• Journal of the Korean Statistical Society
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• v.5 no.1
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• pp.3-18
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• 1976

To test simultaneous significance of more than two linear regression coefficients, we can consider multivariate-t tests with critical regions in t-space instead of F-tests where t-values are t-statistics of significance tests of one coefficient. In this paper bivariate-t distributions and bivariate-t tests of two coefficients such as maxmod, minmod, one-tailed maxmod and one-tailed minmod tests are studied. Through the calculation of powers of test, it is learned that in some cases bivariate-t test are more powerful than F-tests.

• Transactions of the Korean Society of Automotive Engineers
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• v.25 no.2
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• pp.250-256
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• 2017

Automatic transmission(A/T) is one of a car's core components. The durability of A/T has an effect on the durability of the car. The input shaft of A/T passes the power directly from the engine, so the durability of the input shaft for A/T is likewise vital. In this study, the test method of the input shaft is considered and the load spectrum of A/T is analyzed to secure durability of the input shaft. The shape parameter, T-N curve of the input shaft torsional fatigue test are obtained for life evaluation and analysis. Results of this study can be used to get the basic background of the durability test for A/T components.

• The Korean Journal of Nuclear Medicine
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• v.14 no.1
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• pp.17-21
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• 1980

TRH stimulation tests and $T_3$ suppression tests were done in 13 patients with clinically suspected mild or early hyperthyroidism who were all conventional thyroid function tests gave results within the accepted normal range. The results were as follows 1. 6 patients with normal $T_3$ suppression test revealed normal TRH stimulation test and could be easily diagnosed as euthyroidism. 2. 7 patients with abnormal $T_3$ suppression test exhibited no TSH response to TRH stimulation test and could be easily diagnosed as hyperthyroidism. The TRH stimulation test is a single, sensitive and reliable test of thyroid function and can well replace $T_3$ suppression test in the diagnosis of marginal hyperthyroidism.

• International Journal of Reliability and Applications
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• v.15 no.1
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• pp.11-22
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• 2014

New classes of life distributions called new better (worse) than used at age $t_0$ in Laplace transform order, NBUL- $t_0$(NWUL - $t_0$) are introduced. For the classes NBUL - $t_0$(NWUL - $t_0$), preservation under convolution, mixture, mixing and the homogeneous Poisson shock model are studied. In the sequel, we obtain a test for $H_0$ : F is exponential versus $H_1$ : F is NBUL - $t_0$ and not exponential. The critical values and the powers of this test are calculated to assess the performance of the test. It is shown that the proposed test has high efficiencies for some commonly used distributions in reliability. Sets of real data are used as examples to elucidate the use of the proposed test for practical problems.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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• pp.167-173
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• 2005

This paper presents an autocorrelation test that is applicable to dynamic panel data models with serially correlated errors. The residual-based GMM t-test is a significance test that is applied after estimating a dynamic model by using the instrumental variable(IV) method and is directly applicable to any other consistently estimated residuals. Monte Carlo simulations show that the t-test has considerably more power than the $m_2$ test or the Sargan test under both forms of serial correlation (i.e., AR(1) and MA(1)).

• Journal of the Korean Statistical Society
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• v.34 no.4
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• pp.367-375
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• 2005

This paper presents an autocorrelation test that is applicable to dynamic panel data models with serially correlated errors. The residual-based GMM t-test is a significance test that is applied after estimating a dynamic model by using the instrumental variable (IV) method and is directly applicable to any other consistently estimated residuals. Monte Carlo simulations show that the t-test has considerably more power than the $m_2$ test or the Sargan test under both forms of serial correlation (i.e., AR(1) and MA(1)).

