• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.1013-1021
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• 2003

Huffer and Park (2002) proposed a chi-squared test for multivariate structure. Their test detects the deviation of data from mutual independence or multivariate normality. We will compute the Rao-Robson chi-squared version of the test, which is easy to apply in practice since it has a limiting chi-squared distribution. We will provide a self-contained argument that it has a limiting chi-squared distribution. We study the accuracy in finite samples of the limiting distribution. We finally compare the power of our test with those of other popular normality tests in an application to a real data.

• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.423-430
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• 2004

We provide the exact form of a Rao-Robson version of the chi-squared test of multivariate normality suggested by Park(2001). This test is easy to apply in practice since it is easily computed and has a limiting chi-squared distribution under multivariate normality. A self-contained formal argument is provided that it has the limiting chi-squared distribution. A simulation study is provided to study the accuracy, in finite samples, of the limiting distribution. Finally, a simulation study in a nonnormal distribution is conducted in order to compare the power of our test with those of other popular normality tests.

• Journal of applied mathematics & informatics
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• v.1 no.1
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• pp.43-48
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• 1994

There are some difficulties in applying the Pearson's Chi-Square Test for the continuous distribution. The problems include how to form class intervals for the test of fit how to employ in the test when the estimators of parameters are obtained from the ungrouped sample so on. In order to solve these problems we use the generalized minimum Chi-Square technique which is a test free of the complications associated with the Peason's Chi-Square test. This paper show how to apply the goodness of fit tests based on generalized minimum Chi-Square technique to the extreme values.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.117-126
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• 2001

We provide a simple chi-squared test of multivariate normality based on rectangular cells on the spherical data. This test is simple since it is a direct extension of the univariate chi-squared test to multivariate case and the expected cell counts are easily computed. We derive the limiting distribution of the chi-squared statistic via the conditional limit theorems. We study the accuracy in finite samples of the limiting distribution and then compare the poser of our test with those of other popular tests in an application to a real data.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.227-236
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• 2005

A chi-squared test of spherical symmetry is suggested. This test is easy to apply in practice since it is easy to compute and has a limiting chi-squared distribution under spherical symmetry. The result of Park(1998) can be used to show that it has the limiting chi-squared distribution. A simulation study is conducted to study the accuracy, in finite samples, of the limiting distribution. Finally, a simulation study that compares the power of our test with those of other tests of spherical symmetry is performed.

• Journal of the Korean Data and Information Science Society
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• v.20 no.3
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• pp.587-592
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• 2009

The most frequent use of the chi-square distribution is in the area of goodness-of-t of a distribution. The likelihood ratio test is a commonly used test statistic as the maximum likelihood estimate in statistical inferences. The recently revised versions of the likelihood ratio test statistics are used in estimating the parameter in the chi-square distribution. The estimates are compared with the commonly used method of moments and the maximum likelihood estimate.

• 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.

• The Korean Journal of Rehabilitation Nursing
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• v.7 no.2
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• pp.159-168
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• 2004

Purpose: The purpose of this study was to examine effect of Tai-Chi exercise program on joint flexibility for osteoarthritis patients. To evaluate the effects, quasi-experimental study was used for pre and post test with a nonequivalent control group. Method: Fifty-tow subjects participated in the experiment(twenty-seven for experimental group and twenty-five for control group) and they were from two different senior citizen centers in J city. The experiment period was from April 2002 through August 2002. The experiment group took part in Tai-Chi exercise program for eighteen weeks(three times a week for four weeks and five times a week for fourteen week). The exercise was performed for 50 minutes at every time (15 minutes for warm-up, 30 minutes for Tai-Chi exercise, and 5 minutes for ending). In order to pursue study purpose, the SPSS/WIN 8.0 program was chosen for the statistical analysis; ANCOVA was employed in examining test hypothesis; t-test and $x^2$-test were used to examine homogeneity between experimental and control group. Result: The study results were as follows :Score of vertebral joint flexibility increased significantly after of Tai-Chi exercise program. Score of wrist joint extension increased significantly after of Tai-Chi exercise program. Score of wrist joint flexion increased significantly after of Tai-Chi exercise program. Score of elbow joint extension increased significantly after of Tai-Chi exercise program. Score of elbow joint flexion increased significantly after of Tai-Chi exercise program. There was a slight increase of knee joint extension in the Tai-Chi exercise group compared to control group, but without statistical significance. Score of knee joint flexion increased significantly after of Tai-Chi exercise program. Score of ankle plantar flexion increased significantly after of Tai-Chi exercise program. Score of ankle dorsiflexion increased significantly after of Tai-Chi exercise program. Conclusion: As shown in the results, Tai-Chi exercise program can be effective nursing intervention for osteoarthritis patient to improve joint flexibility.

• Journal of muscle and joint health
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• v.18 no.2
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• pp.147-157
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• 2011

Purpose: The purpose of this study was to determine the effect of Tai Chi exercise program (Sun style 12 forms) on anxiety, powerlessness, self-esteem in community-dwelling elderly women. Methods: With a quasi-experimental design, a nonequivalent control group pretest-post test was used. Elderly women who agreed to participate in the study were assigned into an experimental group (n=23), or a control group (n=23). The experimental group participated in Tai Chi exercise program for 50 minutes per session, 2 times a week for 11 weeks. Tai Chi exercise program consisted of 10 minutes for warm-up, 35 minutes for main session, and 5 minutes for cooling down exercises. Anxiety, powerlessness, and self-esteem were measured with questionnaires to evaluate the effect of Tai Chi exercise program. The data were analyzed by using Chi-square test, Fisher's exact test, and Mann-Whitney test by a SPSS WIN 12.0 program. Results: The experimental group showed significant improvement for self-esteem (z=-3.130, p=.002), powerlessness(z=-3.267, p=.001), and anxiety (z=-2.932, p=.003) when compared to control group, Conclusions: Tai chi exercise program may be an effective nursing intervention to improve self-esteem and to reduce powerlessness and anxiety in community-dwelling elderly women.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.4 s.304
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• pp.51-58
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• 2005

This paper proposes a robust scene change detection technique that uses the weighted chi-square test and the automated threshold-decision algorithms. The weighted chi-square test can subdivide the difference values of individual color channels by calculating the color intensities according to NTSC standard, and it can detect the scene change by joining the weighted color intensities to the predefined chi-square test which emphasize the comparative color difference values. The automated threshold-decision at algorithm uses the difference values of frame-to-frame that was obtained by the weighted chi-square test. At first, The Average of total difference values is calculated and then, another average value is calculated using the previous average value from the difference values, finally the most appropriate mid-average value is searched and considered the threshold value. Experimental results show that the proposed algorithms are effective and outperform the previous approaches.