• Title/Summary/Keyword: Distribution of sample mean

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Estimation of the Mean and Variance for Normal Distributions whose Both Sides are Truncated

  • Hong, Chong-Sun;Choi, Yun-Young
    • Communications for Statistical Applications and Methods
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    • v.9 no.1
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    • pp.249-259
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    • 2002
  • In order to estimate the mean and variance for a Normal distribution which is truncated at both right and left sides, maximum likelihood estimators based on the entire sample from the original distribution are compared with the sample mean and variance of the censored sample which is the data remaining after truncation using simulation. We found that, surprisingly, the mean squared error of the mean based on the censored data Is smaller than that of the full sample estimators.

Saddlepoint Approximation to the Distribution of General Statistic (일반적 통계량의 분포함수에 대한 안부점 근사)

  • 나종화
    • The Korean Journal of Applied Statistics
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    • v.11 no.2
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    • pp.287-302
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    • 1998
  • Saddlepoint approximation to the distribution function of sample mean(Daniels, 1987) is extended to the case of general statistic in this paper. The suggested approximation methods are applied to derive the approximations to the distributions of some statistics, including sample valiance and studentized mean. Some comparisons with other methods show that the suggested approximations are very accurate for moderate or small sample sizes. Even in extreme tail the accuracies are also maintained.

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Detection of Microbial Contamination in Commercial Berries

  • Cho, Kyu-Bong
    • Biomedical Science Letters
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    • v.23 no.4
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    • pp.333-338
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    • 2017
  • This study was performed to assess microbial contamination of Aronia melanocarpa, blueberry, raspberry, and cranberry sold in several markets. We investigated total aerobic bacteria and detected foodborne bacteria by multiplex PCR from Aronia melanocarpa, blueberry, raspberry, and cranberry. Total aerobic bacteria of each sample showed mean 3.54 log CFU/g for Aronia melanocarpa, mean 1.90 log CFU/g for blueberry, and mean 1.40 log CFU/g for raspberry, but not detected in cranberry. Specially, Aronia melanocarpa contained high total aerobic bacteria contamination among various berries and contamination level reached 4.17 log CFU/g in sample 5. To evaluate the effect of distribution conditions, we also investigated total aerobic bacteria of various berries. Total aerobic bacteria showed mean 2.89 log CFU/g for berries in refrigerated distribution and 1.40 log CFU/g in frozen distribution, but not in dry distribution. For assessment of foodborne bacteria contamination, we conducted PCR with multiplex primers of E. coli O157, S. aureus, B. cereus, V. parahaemolyticus, L. monocytogenes, Y. enterocolitica, Salmonella spp., Shigella spp. Among these foodborne bacteria, B. cereus was amplified in Aronia melanocarpa in sample 4 and blueberry in sample 1, 2, 3, and 5. The result of quantitative analysis of B. cereus contamination showed 4.08 log CFU/g of Aronia melanocarpa in sample 4 and higher contamination rate 4.07 log CFU/g of blueberry in sample 3. These results suggest that strict food safety control in harvest and distribution of various berries is necessary to prevent foodborne disease and improve microbiological safety.

Estimation in the exponential distribution under progressive Type I interval censoring with semi-missing data

  • Shin, Hyejung;Lee, Kwangho
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.6
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    • pp.1271-1277
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    • 2012
  • In this paper, we propose an estimation method of the parameter in an exponential distribution based on a progressive Type I interval censored sample with semi-missing observation. The maximum likelihood estimator (MLE) of the parameter in the exponential distribution cannot be obtained explicitly because the intervals are not equal in length under the progressive Type I interval censored sample with semi-missing data. To obtain the MLE of the parameter for the sampling scheme, we propose a method by which progressive Type I interval censored sample with semi-missing data is converted to the progressive Type II interval censored sample. Consequently, the estimation procedures in the progressive Type II interval censored sample can be applied and we obtain the MLE of the parameter and survival function. It will be shown that the obtained estimators have good performance in terms of the mean square error (MSE) and mean integrated square error (MISE).

New Definition of the Fibrogram and Its Application to Cotton Blending

  • Jeon, Boong-Soo
    • Fibers and Polymers
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    • v.6 no.4
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    • pp.332-335
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    • 2005
  • The fibrogram theory is newly derived from the superposition principle of the conventional staple diagram, in which the left-hand ends of the fibers have to share a common starting point in order for the fiber length distribution to be measured, and the right-hand ends of the fibers form points. It is shown that the fibrogram is the staple diagram of the fiber sample having different random starting points, as well as the double cumulative distribution function of the frequency length function in the length biased sample. Also, the various means, viz. the numerical mean length, numerical mean length in median, length biased mean length, and length biased mean length in median, and the various upper half means, viz. the numerical upper half mean length, numerical upper half mean length in median, length biased upper half mean length, and length biased upper half mean length in median, are discussed in relation to the cotton blending process.

