Understanding the tumor heterogeneity due to differences in the growth pattern of metastatic tumors and rate of change is important for understanding the sensitivity of tumor cells to drugs and finding appropriate therapies. It is often possible to test for differences in population means using t-test or ANOVA when the group of N samples is distinct. However, these statistical methods can not be used unless the groups are distinguished as the data covered in this paper. Statistical methods have been studied to test heterogeneity between samples. The minimum combination t-test method is one of them. In this paper, we propose a maximum combinatorial t-test method that takes into account combinations that bisect data at different ratios. Also we propose a method based on the idea that examining the heterogeneity of a sample is equivalent to testing whether the number of optimal clusters is one in the cluster analysis. We verified that the proposed methods, maximum combination t-test method and gap statistic, have better type-I error and power than the previously proposed method based on simulation study and obtained the results through real data analysis.
We have inquired on what the statistical classes of the secondary schools had been aiming to, say the epistermlogical objects. And we now appreciate that the main obstacle to the systematic articulation is the lack of anticipation on what the statistical concepts are. This study focuses on the ingredients of the statistical concepts. Those are to be the ground of the systematic articulation of statistic courses, especially of the one for the school kids. Thus we required that those ingredients must satisfy the followings. i) directly related to the contents of statistics ii) psychologically developing iii) mutually exclusive each other as much as possible iv) exhaustive enough to cover all statistical concepts We examined what and how statisticians had been doing and the various previous views on these. After all we suggest the following three concepts are the core of conceptual developments of statistic, say the concept of distributions, the summarizing ability and the concept of samples. By the concepts of distributions we mean the frequency views on each random categories and that is developing from the count through the probability along ages. Summarizing ability is another important resources to embed his probe with the data set. It is not only viewed as a number but also to be anticipated as one reflecting a random phenomena. Inductive generalization is one of the most hazardous thing. Statistical induction is a scientific way of challenging this and this starts from distinguishing the chance with the inevitable consequences. One's inductive logic grows up along with one's deductive arguments, nevertheless they are different. The concept of samples reflects' one's view on the sample data and the way of compounding one's logic with the data within one's hypothesis. With these three in mind we observed Korean Statistic Curriculum from K to 12. Distributional concepts are dealt with throughout but not sequenced well. The way of summarization has been introduced in the 1 st, 5th, 7th and the 10th grade as a numerical value only. One activity on the concept of sample is given at the 6th grade. And it jumps into the statistical reasoning at the selective courses of ' Mathematics I ' or of ' Probability and Statistics ' in the grades of 11-12. We want to suggest further studies on the developing stages of these three conceptual features so as to obtain a firm basis of successive statistical articulation.
Impurity profiling analysis of methamphetamine seized in Korea was investigated for the evidential and intelligent purpose. Samples were extracted with ethylacetate which contai ns internal standard of dioctylsebacate under basic condition and extracts were analyzed by GC-FID. Ephedrine, chloroephedrine & 1,2-dimethyl-3-phenylaziridine were identified impurities in illicit methamphetamine by GC-MS. These impurities revealed that most of abused methamphetamine in Korea were synthesized from ephedrine as a starting material. For the classification of samples. firstly, 24 impurity peaks were selected after inspection of every peak in 50 samples as the specific markers of impurities. Secondly, corresponding peak retention time and area ratio to the internal standard were calculated and database was created with values of 24 peaks by in-house program. Finally, cluster analysis was attempted with the resultant profiles using the STAR plot, which was based on the Euclidian distance for evaluating similarity among samples. A total of 76 samples were divided into 8 different groups within 90% statistical similarity and inter-batch samples showed similar impurity patterns by this procedure. In conclusion, the analysis of impurities is a suitable index for estimation the common or different origin of methamphetamine sample.
A goodness-of-fit test for the two-parameter exponential distribution, for use with the singly Type I and Type II right censored samples, is proposed. The test statistic is based on the $L_1$-norm of discrepancy between the cumulative distribution function and the empirical distribution function. To deal with the unknown parameters problem, the K- transformation is considered and modified to be applied to the censored samples. Rosenblatt's transformation is extended to the cases of Type I and Type II censored samples, in order to transform the censored samples into the complete ones. The critial values of the test statistic are obtained by Monte Carlo simulations for some finite sample sizes. The power studies are conducted to compare the proposed test with the Pettitt(1977) test for exponentiality with censored samples. It appears that the proposed test has relatively good power properties for moderate and large sample sizes.
Makade, Chetana S.;Meshram, Ganesh K.;Warhadpande, Manjusha;Patil, Pravinkumar G.
