scholarly journals Research Methods in Weed Science: Statistics

Weed Science ◽  
2015 ◽  
Vol 63 (SP1) ◽  
pp. 166-187 ◽  
Author(s):  
Christian Ritz ◽  
Andrew R. Kniss ◽  
Jens C. Streibig
Keyword(s):  
Biological Sciences ◽  
Statistical Analysis ◽  
Research Methods ◽  
Confidence Intervals ◽  
Driving Force ◽  
Standard Errors ◽  
Weed Science ◽  
Regression Parameters ◽  
Experimental Variability ◽  
Correct Picture

There are various reasons for using statistics, but perhaps the most important is that the biological sciences are empirical sciences. There is always an element of variability that can only be dealt with by applying statistics. Essentially, statistics is a way to summarize the variability of data so that we can confidently say whether there is a difference among treatments or among regression parameters and tell others about the variability of the results. To that end, we must use the most appropriate statistics to get a “correct” picture of the experimental variability, and the best way of doing that is to report the size of the parameters or the means and their associated standard errors or confidence intervals. Simply declaring that the yields were 1 or 2 ton ha−1does not mean anything without associated standard errors for those yields. Another driving force is that no journal will accept publications without the data having been subjected to some kind of statistical analysis.

scholarly journals Analysis of Nonlinear Regression Models: A Cautionary Note

Dose-Response ◽  
2005 ◽  
Vol 3 (3) ◽  
pp. dose-response.0 ◽  
Author(s):  
Shyamal D. Peddada ◽  
Joseph K. Haseman
Keyword(s):  
Confidence Intervals ◽  
Regression Models ◽  
Nonlinear Models ◽  
Nonlinear Function ◽  
Standard Errors ◽  
True Parameter ◽  
Nonlinear Regression Models ◽  
Confidence Levels ◽  
Regression Parameters ◽  
Large Sample Theory

Regression models are routinely used in many applied sciences for describing the relationship between a response variable and an independent variable. Statistical inferences on the regression parameters are often performed using the maximum likelihood estimators (MLE). In the case of nonlinear models the standard errors of MLE are often obtained by linearizing the nonlinear function around the true parameter and by appealing to large sample theory. In this article we demonstrate, through computer simulations, that the resulting asymptotic Wald confidence intervals cannot be trusted to achieve the desired confidence levels. Sometimes they could underestimate the true nominal level and are thus liberal. Hence one needs to be cautious in using the usual linearized standard errors of MLE and the associated confidence intervals.

scholarly journals EXPRESS: Inter-Laboratory Application of Raman CO2 Densimeter Equations: Experimental Procedure and Statistical Analysis Using Bootstrapped Confidence Intervals

2021 ◽  
pp. 000370282098760
Author(s):  
Samantha Remigi ◽  
Tullio Mancini ◽  
Simona Ferrando ◽  
Maria Luce Frezzotti
Keyword(s):  
Statistical Analysis ◽  
Confidence Intervals ◽  
Spectral Resolution ◽  
Population Level ◽  
Standard Errors ◽  
Experimental Conditions ◽  
Experimental Procedure ◽  
Experimental Parameters ◽  
Density Values ◽  
New Equation

Raman spectroscopy has been used extensively to calculate CO2 fluid density in many geological environments, based on the measurement of the Fermi diad split (Δ; cm-1) in the CO2 spectrum. While recent research has allowed the calibration of several Raman CO2 densimeters, there is a limit to the inter-laboratory application of published equations. These calculate two classes of density values for the same measured Δ, with a deviation of 0.09 ± 0.02 g/cm3 on average. To elucidate the influence of experimental parameters on the calibration of Raman CO2 densimeters, we propose a bottom-up approach beginning with the calibration of a new equation, to evaluate a possible instrument-dependent variability induced by experimental conditions. Then, we develop bootstrapped confidence intervals for density estimate of existing equations to move the statistical analysis from a sample-specific to a population level. We find that Raman densimeter equations calibrated based on spectra acquired with similar spectral resolution calculate CO2 density values lying within standard errors of equations and are suitable for the inter-laboratory application. The statistical analysis confirms that equations calibrated at similar spectral resolution calculate CO2 densities equivalent at 95% confidence, and that each Raman densimeter does have a limit of applicability, statistically defined by a minimum Δ value, below which the error in calculated CO2 densities is too high.

