• Journal of the Korean Data and Information Science Society
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• v.15 no.3
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• pp.543-554
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• 2004

In teaching statistics, the part which is very important but difficult to understand to the students is estimation and hypothesis testing. This paper introduces the developed program about estimation and hypothesis testing by using Excel Macro. This program will help learners to study and use a statistical inference conveniently, and to get a good learning effect.

• Journal of the Korean Statistical Society
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• v.27 no.2
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• pp.197-203
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• 1998

To test the hypothesis of complete or total independence for a multi-way contingency table, the Pearson chi-squared test statistic is usually employed under Poisson or multinomial models. It is well known that, under the hypothesis, this statistic follows an asymptotic chi-squared distribution. We consider the case where all marginal sums of the contingency table are fixed. Using conditional limit theorems, we show that the chi-squared test statistic has the same limiting distribution for this case.

• Industrial Engineering and Management Systems
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• v.15 no.4
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• pp.432-445
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• 2016

A random profile is the result of a process, the output of which is a function instead of a scalar or vector quantity. In the nature of these objects, two main dimensions of "functionality" and "randomness" can be recognized. Valuable researches have been conducted to present control charts for monitoring such processes in which a regression approach has been applied by focusing on "randomness" of profiles. Performing other statistical techniques such as hypothesis testing for different parameters, comparing parameters of two populations, ANOVA, DOE, etc. has been postponed thus far, because the "functional" nature of profiles is ignored. In this paper, first, some needed theorems are proven with an applied approach, so that be understandable for an engineer which is unfamiliar with advanced mathematical analysis. Then, as an application of that, a statistical test is designed for mean of continuous random profiles. Finally, using experimental operating characteristic curves obtained in computer simulation, it is demonstrated that the presented tests are properly able to recognize deviations in the null hypothesis.

• Nuclear Engineering and Technology
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• v.53 no.5
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• pp.1664-1675
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• 2021

In order to verify the statistical performance of the nonparametric tests used in the MARSSIM approach, all plausible contamination distribution types that can be encountered in a survey area should be investigated. As the first of such investigations, this study aims to perform the verification for normal distribution of the contamination in a survey area by simulating the collection of random samples from it through the Monte Carlo simulation. The results of the simulations conducted for a total of 81 simulation cases showed that Sign test and WRS test both exhibited an excellent statistical performance: 100% for the former and 98.8% for the latter. Therefore, in final status surveys of the MARSSIM approach, a high statistical performance can be expected in applying the nonparametric hypothesis tests to survey areas whose net contamination can be assumed to be normally distributed.

• The Journal of Korean Association of Computer Education
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• v.3 no.2
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• pp.107-114
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• 2000

In this study, a program for statistics education is developed. This program deals with statistical hypothesis testing which is indispensible to demonstrate the research hypothesis. Statistical inference which is the process of using data obtained from a sample to make inference about the characteristics of a population is an essential concept to peoples to learn or use statistics. But in practice, there are many cases of wrong application and peoples think that statistics is hard to understand. Therefore, it is very important subject to teach easily and rightly statistics, specially elementary statistics. This program is developed especially for non-specialist. This program under multimedia environment which includes sound, video, animation etc. can interest students greatly. It doesn't show only the result but make it possible for students to execute the program by stages. By executing it, the students can understand the method and meaning of statistical hypothesis testing naturally.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.765-774
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• 2002

Suppose one is given a vector X of a finite set of quantities $X_i$ which are independent Poisson random variables. A null hypothesis $H_0$ about E(X) is to be tested against an alternative hypothesis $H_1$. A quantity $\sum\limits_{i}w_ix_i$ is to be computed and used for the test. The optimal values of $W_i$ are calculated for three cases: (1) signal to noise ratio is used in the test, (2) normal approximations with unequal variances to the Poisson distributions are used in the test, and (3) the Poisson distribution itself is used. The above three cases are considered to the situations that are without background noise and with background noise. A comparison is made of the optimal values of $W_i$ in the three cases for both situations.

• Journal of the Korean Statistical Society
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• v.25 no.1
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• pp.81-94
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• 1996

This paper suggests a new criterion for testing the general linear hypothesis about coefficients in multivariate growth curve model. It is developed from a Bayesian point of view using the highest posterior density region methodology. Likelihood ratio test criterion(LRTC) by Khatri(1966) results as an approximate special case. It is shown that under the simple case of vague prior distribution for the multivariate normal parameters a LRTC-like criterion results; but the degrees of freedom are lower, so the suggested test criterion yields more conservative test than is warranted by the classical LRTC, a result analogous to that of Berger and Sellke(1987). Moreover, more general(non-vague) prior distributions will generate a richer class of tests than were previously available.

• Communications for Statistical Applications and Methods
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• v.2 no.1
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• pp.112-121
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• 1995

Let $p_1$ and $p_2$ be the proportions of two populations. To test the hypothesis $H_0 : p_1 = p_2$, we usually use the $x^2$ statistic, the large sample binomial statistic Z, and the Generalized Likelihood Ratio statistic-2log $\lambda$developed based on different mathematical rationale, respectively. Since testing the above hypothesis is equivalent to testing whether two populations follow the common Bernoulli distribution, one may also test the hypothesis by comparing 1 with the ratio of each density estimate and the hypothesized common density estimate, called comparison density, which was devised by Parzen(1988). We show that the above traditional test statistics ate actually estimating the measure of distance between the true densities and the common density under $H_0$ by representing them with the comparison density.

• The Journal of Korean Medicine
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• v.24 no.3
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• pp.118-129
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• 2003

Objective : To learn the distributional characteristics of Sasang constitutions, Methods : We statistically analyzed those 1338 patients who had been treated at Iksan Wonkwang Oriental Medicine during the period of three years from 2000 to 2002. The data were obtained through the electronic chart developed by Kim Jong- Yeol, and analyzed using the statistical Package SPSS. Results : The distributional ratio of Soeumin : Soyangin : Taeumin was 22.8 : 29.2 : 47.8. Thus the hypothesis : 'the distributional ratio of Soeumin : Soyangin : Taeumin is 2 : 3 : 5' was barely rejected by $x^2$ test for goodness-of-fit at the significance level of 5 %. When $x^2$ test for homogeneity was applied, the distributional characteristics between women and men were different and the distributional characteristics among several age groups were different under significance level of 5%. Conclusion : Though the hypothesis: 'the distributional ratio of Soeumin : Soyangin : Taeumin is 2 : 3 : 5' was rejected by $x^2$ test at the significance level of 5%, the observed distributional ratio was not so far away from the hypothesis.

• 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.