The Journal of Advanced Prosthodontics
/
v.3
no.2
/
pp.90-95
/
2011
PURPOSE. To compare the fracture resistance and the mode of failure of endodontically treated teeth restored with different post-core systems. MATERIALS AND METHODS. Root canal treatment was performed on 40 maxillary incisors and the samples were divided into four groups of 10 each. For three experimental groups post space preparation was done and teeth were restored with cast post-core (Group B), stainless steel post with composite core (Group C) and glass fiber post with composite core using adhesive resin cement (Group D). Control group (A) samples were selected with intact coronal structure. All the samples were prepared for ideal abutment preparation. All the samples were subjected to a load of 0.5 mm/min at $130^{circ}$.until fracture occurred using the universal testing machine. The fracture resistance was measured and the data were analyzed statistically. The fracture above the embedded resin was considered to be favorable and the fracture below the level was considered as unfavorable. The statistical analysis of fracture resistance between different groups was carried out with t-test. For the mode of failure the statistical analysis was carried out by Kruskal-Wallis test and Chi-Square test. RESULTS. For experimental group Vs control group the fracture resistance values showed significant differences (P<.05). For the mode of failure the chi-square value is 16.1610, which means highly significant (P=.0009) statistically. CONCLUSION. Endodontically treated teeth without post core system showed the least fracture resistance demonstrating the need to reinforce the tooth. Stainless steel post with composite core showed the highest fracture resistance among all the experimental groups. Teeth restored with the Glass fiber post showed the most favorable fractures making them more amenable to the re-treatment.
Although concrete is the most widely used construction material, its deficiency in shrinkage and low tensile resistance is undeniable. However, the aforementioned defects can be partially modified by addition of fibers. On the other hand, possibility of adding waste materials in concrete has provided a new ground for use of recycled concrete aggregates in the construction industry. In this study, a constant combination of recyclable coarse and fine concrete aggregates was used to replace the corresponding aggregates at 50% substitution percentage. Moreover, in order to investigate the effects of fibers on mechanical and durability properties of recycled aggregate concrete, the amounts of 0.5%, 1%, and 1.5% steel fibers (ST) and 0.05%, 0.1% and 0.15% polypropylene (PP) fibers by volumes were used individually and in hybrid forms. Compressive strength, tensile strength, flexural strength, ultrasonic pulse velocity (UPV), water absorption, toughness, elastic modulus and shrinkage of samples were investigated. The results of mechanical properties showed that PP fibers reduced the compressive strength while positive impact of steel fibers was evident both in single and hybrid forms. Tensile and flexural strength of samples were improved and the energy absorption of samples containing fibers increased substantially before and after crack presence. Growth in toughness especially in hybrid fiber-reinforced specimens retarded the propagation of cracks. Modulus of elasticity was decreased by the addition of PP fibers while the contrary trend was observed with the addition of steel fibers. PP fibers decreased the ultrasonic pulse velocity slightly and had undesirable effect on water absorption. However, steel fiber caused negligible decline in UPV and a small impact on water absorption. Steel fibers reduce the drying shrinkage by up to 35% when was applied solely. Using fibers also resulted in increasing the ductility of samples in failure. In addition, mechanical properties changes were also evaluated by statistical analysis of MATLAB software and smoothing spline interpolation on compressive, flexural, and indirect tensile strength. Using shell interpolation, the optimization process in areas without laboratory results led to determining optimal theoretical points in a two-parameter system including steel fibers and polypropylene.
Anastasios Katsileros;Nikolaos Antonetsis;Paschalis Mouzaidis;Eleni Tani;Penelope J. Bebeli;Alex Karagrigoriou
Communications for Statistical Applications and Methods
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v.31
no.1
/
pp.1-35
/
2024
The assumption of homoscedasticity is one of the most crucial assumptions for many parametric tests used in the biological sciences. The aim of this paper is to compare the empirical probability of type I error and the power of ten parametric and two non-parametric tests for homoscedasticity with simulations under different types of distributions, number of groups, number of samples per group, variance ratio and significance levels, as well as through empirical data from an agricultural experiment. According to the findings of the simulation study, when there is no violation of the assumption of normality and the groups have equal variances and equal number of samples, the Bhandary-Dai, Cochran's C, Hartley's Fmax, Levene (trimmed mean) and Bartlett tests are considered robust. The Levene (absolute and square deviations) tests show a high probability of type I error in a small number of samples, which increases as the number of groups rises. When data groups display a nonnormal distribution, researchers should utilize the Levene (trimmed mean), O'Brien and Brown-Forsythe tests. On the other hand, if the assumption of normality is not violated but diagnostic plots indicate unequal variances between groups, researchers are advised to use the Bartlett, Z-variance, Bhandary-Dai and Levene (trimmed mean) tests. Assessing the tests being considered, the test that stands out as the most well-rounded choice is the Levene's test (trimmed mean), which provides satisfactory type I error control and relatively high power. According to the findings of the study and for the scenarios considered, the two non-parametric tests are not recommended. In conclusion, it is suggested to initially check for normality and consider the number of samples per group before choosing the most appropriate test for homoscedasticity.