Approximate Maximum Likelihood Estimation for the Three-Parameter Weibull Distribution

  • Kang, S.B.;Cho, Y.S.;Choi, S.H.
    • Communications for Statistical Applications and Methods
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    • v.8 no.1
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    • pp.209-217
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    • 2001
  • We obtain the approximate maximum likelihood estimators (AMLEs) for the scale and location parameters $\theta$ and $\mu$ in the three-parameter Weibull distribution based on Type-II censored samples. We also compare the AMLEs with the modified maximum likelihood estimators (MMLEs) in the sense of the mean squared error (MSE) based on complete sample.

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Saddlepoint approximation for distribution function of sample mean of skew-normal distribution (왜정규 표본평균의 분포함수에 대한 안장점근사)

  • Na, Jong-Hwa;Yu, Hye-Kyung
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.6
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    • pp.1211-1219
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    • 2013
  • Recently, the usage of skew-normal distribution, instead of classical normal distribution, is rising up in many statistical theories and applications. In this paper, we deal with saddlepoint approximation for the distribution function of sample mean of skew-normal distribution. Comparing to normal approximation, saddlepoint approximation provides very accurate results in small sample sizes as well as for large or moderate sample sizes. Saddlepoint approximations related to the skew-normal distribution, suggested in this paper, can be used as a approximate approach to the classical method of Gupta and Chen (2001) and Chen et al. (2004) which need very complicate calculations. Through simulation study, we verified the accuracy of the suggested approximation and applied the approximation to Robert's (1966) twin data.

Methods and Sample Size Effect Evaluation for Wafer Level Statistical Bin Limits Determination with Poisson Distributions (포아송 분포를 가정한 Wafer 수준 Statistical Bin Limits 결정방법과 표본크기 효과에 대한 평가)

  • Park, Sung-Min;Kim, Young-Sig
    • IE interfaces
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    • v.17 no.1
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    • pp.1-12
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    • 2004
  • In a modern semiconductor device manufacturing industry, statistical bin limits on wafer level test bin data are used for minimizing value added to defective product as well as protecting end customers from potential quality and reliability excursion. Most wafer level test bin data show skewed distributions. By Monte Carlo simulation, this paper evaluates methods and sample size effect regarding determination of statistical bin limits. In the simulation, it is assumed that wafer level test bin data follow the Poisson distribution. Hence, typical shapes of the data distribution can be specified in terms of the distribution's parameter. This study examines three different methods; 1) percentile based methodology; 2) data transformation; and 3) Poisson model fitting. The mean square error is adopted as a performance measure for each simulation scenario. Then, a case study is presented. Results show that the percentile and transformation based methods give more stable statistical bin limits associated with the real dataset. However, with highly skewed distributions, the transformation based method should be used with caution in determining statistical bin limits. When the data are well fitted to a certain probability distribution, the model fitting approach can be used in the determination. As for the sample size effect, the mean square error seems to reduce exponentially according to the sample size.

Asymptotic Distribution of Sample Autocorrelation Function for the First-order Bilinear Time Series Model

  • Kim, Won-Kyung
    • Journal of the Korean Statistical Society
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    • v.19 no.2
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    • pp.139-144
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    • 1990
  • For the first-order bilinear time series model $X_t = aX_{t-1} + e_i + be_{t-1}X_{t-1}$ where ${e_i}$ is a sequence of independent normal random variables with mean 0 and variance $\sigma^2$, the asymptotic distribution of sample autocarrelation function is obtained and shown to follow a normal distribution. The variance of the asymptotic distribution is of a complicated form and hence a bootstrap estimate of the variance is proposed for large sample inference. This result can be used to distinguish between different bilinear models.

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Comparisons of Probability and Statistics Education in Mathematics Textbooks in Korea High School

  • Lee, Sang-Bock
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.3
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    • pp.523-529
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    • 2004
  • In Korea, mathematics education has been changed according to the 7th national mathematics curriculum renovated by the Ministry of Education and Human Resources Development announcement in 1997. The education of probability and Statistics has been carried out as a part of this curriculum. We analyze and compare 3 kinds of mathematics textbooks for 10-12 grade students. Descriptions of random variable, sample variance and sample standard deviation, distribution of sample mean, and etc. which are on some textbooks, are misleaded in school education. We suggest the unbiased estimator of sample variance in textbooks and distributions of sample means with normal population assumption.

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