• Journal of the Korea Safety Management & Science
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• v.9 no.6
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• pp.193-196
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• 2007

This paper presents real examples of quality statistics for users to easily understand the concept and purpose for obtaining the degree of freedom. Moreover degree of freedom by Satterwaite can be used for linear combinations of unbiased variance. Finally effective degree of freedom by Welch-Satterthwaite is applicable to obtain expanded uncertainty considering type A and type B uncertainty.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1155-1163
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• 2016

This paper deals with an estimation procedure of variance components in a mixed effects model by projections. Projections are used to obtain sums of squares instead of using reductions in sums of squares due to fitting both the assumed model and sub-models in the fitting constants method. A projection matrix can be obtained for the residual model at each step by a stepwise procedure to test the hypotheses. A weighted least squares method is used for the estimation of fixed effects. Satterthwaite's approximation is done for the confidence intervals for variance components.

• The Korean Journal of Applied Statistics
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• v.29 no.2
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• pp.291-299
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• 2016

This paper discusses how to establish estimable functions when there are fixed and random effects in design models. It proves that estimable functions of mixed models are not related to random effects. A fitting constants method is used to obtain sums of squares due to random effects and Hartley's synthesis is used to calculate coefficients of variance components. To test about the fixed effects the degrees of freedom associated with divisor are determined by means of the Satterthwaite approximation.

• Journal of the Korea Safety Management & Science
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• v.12 no.1
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• pp.199-205
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• 2010

The research proposes the three-factor random measurement models for estimating the precision about operator, part, tool, and various measurement environments. The combined model with crossed and nested factors is developed to analyze the approximate F test by degrees of freedom given by Satterthwaite and point estimation of precisions from expected mean square. The model developed in this paper can be extended to the three useful models according to the type of nested designs. The study also provides the three-step procedures to evaluate the measurement precisions using three indexes such as SNR(Signal-To-Noise Ratio), R&R TR(Reproducibility&Repeatability-To-Total Precision Ratio), and PTR(Precision-To-Tolerance Ratio), The procedures include the identification of resolution, the improvement of R&R reduction, and the evaluation of precision effect.

• Journal of the Korea Safety Management & Science
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• v.11 no.3
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• pp.209-216
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• 2009

A development in method of evaluating the measurement precisions using approximate F tests and variance components from expected mean square (EMS) is investigated. The research proposes three-factor mixed measurement models with the fixed and random factors. Unrestricted and unconstrained design work was rarely studied, while restricted and constrained designs have been significantly discussed. The unrestricted and unconstrained designs assume to be an independence of interaction. The proposed evaluation method about the measurement precisions can be extended to four-factor random measurement model or mixed measurement model. The study also presents the three evaluation indexes of precisions such as R&RTR (Reproducibility & Repeatability-To-Total Precision Ratio), PTR (Precision-To-Tolerance Ratio), and SNR (Signal-To-Noise Ratio). Numerical examples are proposed to evaluate the approximate F tests with Satterthwaite degrees of freedom and three indexes using the measurement precisions from EMS.

• The Mathematical Education
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• v.45 no.2 s.113
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• pp.145-154
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• 2006

The main purpose of this study is to investigate the effect of departures from normality and equal variance on the two-sample test when the variances are unknown. We have found that type I error brought about a little bit change which is ignorable in relation to kurtosis. But the change of type I error was mainly based on the skewness of the parent population. In introductory statistics classes where data analysis includes techniques for detecting skewness of two populations, we recommend the two-sample t-test when maximal skewness of two populations is smalter than the value 4 when the variances seem equal. Furthermore, our simulations reveal that the two-sample t-test appears somewhat more robust than that of z-test if the assumption of equal variance is satisfied. In the case of unequal variance, the two-sample t-test appears somewhat more robust provided the t-statistic using Satterthwaite's approximate degrees of freedom.

