supernovae (SNIa) over a wide range of redshifts using a complete sample from the IfA Deep Survey. This sample of more than 100 SNIa is the largest set ever collected from a single survey, and therefore uniquely powerful for a detailed supernova rate (SNR) calculation. Measurements of the SNR as a function of cosmological time offer a glimpse into the relationship between the star formation rate (SFR) and Type Ia SNR, and may provide evidence for the progenitor pathway. We observe a progressively increasing Type Ia SNR between redshifts z~0.3-0.8. The Type Ia SNR measurements are consistent with a short time delay (t~1 Gyr) with respect to the SFR, indicating a fairly prompt evolution of SNIa progenitor systems. We derive a best-fit value of SFR/SNR 580 h_70^(-2) M_solar/SNIa for the conversion factor between star formation and SNIa rates, as determined for a delay time of t~1 Gyr between the SFR and the Type Ia SNR. More complete measurements of the Type Ia SNR at z>1 are necessary to conclusively determine the SFR--SNR relationship and constrain SNIa evolutionary pathways.Comment: 37 pages, 9 figures, accepted for publication in Astrophysical Journal. Figures 7-9 correcte

Racial and Ethnic Discrimination in Local Consumer Markets: Exploiting the Army’s Procedures for Matching Personnel to Duty Locations

We use the exogenous assignment of Army personnel to duty locations to analyze the relationship between the characteristics of local markets and the propensity for consumers to be subjected to racial discrimination in their everyday commercial transactions. Overall, one in ten soldiers report that they or their families have experienced racial discrimination in finding non-government housing or in patronizing businesses in their local communities. Discrimination is related to a community’s demographic profile with white and Asian soldiers feeling more unwelcome in local businesses as the local population becomes heavily weighted towards other groups. Moreover, there is evidence that increased economic vulnerability in the community results in more housing discrimination amongst minorities. While the evidence that increased competition reduces consumer market discrimination is mixed, it is clear that discrimination is related to the nature of a soldier’s interaction with the local community.Consumer Markets, discrimination, U.S. Military, Economics of Minorities

The role of motion analysis in elite soccer

The optimal physical preparation of elite soccer (association football) players has become an indispensable part of the professional game especially due to the increased physical demands of match-play. The monitoring of players’ work-rate profiles during competition is now feasible through computer-aided motion analysis. Traditional methods of motion analysis were extremely labour intensive and were largely restricted to university- based research projects. Recent technological developments have meant that sophisticated systems, capable of quickly recording and processing the data of all players’ physical contributions throughout an entire match, are now being used in elite club environments. In recognition of the important role motion analysis now plays as a tool for measuring the physical performance of soccer players, this review critically appraises various motion analysis methods currently employed in elite soccer and explores research conducted using these methods. This review therefore aims to increase the awareness of both practitioners and researchers of the various motion analysis systems available, identify practical implications of the established body of knowledge, while highlighting areas that require further exploration

The impact of asking intention or self-prediction questions on subsequent behavior: a meta-analysis

The current meta-analysis estimated the magnitude of the impact of asking intention and self-prediction questions on rates of subsequent behavior, and examined mediators and moderators of this question–behavior effect (QBE). Random-effects meta-analysis on 116 published tests of the effect indicated that intention/prediction questions have a small positive effect on behavior (d+ = 0.24). Little support was observed for attitude accessibility, cognitive dissonance, behavioral simulation, or processing fluency explanations of the QBE. Multivariate analyses indicated significant effects of social desirability of behavior/behavior domain (larger effects for more desirable and less risky behaviors), difficulty of behavior (larger effects for easy-to-perform behaviors), and sample type (larger effects among student samples). Although this review controls for co-occurrence of moderators in multivariate analyses, future primary research should systematically vary moderators in fully factorial designs. Further primary research is also needed to unravel the mechanisms underlying different variants of the QBE