Regression Analysis and Best Fit Lines (XE0124)

2007 ◽  
pp. 409-409
Keyword(s):  
Regression Analysis ◽  
Best Fit

scholarly journals Regression Analysis of Bond Parameters between Corroded Rebar and Concrete Based on Reported Test Data

2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
H. J. Zhou ◽  
Y. F. Zhou ◽  
Y. N. Xu ◽  
Z. Y. Lin ◽  
F. Xing ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Bond Strength ◽  
Crack Width ◽  
Experimental Tests ◽  
Test Results ◽  
Bond Slip ◽  
Regression Effect ◽  
Pull Out ◽  
Maximum Crack ◽  
Best Fit

Reinforcement corrosion is a major cause of degradation in reinforced concrete structures. The fragile rust layer and cracking and spalling of the cover caused by splitting stress due to rust expansion can alter bond behaviors significantly. Despite extensive experimental tests, no stochastic model has yet incorporated randomness into the bond parameters model. This paper gathered published experimental data on the bond-slip parameters of pull-out specimens and beam-end specimens. Regression analysis was carried out to identify the best fit of bond strength and the corresponding slip value in the context of different corrosion levels from the recollected test results. An F-test confirmed the regression effect to be significant. Residual data were also analyzed and found to be well described by a normal distribution. Crack width data of the tested specimens were also collected. A regression analysis of the bond strength and maximum crack width was carried out given the comparative simplicity of measuring crack width versus rebar area loss. Results indicate that maximum crack width can also be used to predict bond strength degradation with similar variation magnitude.

scholarly journals Technical Note: Nominal Stiffness Evaluation and Regression Analysis of GT-2 Rubber-Fiberglass Timing Belts

2018 ◽  
Author(s):  
Bozun Wang ◽  
Yefei Si ◽  
Charul Chadha ◽  
James T. Allison ◽  
Albert E. Patterson
Keyword(s):  
Regression Analysis ◽  
Regression Models ◽  
Linear Models ◽  
System Modeling ◽  
Technical Note ◽  
Effective Stiffness ◽  
Modeling Error ◽  
Mechatronic Systems ◽  
Stiffness Evaluation ◽  
Best Fit

GT-style rubber-fiberglass (RF) timing belts are designed to effectively transfer rotational motion from pulleys to linear motion in small machines and mechatronic systems. One of the characteristics of belts under this type of loading condition is that the length between load and pulleys changes during operation, thereby changing their effective stiffness. It has been shown that the effective stiffness of such a belt is a function of a "nominal stiffness" and the real-time belt section lengths. However, this nominal stiffness is not necessarily constant; it is common to assume linear proportional stiffness, but this often results in system modeling error. This technical note describes a brief study where the nominal stiffness of two lengths (400 mm and 760 mm ) of GT-2 RF timing belts was tested up to breaking point; regression analysis was performed on the results to best model the observed stiffness. The study was replicated three times, providing a total of six stiffness curves. It was found that cubic regression models (R^2 > 0.999) were the best fit, but that quadratic and linear models still provided acceptable representations of the whole dataset with R^2 values above 0.940.

Examining deceptive behaviours by attackers in rugby union: The influence of decoy runners on defensive performance

2018 ◽  
Vol 13 (6) ◽  
pp. 1100-1107 ◽  
Author(s):  
Sebastian Sherwood ◽  
Rich SW Masters ◽  
Tiaki Brett Smith
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Binary Logistic Regression ◽  
Dependent Measure ◽  
Rugby Union ◽  
Binary Logistic Regression Analysis ◽  
Observational Analysis ◽  
Psychological Mechanisms ◽  
Best Fit

Background Deceptive tactics are commonly used in sport; however, the psychological mechanisms underpinning the effectiveness of these tactics are unclear. Increasingly, in rugby union, decoy runners are used to cause deception. Multiple players in an attacking team run option lines off the ball carrier, making it possible that any of the players could receive the ball. Runners who do not receive the ball are decoys. The aim of the tactic is for the decoys to attract attention from defending players, which creates confusion about which player will receive the ball. Aim To identify behaviours of option line runners that can be used to improve the effectiveness of this deceptive tactic. Method Observational analysis of completed scrums from the 2015 Super Rugby season (n = 260) during which decoy runners were used by the attacking side. Decoy characteristics, including Hands Up, Line Change and Hands Up with Line Change were noted following each scrum. Gainline success was used as a dependent measure of the efficacy of the decoy characteristics. Characteristics were included in a binary logistic regression analysis to develop a best-fit model for gainline success. Results Hands Up, Line Change and Hands Up with Line Change significantly improved the likelihood of gainline success seven, eight and six times, respectively. Discussion We discuss possible mechanisms that underpin the effectiveness of decoy runners and make recommendations for coaches.

