Fitting Regression Lines to Scatterplots: The Role of Perceptual Heuristics

2020 ◽  
Vol 64 (1) ◽  
pp. 1650-1654
Author(s):  
Douglas J. Gillan
Keyword(s):  
Least Squares ◽  
Regression Line ◽  
Formal Training ◽  
Least Squares Fit ◽  
Graph Reading ◽  
Best Fitting

Relations in data are described and analyzed by fitting a regression line to the data. The graphical equivalent is a line fit to a scatterplot, typically via the least squares fit. How do people visually fit a line or recognize the best fitting line for a scatterplot? The present research proposes that people use a set of perceptual heuristics – point capture, early point, balancing points and balancing distances. Experiments 1 and 2A found that participants with no training in regression drew a line and chose the best fitting line, respectively, using those heuristics, especially balancing points. The application of the heuristics was sensitive to the structure of the graphs and influenced the error in drawing the regression line. Participants in Experiment 2B who had received formal training in regression were less likely to apply the heuristics and more likely to choose a line based on the least squares fit. The discussion focuses on the value of cognitive/perceptual analyses of graph reading and proposes methods to help people overcome biases produced by the application of these perceptual heuristics.

Some Aspects of Discrete Relaxation Time Spectra as Obtained from Dynamic Moduli Data

1995 ◽  
Vol 60 (11) ◽  
pp. 1815-1829 ◽  
Author(s):  
Jaromír Jakeš
Keyword(s):  
Relaxation Time ◽  
Least Squares ◽  
Discrete Spectrum ◽  
Integral Transform ◽  
Time Spectrum ◽  
Relaxation Time Spectrum ◽  
Dynamic Moduli ◽  
Best Fitting ◽  
Discrete Spectra ◽  
Well Posed

The problem of finding a relaxation time spectrum best fitting dynamic moduli data in the least-squares sense is shown to be well-posed and to yield a discrete spectrum, provided the data cannot be fitted exactly, i.e., without any deviation of data and calculated values. Properties of the resulting spectrum are discussed. Examples of discrete spectra obtained from simulated literature data and experimental literature data on polymers are given. The problem of smoothing discrete spectra when continuous ones are expected is discussed. A detailed study of an integral transform inversion under the non-negativity constraint is given in Appendix.

scholarly journals Molecular Signatures of Reticulate Evolution within the Complex of European Pine Taxa

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 489
Author(s):  
Bartosz Łabiszak ◽  
Witold Wachowiak
Keyword(s):  
Gene Flow ◽  
Reticulate Evolution ◽  
Modeling Framework ◽  
Closely Related Species ◽  
Interspecific Gene Flow ◽  
Nucleotide Sequence Variation ◽  
History Of ◽  
Best Fitting ◽  
Species Integrity

Speciation mechanisms, including the role of interspecific gene flow and introgression in the emergence of new species, are the major focus of evolutionary studies. Inference of taxonomic relationship between closely related species may be challenged by past hybridization events, but at the same time, it may provide new knowledge about mechanisms responsible for the maintenance of species integrity despite interspecific gene flow. Here, using nucleotide sequence variation and utilizing a coalescent modeling framework, we tested the role of hybridization and introgression in the evolutionary history of closely related pine taxa from the Pinus mugo complex and P. sylvestris. We compared the patterns of polymorphism and divergence between taxa and found a great overlap of neutral variation within the P. mugo complex. Our phylogeny reconstruction indicated multiple instances of reticulation events in the past, suggesting an important role of interspecific gene flow in the species divergence. The best-fitting model revealed P. mugo and P. uncinata as sister species with basal P. uliginosa and asymmetric migration between all investigated species after their divergence. The magnitude of interspecies gene flow differed greatly, and it was consistently stronger from representatives of P. mugo complex to P. sylvestris than in the opposite direction. The results indicate the prominent role of reticulation evolution in those forest trees and provide a genetic framework to study species integrity maintained by selection and local adaptation.

scholarly journals The Role of Managerial Commitment and TPM Implementation Strategies in Productivity Benefits

