scholarly journals How cann soccer improve statistical learning?

2014 ◽  
Vol 2 (7) ◽  
pp. 83-87
Author(s):  
Enivaldo C. Rocha ◽  
Dalson Britto Figueiredo Filho ◽  
Ranulfo Paranhos ◽  
José Alexandre Silva Jr. ◽  
Denisson Silva
Keyword(s):  
Linear Regression ◽  
Statistical Learning ◽  
Undergraduate Students ◽  
Ordinary Least Squares ◽  
Regression Coefficients ◽  
Least Squares Regression ◽  
Practical Application ◽  
Implementation Cost ◽  
Home Team ◽  
Classical Hypothesis

This paper presents an active classroom exercise focusing on the interpretation of ordinary least squares regression coefficients. Methodologically, undergraduate students analyze Brazilian soccer data, formulate and test classical hypothesis regarding home team advantage. Technically, our framework is simply adapted for others sports and has no implementation cost. In addition, the exercise is easily conducted by the instructor and highly enjoyable for the students. The intuitive approach also facilitates the understanding of linear regression practical application.

scholarly journals Tolerance Intervals in a Heteroscedastic Linear Regression Context with Applications to Aerospace Equipment Surveillance

2009 ◽  
Vol 2009 ◽  
pp. 1-8 ◽  
Author(s):  
Janet Myhre ◽  
Daniel R. Jeske ◽  
Michael Rennie ◽  
Yingtao Bi
Keyword(s):  
Linear Regression ◽  
Least Squares ◽  
Performance Metrics ◽  
Weighted Least Squares ◽  
Ordinary Least Squares ◽  
Automated System ◽  
Least Squares Regression ◽  
Data Set ◽  
Tolerance Intervals ◽  
Power Of The Test

A heteroscedastic linear regression model is developed from plausible assumptions that describe the time evolution of performance metrics for equipment. The inherited motivation for the related weighted least squares analysis of the model is an essential and attractive selling point to engineers with interest in equipment surveillance methodologies. A simple test for the significance of the heteroscedasticity suggested by a data set is derived and a simulation study is used to evaluate the power of the test and compare it with several other applicable tests that were designed under different contexts. Tolerance intervals within the context of the model are derived, thus generalizing well-known tolerance intervals for ordinary least squares regression. Use of the model and its associated analyses is illustrated with an aerospace application where hundreds of electronic components are continuously monitored by an automated system that flags components that are suspected of unusual degradation patterns.

scholarly journals La distancia más corta. El método de los mínimos cuadrados.

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Manuel Molina
Keyword(s):  
Linear Regression ◽  
Least Squares ◽  
Regression Line ◽  
Regression Method ◽  
Regression Coefficients ◽  
Least Squares Regression ◽  
Linear Regression Line ◽  
Shortest Distance ◽  
The Way

El método de los mínimos cuadrados se utiliza para calcular la recta de regresión lineal que minimiza los residuos, esto es, las diferencias entre los valores reales y los estimados por la recta. Se revisa su fundamento y la forma de calcular los coeficientes de regresión con este método. ABSTRACT The shortest distance. Least squares regression. Least squares regression method is used to calculate the linear regression line that minimizes residuals, that is, the differences among real values and those estimated by the line. Its basis and the way of calculating the regression coefficients with this method are reviewed.

scholarly journals Model Correlates Many Factors to Undergraduates’ Perceived Importance of Library and Research Activities, but Low Explanation Power Suggests More Research Needed

2014 ◽  
Vol 9 (2) ◽  
pp. 16
Author(s):  
Diana K. Wakimoto
Keyword(s):  
Factor Analysis ◽  
Student Perceptions ◽  
Undergraduate Students ◽  
Academic Engagement ◽  
The United States ◽  
Ordinary Least Squares ◽  
Least Squares Regression ◽  
Academic Variables ◽  
Research Activities ◽  
World Class