• Journal of Integrative Natural Science
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• v.15 no.1
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• pp.9-18
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• 2022

This research examines the power of bootstrap two-sample test, and compares it with the powers of two-sample t-test and Wilcoxon rank sum test, through simulation. For simulation work, a positively skewed and heavy tailed distribution was selected as a population distribution, the chi-square distributions with three degrees of freedom, χ²₃. For two independent samples, the fist sample was selected from χ²₃. The second sample was selected independently from the same χ²₃ as the first sample, and calculated d+ax for each sampled value x, a randomly selected value from χ²₃. The d in d+ax has from 0 to 5 by 0.5 interval, and the a has from 1.0 to 1.5 by 0.1 interval. The powers of three methods were evaluated for the sample sizes 10,20,30,40,50. The null hypothesis was the two population medians being equal for Bootstrap two-sample test and Wilcoxon rank sum test, and the two population means being equal for the two-sample t-test. The powers were obtained using r program language; wilcox.test() in r base package for Wilcoxon rank sum test, t.test() in r base package for the two-sample t-test, boot.two.bca() in r wBoot pacakge for the bootstrap two-sample test. Simulation results show that the power of Wilcoxon rank sum test is the best for all 330 (n,a,d) combinations and the power of two-sample t-test comes next, and the power of bootstrap two-sample comes last. As the results, it can be recommended to use the classic inference methods if there are widely accepted and used methods, in terms of time, costs, sometimes power.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.14 no.2
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• pp.9-16
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• 2006

FAA AC120-40B Level D flight dynamics model for T-50 Full Mission Trainer was successfully developed. Since AC120-40B Level D requires the quantitative validation tests for simulation model compared with flight test data, T-50 flight test data for each validation test item was gathered, and also automatic test environments which include AFT (Automatic Fidelity Tester) and STA (Simulation Test Analyzer) were developed. The final test results after the iterative test-tuning processes were all within the tolerances specified in AC120-40B Level D. Qualification Test Guide, QTG contains the detail test processes and results.

• Journal of Acupuncture Research
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• v.21 no.1
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• pp.176-188
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• 2004

This study was carried out to investigate statistical validity of medical articles that used various statistical techniques such as t-test, analysis of variance, correlation analysis, regression analysis and chi-square test. For study 429 original articles using those statistical methods were selected from Journal of Korean Acupuncture & Moxibusition Society published from 1984 to 2002. 429 original articles were reviewed to analyzed the statistical procedures. Results are summarized as follows : 1. In this study 93 articles(21.68%) of 429 ones didn't report statement of statistical method in detail. 2. 53 articles(12.53%) didn't report p-value in correctly, and 245 articles(57.11 %) used mean${\pm}$standard error (Mean${\pm}$SEM.) and 109 articles used mean${\pm}$standard deviation(Mean${\pm}$SD.). All of 23 articles using nonparametric statistical techniques made an error to central tendency or dispersion. 3. 175 articles(59.93%) and 14 articles(4.79%) of 292 ones made an error to description of equal variances and normal distribution. 4. 99 articles(50%) of 185 ones misused t-test and 4 articles of 5 ones misused chi-square test. 5. 28 articles(73.68%) of 38 ones using discrete variable misused parametric technique such as t-test or ANOVA. 2 articles and 1 article of 125 ones choosing paired samples misused independent t-test and Mann-Whitney U test. 6. 20 articles using analysis of variance didn't use multiple comparison.

• Interdisciplinary Bio Central
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• v.2 no.2
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• pp.4.1-4.6
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• 2010

The most common type of microarray experiment has a simple design using microarray data obtained from two different groups or conditions. A typical method to identify differentially expressed genes (DEGs) between two conditions is the conventional Student's t-test. The t-test is based on the simple estimation of the population variance for a gene using the sample variance of its expression levels. Although empirical Bayes approach improves on the t-statistic by not giving a high rank to genes only because they have a small sample variance, the basic assumption for this is same as the ordinary t-test which is the equality of variances across experimental groups. The t-test and empirical Bayes approach suffer from low statistical power because of the assumption of normal and unimodal distributions for the microarray data analysis. We propose a method to address these problems that is robust to outliers or skewed data, while maintaining the advantages of the classical t-test or modified t-statistics. The resulting data transformation to fit the normality assumption increases the statistical power for identifying DEGs using these statistics.