Standards for physical fitness of biathletes during the period of sport skills perfectionм

2019 ◽  
Vol 7 (4) ◽  
pp. 43-50
Author(s):  
Vladimir Mikhalev ◽  
Elena Reutskaya ◽  
Pavel Pinyagin
Keyword(s):  
Rotator Cuff ◽  
Physical Fitness ◽  
Research Methods ◽  
Confidence Intervals ◽  
Research Results ◽  
Educational Experiment ◽  
Weak Points ◽  
Sport Skills ◽  
One Year ◽  
Testing Speed

The purpose – perfection of the techniques for controlling speed-strength capabilities and endurance of the rotator cuff muscles of biathletes during the period of sport skills perfection. Research methods and organization. The study involved 204 biathletes aged 15-17. We tested the speed- strength abilities and endurance of rotator cuff muscles with the Skierg Concept2 ski ergometer (USA). Research results. Significant changes in the endurance of rotator cuff muscles of biathletes occur in the age period from 15 to 16 years. The change in speed-strength abilities of female biathletes, in contrast to male biathletes, occurs against the background of an increase in the number of ski pole movements per minute. We processed the obtained data using the method of determining the boundaries of confidence intervals. Based on the data processed, we developed the standards for assessment of the speed-strength abilities and strength endurance of rotator cuff muscles of biathletes during the period of sport skills perfection with the Skierg Concept2 ski ergometer (USA). We tested applicability of the developed standards for speed-strength abilities and strength endurance of rotator cuff muscles in a one-year educational experiment. Conclusion. We proposed a methodology for testing speed-strength abilities and strength endurance of rotator cuff muscles with the Skierg Concept2 ski ergometer (USA) in the framework of our study. The developed stand- ards for assessing speed-strength abilities and strength endurance of rotator cuff muscles of biathletes during the period of sport skills perfection help to identify strong and weak points of fitness and to predict the possibility of achieving certain results by individual parameters.

Uncertainty in protein–ligand binding constants: asymmetric confidence intervals versus standard errors

2021 ◽  
Author(s):  
Vaida Paketurytė ◽  
Vytautas Petrauskas ◽  
Asta Zubrienė ◽  
Olga Abian ◽  
Margarida Bastos ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Confidence Intervals ◽  
Binding Constants ◽  
Standard Errors

scholarly journals PENERAPAN METODE BOOTSTRAP RESIDUAL DALAM MENGATASI BIAS PADA PENDUGA PARAMETER ANALISIS REGRESI

2014 ◽  
Vol 3 (4) ◽  
pp. 130
Author(s):  
NI MADE METTA ASTARI ◽  
NI LUH PUTU SUCIPTAWATI ◽  
I KOMANG GDE SUKARSA
Keyword(s):  
Regression Analysis ◽  
Statistical Analysis ◽  
Confidence Intervals ◽  
Bootstrap Method ◽  
Least Square ◽  
Prediction Tool ◽  
Analysis Method ◽  
Ordinary Least Square ◽  
Independent Variable ◽  
Parameter Estimators

Statistical analysis which aims to analyze a linear relationship between the independent variable and the dependent variable is known as regression analysis. To estimate parameters in a regression analysis method commonly used is the Ordinary Least Square (OLS). But the assumption is often violated in the OLS, the assumption of normality due to one outlier. As a result of the presence of outliers is parameter estimators produced by the OLS will be biased. Bootstrap Residual is a bootstrap method that is applied to the residual resampling process. The results showed that the residual bootstrap method is only able to overcome the bias on the number of outliers 5% with 99% confidence intervals. The resulting parameters estimators approach the residual bootstrap values ??OLS initial allegations were also able to show that the bootstrap is an accurate prediction tool.

scholarly journals Intermediate Stars in Extragalactic Radiosource Fields: Astrometric Measurements

2000 ◽  
Vol 180 ◽  
pp. 92-96
Author(s):  
Mirel Birlan ◽  
Gheorghe Bocsa
Keyword(s):  
Statistical Analysis ◽  
Standard Errors

AbstractThe statistical analysis of the O – C and the standard errors for the astrometric RRS2 standard stars, and the analysis of the standard errors for the intermediate PIRS stars for 75 extragalactic radiosource fields are presented. This study was performed at Bucharest Observatory.

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