Journal of the Korea Academia-Industrial cooperation Society
/
v.17
no.5
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pp.645-652
/
2016
The statistical modeling of input random variables is necessary in reliability analysis, reliability-based design optimization, and statistical validation and calibration of analysis models of mechanical systems. In statistical modeling methods, there are the Akaike Information Criterion (AIC), AIC correction (AICc), Bayesian Information Criterion, Maximum Likelihood Estimation (MLE), and Bayesian method. Those methods basically select the best fitted distribution among candidate models by calculating their likelihood function values from a given data set. The number of data or parameters in some methods are considered to identify the distribution types. On the other hand, the engineers in a real field have difficulties in selecting the statistical modeling method to obtain a statistical model of the experimental data because of a lack of knowledge of those methods. In this study, commonly used statistical modeling methods were compared using statistical simulation tests. Their advantages and disadvantages were then analyzed. In the simulation tests, various types of distribution were assumed as populations and the samples were generated randomly from them with different sample sizes. Real engineering data were used to verify each statistical modeling method.
The prevalence of Bacillus cereus was determined in salad and Kimbab obtained from commercial retailers. Among the 100 salad samples analyzed, 54 samples were negative for B. cereus, whereas the bacterial count was < 10 colony forming units (CFU)/g in 8 samples, < 100 CFU/g in 25 samples, < 1,000 CFU/g in 11 samples, and > 1,000 CFU/g in 2 samples. The mean (standard deviation) was 1.18 log CFU/g (${\pm}0.71$ log CFU/g). In Kimbab, B. cereus was isolated from 20 samples; the mean bacterial count was 1.01 log CFU/g (${\pm}0.71$ log CFU/g). On the basis of the monitoring data, a statistical sampling plan was determined with the NEW sampleplan program (ICMSF), which was used as an analytical tool. To identify the most suitable sampling plan, the microbial limits (m, M) and the maximum allowable number of sample units yielding unsatisfactory test results (c) were varied, but the number of samples units, n = 5, was fixed. Sampling plans showing an acceptable probability (Pa) over 0.95 were considered suitable. Two plans (A and B) were finally suggested. Parameters for plan A are n = 5, c = 0, m = 1,000, and M = 10,000 and for plan B are n = 5, c = 2, m = 100, and M = 1,000. Interestingly, the latter plan was identical to the microbial sampling plan used in New Zealand. Thus, it was concluded that the suggested plan can be used as a sampling plan that is in line with international standards.
Objective: Detection of adulteration in processed meats is an important issue for some countries due to substitution of beef with a cheaper source of protein like poultry. In this study, the presence of chicken meat was investigated using real-time polymerase chain reaction (real-time PCR) and enzyme-linked immunosorbent assay (ELISA) techniques to verify adulteration of fermented sausage samples. Methods: A total of 60 commercial samples were collected from 20 establishments in three replicates including 10 fermented sausage manufacturers and 10 butchers to investigate the presence of chicken meat with the sequential use of real-time PCR and ELISA techniques. In addition, pH, moisture content, water activity and color values of the samples were determined. Results: Both real-time PCR and ELISA showed agreement on the presence or absence of chicken meat in 55 out of 60 fermented sausage samples and chicken meat was identified with both methods in 16 samples. Five samples produced inconsistent results for the presence of chicken meat in the first run. Nevertheless, the presence of chicken meat was verified with both methods when these samples were analyzed for the second time. In addition, the average physico-chemical values of the fermented sausage samples tested positive for chicken meat were not significantly different from some of those fermented sausage samples tested negative for the chicken meat. Conclusion: The sequential use of real-time PCR and ELISA techniques in fermented sausages could be beneficial for the government testing programs to eliminate false negatives for detection of adulteration with chicken meat. Furthermore, consumers should not rely on some of the quality cues including color to predict the adulteration of fermented sausages with chicken meat since there were no statistical differences among some of the samples tested positive and negative for chicken meat.
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