• Korean Journal of Veterinary Research
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• v.47 no.2
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• pp.139-145
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• 2007

Measurement uncertainty could play an important role in the assessment of test results in laboratories and industries. We investigated measurement uncertainties possibly included in determination of flubendazole, a benzimidazole anthelmintic, in pork by HPLC. The concentration of flubendazole was 62.69 ng/g in a sample of pork. Uncertainty was estimated in the analytical procedure of flubendazole. A model equation was made for determination of flubendazole in pork. The four uncertainty components such as weight of sample, volume of sample, calibration curve, and recovery were selected to estimate measurement uncertainties. Standard uncertainty was calculated for each component and all the standard uncertainties were combined. The combined standard uncertainty was expanded to a sample population as an expanded uncertainty. The expanded uncertainty was calculated using k value on Student's t-table and effective degrees of freedom from Welch-Satterthwaite formula. The expanded uncertainty was calculated as 3.45 with the combined standard uncertainty, 1.584 6 and the k value, 2.18. The final expression can be ($62.69{\pm}3.45$) ng/g (confidence level 95%, k = 2.18). The uncertainty value might be estimated differently depending on the selection of the uncertainty components. It is difficult to estimate all the uncertainty factors. Therefore, it is better to take several big effecting components instead of many small effecting components.

• Journal of Animal Science and Technology
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• v.56 no.5
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• pp.16.1-16.9
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• 2014

Fatty acids (FA) have recently been used in several studies to infer the diet in a number of species. While these studies have been largely successful, most have dealt with predators that have a fairly specialized diet. In this paper, we used FA analysis as a tool to infer the diet of the nearctic river otter (Lontra canadensis). The river otter is an opportunistic predator known to subsist on a wide variety of prey including, fishes, crayfish, molluscs, reptiles and amphibians, among others. We analyzed the principle components of 60 FA from otters and 25 potential prey species in Illinois, USA. Prey species came from 4 major taxonomic divisions: fishes, crayfish, molluscs and amphibians. Within each division, most, but not all, species had significantly different profiles. Using quantitative FA signature analysis, our results suggest that, by mass, fish species are the most significant component of Illinois River otters' diet ($37.7{\pm}1.0%$). Molluscs ranked second ($32.0{\pm}0.8%$), followed by amphibians ($27.3{\pm}4.3%$), and finally, crayfish ($3.0{\pm}0.6%$). Our analysis indicates that molluscs make up a larger portion of the otter diet than previously reported. Throughout much of the Midwest there have been numerous otter reintroduction efforts, many of which appear to be successful. In regions where mollusc species are endangered, these data are essential for management agencies to better understand the potential impact of otters on these species. Our analysis further suggests that quantitative FA signature analysis can be used to infer diet even when prey species are diverse, to the extent that their FA profiles differ. Better understanding of the otter's metabolism of FA would improve inferences of diet from FA analysis.

• Journal of Korea Trade
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• v.27 no.4
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• pp.77-100
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• 2023

Purpose - Using the Model of Goal-Directed Behavior (MGB), this study identifies the critical factors that influence consumer intention to purchase an electric vehicle (EV). This study also provides differentiated policy implications to the Korean and Chinese governments and EV-related companies for the expansion of the EV market in both countries by comparing consumers' perceptions of EV purchase intentions. Design/methodology - Our extended MGB model adds to the standard model consideration of financial incentives, perceived risks, and environmental concerns. An online survey was conducted of Korean and Chinese consumers. Based on the collected responses, all tested hypotheses were verified using PLS-SEM (Partial Least Squares-Structural Equation Modeling). Differences in the path analysis results between Korea and China were compared and verified using Henseler's MGA (multi-group analysis), the parametric test, and the Welch-Satterthwaite test. Findings - The most critical factor that influences the intent to purchase an EV in consumers from both countries is personal desire. PBC and SN were identified as the critical factors that respectively increase personal desire in Korea and China. In addition, in Korea, among the three factors EC, FIP, and PR, environmental concerns were found to have the most significant impact on attitudes and purchase intention. In contrast, in China, economic factors (specifically financial incentives) had greater importance than environmental issues. Originality/value - This study has academic contributions in that it presents a new research model that includes financial incentive policies, environmental concerns, and perceived risk variables based on the MGB to explore consumers' purchase intentions. This study can also make a practical contribution in that it provides some meaningful implications to the governments and EV-related companies of both countries based on the differences in the analysis results of the Korean and Chinese markets.