• Journal of the korean academy of Pediatric Dentistry
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• v.40 no.3
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• pp.223-232
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• 2013

There are many problems in evaluating study results by p value in null hypothesis testing for dental research. It is a logical fallacy to conclude that the null hypothesis is true when the it is not rejected. There are much serious misunderstanding about p value, and researchers should be cautious about interpreting p value in writing papers. As alternatives to complement or replace the null hypothesis significance testing, effect size, confidence interval, and Bayesian statistics are introduced.

• Journal of the Korean Society of Systems Engineering
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• v.15 no.1
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• pp.43-50
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• 2019

Statistical hypothesis tests are important for quantifying answers to questions about samples of data. The Step Process of Statistical Hypothesis Testing; state the null hypothesis, State the alternate hypothesis, State the alpha level, Find the z-score associated with alpha level, Find the test statistic using this formula, If the calculated t distribution value from the data is larger than the t distribution value of alpha level, then you are in the Rejection region and you can reject the Null Hypothesis with ($1-{\alpha}$) level of confidence.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.483-497
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• 2001

When one fits a parametric density function to a data set, it is usually advisable to test the goodness of the postulated model. In this paper we study the nonparametric tests for testing the null hypothesis against general alternatives, when the null hypothesis specifies the density function up to unknown parameters. We modify the test statistic which was proposed by the first author and his colleagues. Asymptotic distribution of the modified statistic is derived and its performance is compared with some other tests through simulation.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.32 no.4
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• pp.41-61
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• 2019

Background : The current medical statistics used in clinical research are the results of Fisher's significance test and the Neyman-Pearson hypothesis test, which were combined by psychologists. Also, in the philosophical background, it is related to Popper's falsificationism based hypothesis-deductive method and reduction to absurdity. Objectives : This study was designed to find complementary and alternative methods of null hypothesis and alternative hypothesis used for the clinical research methodology of Korean medicine otolaryngology. Methods : The body of this paper was divided into seven part. These are historical background, hypothesis test, hypothesis test method used in the design of clinical study, falsificationism and reduction to absurdity, problem and alternative method of the Neyman-Pearson hypothesis test, diagnosis example of sinusitis differentiation syndromes by Bayesian statistics. Through this process, we found out problems of frequentist statistics and suggested alternative methods. Result & Conclusion : As a solution to the problems of the null hypothesis and the alternative hypothesis, there are effects size, confidence interval, Bayesian statistics and Lakatos methodology of scientific research programmes.

• Communications for Statistical Applications and Methods
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• v.4 no.3
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• pp.787-793
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• 1997

It is well known that the assumption of independence is ofter not valid for real data. This phenomenon has been observed empirically by many prominent scientists. In this article the sensitivity of dependence on Bayes test of a sharp null hypothesis is considered. The robustness is considered with respect to the significant level and the prior probability on the null hypothesis.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.97-100
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• 2004

We propose some properties of fuzzy multivariate analysis of variance by fuzzy vector operation with agreement index. We deals fuzzy null hypotheses and fuzzy alternative hypothesis and define the agreement index for the grades of the judgements that the hypothesis is rejection or acceptance. Finally, we provide an example to evaluate the judgements.

• Communications for Statistical Applications and Methods
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• v.3 no.2
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• pp.69-76
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• 1996

In a two-way contingency table, the analyst is most interested in the hypotheses of either homogeneity or independence. For testing this as a null hypothesis, Pearson's ${\chi}^2$ statistic is most commonly used in practice. Once the null Hypothesis is rejected, he will further search forcells which caused the rejection of the null hypothesis. For this purpose, so called cell${\chi}^2$ components are used. In this paper, we derive the influence function of an obsevation to the ${\chi}^2$ statistic, with which cells with high influence can be identified.

• Journal of the Korea Safety Management & Science
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• v.24 no.4
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• pp.143-148
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• 2022

This paper attempted to analyze the correlation between the risk image of the evacuees in the tunnel and the variables that affect the evacuation behavior due to the closed feeling. As to whether there is a difference in the level of recognizing the tunnel risk image according to the distribution of jobs, the null hypothesis was rejected at the significance probability of 0.002, so it can be said that the level of recognition of the tunnel risk image varies depending on the job group. In the distribution difference between gender and tunnel risk image recognition level, the significance probability was 0.012, indicating that the null hypothesis was rejected, indicating that the tunnel risk recognition distribution according to gender was different. As a result of analyzing the distribution difference between the tunnel's closed feeling and the tunnel risk perception level, the significance probability was 0.001, and the null hypothesis was rejected, indicating that there was a difference in the tunnel risk image level.

• Proceedings of the PSK Conference
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• 2003.04a
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• pp.90-90
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• 2003

Sample size calculations play an important role in bioequivalence trials. In almost all clinical trials sample size is determined by considering power under the alternative hypothesis. The alternative hypothesis is the hypothesis that we wish to prove with experiments. Hence, in bioequivalence trials the alternative hypothesis is that two formulations are bioequivalent, while the null hypothesis is that the two formulations are not bioequivalent. (omitted)

• Journal of Korean Society for Quality Management
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• v.43 no.3
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• pp.289-298
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• 2015

Purpose: This study examined the problem of crack formation in the fire control system(FCS) of the K11 objective individual combat weapon(OCIW), using design of experiment analysis. Three hypothesis were considered. The first hypothesis is that bolted joint has an effect on impulse caused by firing the weapon and the second hypothesis is that a short time interval of shooting has an effect on impulse and lastly, the third hypothesis is that a positive correlation has between the bolted joint of the FCS and the impulse. Methods: The relationship between the bolted joint and the impulse cause by firing the weapon were examined experimentally. The first and second hypothesis was tested using correlation analysis and the t-test. Results: Using ANOVA, the first null hypothesis was rejected and the alternative hypothesis was accepted. ANONA confirmed the second null hypothesis. Correlation analysis dismissed the last null hypothesis. A positive correlation between the bolted joint and the impulse caused by shooting the weapon was verified. Conclusion: The bolted joint of the K11 FCS and the barrel of the K11 affect the impulse caused by firing the weapon. A positive correlation was established between the bolted joint of the FCS and the impulse on firing the K11 OICW.