A Review of: Soria, K. M. (2013). Factors predicting the importance of libraries and research activities for undergraduates. Journal of Academic Librarianship, 39(6), 464-470. Objective – The purpose is to analyze characteristics and perceptions of undergraduate students to determine factors that predict the importance of library and research activities for the students. Design – Student Experience in the Research University (SERU) survey questionnaire. Setting – Nine large, public, research universities in the United States of America. Subjects – 16,778 undergraduates who completed the form of the survey that included the academic engagement module questions. Methods – The researcher used descriptive and inferential statistics to analyze student responses. Descriptive statistics included coding demographic, collegiate, and academic variables, as well as student perceptions of the importance of library and research activities. These were used in the inferential statistical analyses. Ordinary least squares regression and factor analysis were used to determine variables and factors that correlated to students’ perceptions of the importance of libraries and research activities. Main Results – The response rate for the overall SERU survey was 38.1%. The results showed that the majority of students considered having access to a “world-class library collection,” learning research methods, and attending a university with “world-class researchers” to be important. The regression model explained 22.7% of variance in the importance students placed on libraries and research activities; factors important to the model covered demographics, collegiate, and academic variables. Four variables created in factor analysis (academic engagement, library skills, satisfaction with libraries and research, and faculty interactions) were significantly correlated with the importance students placed on libraries and research activities. The most important predictors in the model were: student satisfaction, interest in a research or science profession, interest in medical or health-related profession, academic engagement, and academic level. Conclusion – Based on the results of this study, librarians should be able to tailor their marketing to specific student groups to increase the perception of importance of libraries by undergraduates. For example, more success may be had marketing to students who are Hispanic, Asian, international, interested in law, psychology or research professions as the study found these students place more importance on libraries and research activities than other groups. These students may be targeted for being peer advocates for the libraries. Further research is suggested to more fully understand factors that influence the value undergraduate students place on libraries and find ways to increase the value of libraries and research activities for those demographic groups who currently rate the importance lower.

scholarly journals Online, Interactive Tutorials Provide Effective Instruction in Science Process Skills

2017 ◽  
Author(s):  
Maxwell Kramer ◽  
Dalay Olson ◽  
J.D. Walker
Keyword(s):  
Undergraduate Students ◽  
Ordinary Least Squares ◽  
Teaching Science ◽  
Skill Assessment ◽  
Process Skills ◽  
Least Squares Regression ◽  
Multimedia Design ◽  
Science Process Skills ◽  
Online Tutorials ◽  
English Speaking

AbstractExplicit emphasis on teaching science process skills leads to both gains in the skills themselves and, strikingly, deeper understanding of content. Here, we created and tested a series of online, interactive tutorials with the goal of helping undergraduate students develop science process skills. We designed the tutorials in accordance with evidence-based multimedia design principles and student feedback from usability testing. We then tested the efficacy of the tutorials in an introductory undergraduate biology class. Based on a multivariate ordinary least squares regression model, students that received the tutorials are predicted to score 0.824 points higher on a 15 point science process skill assessment than their peers that received traditional textbook instruction on the same topic. This moderate but significant impact indicates that well designed online tutorials can be more effective than traditional ways of teaching science process skills to undergraduate students. We also found trends that suggest the tutorials are especially effective for non-native English speaking students. However, due to a limited sample size, we were unable to confirm that these trends occurred due to more than just variation in the sampled student group.

scholarly journals Combining Regression and Factor Analysis for Use in Agricultural Economics Research

1976 ◽  
Vol 8 (2) ◽  
pp. 145-149
Author(s):  
John T. Scott
Keyword(s):  
Time Series Data ◽  
Correlation Coefficients ◽  
Ordinary Least Squares ◽  
Statistical Technique ◽  
Regression Coefficients ◽  
Series Data ◽  
Least Squares Regression ◽  
Chi Square ◽  
Explanatory Variables ◽  
Chi Square Test

While ordinary least squares regression has become a standard statistical technique, there are problems frequently overlooked or ignored by researchers in applying this statistical method. Two basic assumptions of the OLS regression model—(1) that the explanatory variables are independent of each other and (2) that the explanatory variables are known, fixed numbers—do not hold for most economic data, particularly time series data. This has been a consternation for econometricians, if not for the general researcher, for many years.In the case of nonindependence of explanatory variables (multicollinearity), signs of the regression coefficients often are inconsistent with economic theory and with correlation coefficients calculated from the data. Also, variances of the estimated regression coefficients are inconsistent. In practice for prediction equations, multicollinearity can usually be sufficiently reduced by either dropping one or more multicollinear variables or by indexing them and using the index as a regressor, thus circumventing the assumption regarding independence of the explanatory variables. A chi-square test for multicollinearity is available, and can be used as a guide to alert a researcher to the problem.

scholarly journals Least Square Regression for Prediction Problems in Machine Learning using R

2018 ◽  
Vol 7 (3.12) ◽  
pp. 960
Author(s):  
Anila. M ◽  
G Pradeepini
Keyword(s):  
Machine Learning ◽  
Linear Regression ◽  
Ordinary Least Squares ◽  
Least Square ◽  
Least Squares Regression ◽  
Ols Regression ◽  
Least Square Regression ◽  
Psychology And Economics ◽  
Prediction Technique ◽  
Prediction Problems

The most commonly used prediction technique is Ordinary Least Squares Regression (OLS Regression). It has been applied in many fields like statistics, finance, medicine, psychology and economics. Many people, specially Data Scientists using this technique know that it has not gone with enough training to apply it and should be checked why & when it can or can’t be applied.It’s not easy task to find or explain about why least square regression [1] is faced much criticism when trained and tried to apply it. In this paper, we mention firstly about fundamentals of linear regression and OLS regression along with that popularity of LS method, we present our analysis of difficulties & pitfalls that arise while OLS method is applied, finally some techniques for overcoming these problems.  