Comparison of Six Cursor Control Devices Based on Fitts' Law Models

1986 ◽  
Vol 30 (4) ◽  
pp. 327-331 ◽  
Author(s):  
Brian W. Epps
Keyword(s):  
Regression Analysis ◽  
Movement Time ◽  
Performance Data ◽  
Target Acquisition ◽  
Acquisition Performance ◽  
Cursor Control ◽  
Fitts Law ◽  
Acquisition Task ◽  
Control Devices ◽  
Best Fit

Six cursor control devices were compared on a target acquisition task which required subjects to move a cursor into square targets of varying sizes and at various screen distances. The target acquisition performance data were fitted to movement time models proposed by Fitts, Jagacinski, and Kvalseth. Regression analysis results indicated good predictions of target acquisition performance for the six cursor devices. The best fit was obtained with the trackball across the three models.

scholarly journals Time Trend and prediction of Grade 2 Disability among new cases of leprosy in Nepal: A Statistical Modelling

2014 ◽  
Vol 4 (3) ◽  
pp. 378-383 ◽  
Author(s):  
Brijesh Sathian ◽  
Ajay Kumar ◽  
Jayadevan Sreedharan ◽  
Indrajit Banerjee ◽  
Bedanta Roy ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Time Trends ◽  
Time Trend ◽  
Constant Term ◽  
Statistical Modelling ◽  
Inverse Model ◽  
Descriptive Statistics ◽  
Health Ministry ◽  
Data Points ◽  
Best Fit

Background  It is estimated that globally there are around 2 million people with grade 2 disabilities attributed to leprosy. Objective of the study was to find out the time trends of Grade 2 Disability among the new cases of Leprosy in Nepal. Materials and Methods A retrospective study was carried out on the data collected from the Health ministry records of Nepal, between 2009 and 2013. The annual reported numbers of Grade 2 Disability among new cases of leprosy plotted in y-axis against the corresponding year in the x-axis. Curve fitting, also known as regression analysis, was used to find the "best fit" line or curve for a series of data points. Linear, Logarithmic, Inverse, Quadratic, and Cubic were chosen to fit to the obtained curve. Descriptive statistics and statistical modelling were used for the analysis and forecasting of data. Results Including the constant term from the equation, the inverse model was the best fit, for the forecasting of the Grade 2 Disability among new cases of leprosy in Nepal [R2=0.739, p=0.062]. Using inverse model, it is estimated that 78 with CI [0, 170] of Grade 2 Disability among new cases of leprosy can be expected in Nepal by the year 2020. Conclusion Our study proves Inverse model is the best fit for epidemiological modelling of Grade 2 Disability among the new cases of Leprosy in Nepal. Prevention of disabilities should begin with diagnosing leprosy.DOI: http://dx.doi.org/10.3126/nje.v4i3.10668 Nepal Journal of Epidemiology 2014; 4(3): 378-383

scholarly journals A Study on Statistical Modelling on Recovery Informatics of Covid19

2020 ◽  
Author(s):  
Jaydip Datta
Keyword(s):  
Regression Analysis ◽  
Rate Constant ◽  
Standard Error ◽  
Model Equation ◽  
Antiviral Drug ◽  
Statistical Modelling ◽  
Scattered Data ◽  
Pearson Coefficient ◽  
Statistical Relevance ◽  
Best Fit

Abstract In this article the positive cases of Covid19 in India with effect from 7th September, 2020 to 25th October, 2020 are analysed for statistical relevance . The scattered data are used to find out a model equation correlating two variables number of recovered Covid –patient with an interval of regular seven days . The best fit regression analysis shows a significant correlation of Pearson coefficient (r) with standard error ( s ) with a second –order rate law .The rate constant (k) obtained from this model can be simulated to stability aspects of antiviral drug modelling like Remdesivir as an objective of this work .

scholarly journals A Statistical Analysis on Recovery Cases of Covid19 in India

2020 ◽  
Author(s):  
JAYDIP DATTA
Keyword(s):  
Regression Analysis ◽  
Statistical Analysis ◽  
Mortality Rate ◽  
Standard Error ◽  
Model Equation ◽  
Scattered Data ◽  
Lower Mortality ◽  
Pearson Coefficient ◽  
Statistical Relevance ◽  
Best Fit

In this report the positive cases of Covid19 in India with effect from 7th September ,2020 to 25th October ,2020 are analysed for statistical relevance . The scattered data are used to find out a model equation correlating two variables number of recovered Covid –patient with an interval of regular seven days . The best fit regression analysis shows a significant correlation of Pearson coefficient (r) with standard error ( s ) with a probable lower mortality rate . Finally the limitations of this analysis is discussed herewith .

A best fit regression analysis to predict dosimetric parameters in prostate brachytherapy using 131 Cs given the impact of changing prostate edema

Brachytherapy ◽  
2009 ◽  
Vol 8 (2) ◽  
pp. 166
Author(s):  
Than S. Kehwar ◽  
Heather A. Jones ◽  
Sushil Beriwal ◽  
Ronald M. Benoit ◽  
Ryan P. Smith
Keyword(s):  
Regression Analysis ◽  
Prostate Brachytherapy ◽  
The Impact ◽  
Best Fit

PROTEINS, CARBOHYDRATES AND LIPIDS IN THE LARVAE, PUPAE AND ADULTS OF PECAN WEEVIL, CURCULIO CARYAE HORN

1985 ◽  
Vol 20 (1) ◽  
pp. 42-46
Author(s):  
A. C. Thompson ◽  
P. P. Sikorowski
Keyword(s):  
Fatty Acids ◽  
Regression Analysis ◽  
Fatty Acid ◽  
Rapid Decline ◽  
Average Life ◽  
Average Life Span ◽  
Logarithmic Curve ◽  
Polynomial Expression ◽  
Fatty Acid Data ◽  
Best Fit

Pecan weevil larvae, in the 4th instar, held at 20°C showed a rapid decline in fatty acids, carbohydrates and proteins with time. Regression analysis of the fatty acid data (with time) gave a best fit for a polynomial expression, whereas both protein and carbohydrate fit a logarithmic curve. The larvae at 20°C pupated in an average of 42 days. The average life span of adults fed sucrose water was 82 days.

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