2018 ◽  
Vol 8 (7) ◽  
pp. 1153 ◽  
Author(s):  
José Díaz-Reza ◽  
Jorge García-Alcaraz ◽  
Liliana Avelar-Sosa ◽  
José Mendoza-Fong ◽  
Juan Sáenz Diez-Muro ◽  
...  
Keyword(s):  
Least Squares ◽  
Structural Equation Model ◽  
Preventive Maintenance ◽  
Latent Variables ◽  
Structural Equation ◽  
Manufacturing Industry ◽  
Implementation Strategies ◽  
Equation Model ◽  
Total Productive Maintenance

The present research proposes a structural equation model to integrate four latent variables: managerial commitment, preventive maintenance, total productive maintenance, and productivity benefits. In addition, these variables are related through six research hypotheses that are validated using collected data from 368 surveys administered in the Mexican manufacturing industry. Consequently, the model is evaluated using partial least squares. The results show that managerial commitment is critical to achieve productivity benefits, while preventive maintenance is indispensable to total preventive maintenance. These results may encourage company managers to focus on managerial commitment and implement preventive maintenance programs to guarantee the success of total productive maintenance.

The role of internalizing and externalizing liability factors in accounting for gender differences in the prevalence of common psychopathological syndromes

2007 ◽  
Vol 38 (1) ◽  
pp. 51-61 ◽  
Author(s):  
Mark D. Kramer ◽  
Robert F. Krueger ◽  
Brian M. Hicks
Keyword(s):  
Gender Differences ◽  
Common Mental Disorders ◽  
Future Research ◽  
Latent Factor ◽  
Gender Invariance ◽  
Co Morbidity ◽  
Best Fitting ◽  
Invariance Model ◽  
Internalizing And Externalizing

BackgroundWe hypothesized that gender differences in average levels on the internalizing and externalizing factors that account for co-morbidity among common psychopathological syndromes in both men and women account for gender differences in the prevalence of specific syndromes.MethodThe latent structure of 11 syndromes was examined in a middle-aged (mean age=52.66 years, s.d.=5.82) sample of 2992 (37% men) members of the community-based Minnesota Twin Registry (MTR) assessed using 10 scales of the Psychiatric Diagnostic Screening Questionnaire (PDSQ) and an adult antisocial behavior scale. Confirmatory factorial invariance models were applied to a best-fitting, internalizing–externalizing model.ResultsA ‘strong gender invariance model’ fit best, indicating that gender differences in the means of individual syndromes were well accounted for by gender differences in mean levels of internalizing and externalizing. Women exhibited higher mean levels of internalizing (d=0.23) and lower mean levels of externalizing (d=−0.52) than men.ConclusionsThese findings suggest that risk factors for common mental disorders exhibiting gender differences may influence prevalence at the latent factor level. Future research may benefit from focusing on both the latent factor and individual syndrome levels in explaining gender differences in psychopathology.

scholarly journals Initial coin offerings and the cryptocurrency hype - the moderating role of exogenous and endogenous signals

2021 ◽  
Author(s):  
Ferdinand Thies ◽  
Sören Wallbach ◽  
Michael Wessel ◽  
Markus Besler ◽  
Alexander Benlian
Keyword(s):  
Least Squares ◽  
Ordinary Least Squares ◽  
High Quality ◽  
Academic Interest ◽  
Entrepreneurial Ventures ◽  
Asset Class ◽  
The Impact ◽  
Moderating Role ◽  
Initial Coin Offerings

AbstractInitial coin offerings (ICOs) have recently emerged as a new financing instrument for entrepreneurial ventures, spurring economic and academic interest. Nevertheless, the impact of exogenous and endogenous signals on the performance of ICOs as well as the effects of the cryptocurrency hype and subsequent downfall of Bitcoin between 2016 and 2019 remain underexplored. We applied ordinary least squares (OLS) regressions based on a dataset containing 1597 ICOs that covers almost 2.5 years. The results show that exogenous and endogenous signals have a significant effect on the funds raised in ICOs. We also find that the Bitcoin price heavily drives the performance of ICOs. However, this hype effect is moderated, as high-quality ICOs are not pegged to these price developments. Revealing the interplay between hypes and signals in the ICO’s asset class should broaden the discussion of this emerging digital phenomenon.

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