scholarly journals Design and Assessment of Online, Interactive Tutorials That Teach Science Process Skills

2018 ◽  
Vol 17 (2) ◽  
pp. ar19 ◽  
Author(s):  
Maxwell Kramer ◽  
Dalay Olson ◽  
J. D. Walker
Keyword(s):  
Undergraduate Students ◽  
Ordinary Least Squares ◽  
Teaching Science ◽  
Skill Assessment ◽  
Process Skills ◽  
Least Squares Regression ◽  
Multimedia Design ◽  
Science Process Skills ◽  
Online Tutorials ◽  
English Speaking

Explicit emphasis on teaching science process skills leads to both gains in the skills themselves and, strikingly, deeper understanding of content. Here, we created and tested a series of online, interactive tutorials with the goal of helping undergraduate students develop science process skills. We designed the tutorials in accordance with evidence-based multimedia design principles and student feedback from usability testing. We then tested the efficacy of the tutorials in an introductory undergraduate biology class. On the basis of a multivariate ordinary least-squares regression model, students who received the tutorials are predicted to score 0.82 points higher on a 15-point science process skill assessment than their peers who received traditional textbook instruction on the same topic. This moderate but significant impact indicates that well-designed online tutorials can be more effective than traditional ways of teaching science process skills to undergraduate students. We also found trends that suggest the tutorials are especially effective for nonnative English-speaking students. However, due to a limited sample size, we were unable to confirm that these trends occurred due to more than just variation in the student group sampled.

Errors in Variables: A Problem in Regression and its Solution

1986 ◽  
Vol 18 (5) ◽  
pp. 687-693 ◽  
Author(s):  
K J Thomson ◽  
K G Willis
Keyword(s):  
Linear Regression ◽  
Least Squares ◽  
Regression Models ◽  
Ordinary Least Squares ◽  
Regression Coefficients ◽  
Car Ownership ◽  
Errors In Variables ◽  
Socioeconomic Analysis ◽  
Multiple Regression Models ◽  
Least Squares Techniques

It is not uncommon in socioeconomic analysis to measure variables with error, as in a 10% census. The estimation of linear regression coefficients using such ‘errors-in-variables’ models requires modification of the usual ordinary least squares techniques. The underlying theory both for simple and for multiple regression models is explained, and followed up with a numerical example based on a structure plan model of car ownership.

scholarly journals Voice or silence: antecedents of whistleblowing intentions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Tatiana Iwai ◽  
Luciana Yeung ◽  
Rinaldo Artes
Keyword(s):  
Undergraduate Students ◽  
Ethical Behavior ◽  
Interactive Effect ◽  
Underlying Mechanism ◽  
Ordinary Least Squares ◽  
Least Squares Regression ◽  
Content Type ◽  
Positive Effects ◽  
Fear Of Retaliation ◽  
Reporting Intentions

Purpose This study aims to examine the effects of peer ethical behavior and individual differences in valuation of fairness vs loyalty on whistleblowing intentions in academic settings. This study also tests the underlying mechanism responsible for the effects of peer behavior on reporting intentions, namely, fear of reprisal. Design/methodology/approach A survey was conducted with 947 undergraduate students. The model was tested using ordinary least squares regression models followed by bootstrapped mediation analyses. Findings Results showed that the effects of peer ethical behavior on whistleblowing intentions are mediated by fear of retaliation. Moreover, the findings indicated that, for low-severity transgressions, there is an interactive effect between fear of retaliation and endorsement of fairness over loyalty on whistleblowing intentions. Research limitations/implications When the misconduct is seen as minor, a potential whistleblower may understand that the expected costs outweigh the possible benefits of blowing the whistle. In such situations, higher fear of retaliation would undermine the effects of individual’s endorsement of fairness over loyalty on reporting intentions. Practical implications As the social environment significantly affects someone’s whistleblowing intentions, there should be visible efforts to improve and to foster an ethical infrastructure in organizations. Social implications As fear of retaliation by peers is one of the most important determinants affecting the decision to report misconduct in general, there must be serious efforts from leaders to mitigate any threat of retaliation to those who come forward. Originality/value This work contributes to the discussion about individual and situational antecedents of whistleblowing. More importantly, it sheds light on one potential boundary condition for the influence of the fairness–loyalty tradeoff on whistleblowing decisions: severity of the transgression. The findings provide initial evidence that, for low-severity transgressions, fear of retaliation weakens the positive effects of one’s moral compass in terms of preference for fairness over loyalty on whistleblowing intentions.

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