Design of the Bartlett and Hartley tests for homogeneity of variances under indeterminacy environment

The existing Bartlett’s test and Hartley’s test under classical statistics can be applied only when all observations in the sample are determined, precise and determinate. In some complex situations, it may not possible to measure the exact observations. In this case, the neutrosophic statistics is applied for the decision. In this paper, we present Bartlett’s test and Hartley’s test under the neutrosophic statistics. We present the designing for the proposed tests under neutrosophic statistical interval method. We present an example and compare the proposed neutrosophic Bartlett’s test and Hartley’s test over the existing tests under classical statistics. From the comparative study, we conclude that the proposed tests are quite effective, informative and flexible to be applied under the indeterminate environment.

[1]  M. E. Johnson,et al.  A Comparative Study of Tests for Homogeneity of Variances, with Applications to the Outer Continental Shelf Bidding Data , 1981 .

[2]  Patricia S. O Sullivan,et al.  100 Statistical Tests , 1995 .

[3]  Bartlett's Test Applied to Variance Component Models , 2003 .

[4]  Hsien-Chung Wu,et al.  Analysis of variance for fuzzy data , 2007, Int. J. Syst. Sci..

[5]  J. Gastwirth,et al.  The impact of Levene’s test of equality of variances on statistical theory and practice , 2009, 1010.0308.

[6]  María Asunción Lubiano,et al.  Bootstrap Comparison of Statistics for Testing the Homoscedasticity of Random Fuzzy Sets , 2012, SMPS.

[7]  María Asunción Lubiano,et al.  K-sample tests for equality of variances of random fuzzy sets , 2012, Comput. Stat. Data Anal..

[8]  Rudolf Kruse,et al.  Synergies of Soft Computing and Statistics for Intelligent Data Analysis, Proceedings of the 6th International Conference on Soft Methods in Probability and Statistics, SMPS 2012, Konstanz, Germany, October 4-6, 2012 , 2013, SMPS.

[9]  Yu Zhao,et al.  An Adjustment to the Bartlett's Test for Small Sample Size , 2015, Commun. Stat. Simul. Comput..

[10]  M. Daramola,et al.  Influence of operating variables on the transesterification of waste cooking oil to biodiesel over sodium silicate catalyst: A statistical approach , 2016 .

[11]  A. Abaza,et al.  Evaluation of low dose ionizing radiation effect on some blood components in animal model , 2016 .

[12]  Jiawei Tian,et al.  A novel breast ultrasound image segmentation algorithm based on neutrosophic similarity score and level set , 2018, Comput. Methods Programs Biomed..

[13]  Jun Ye,et al.  Expressions of Rock Joint Roughness Coefficient Using Neutrosophic Interval Statistical Numbers , 2017, Symmetry.

[14]  Jun Ye,et al.  Scale Effect and Anisotropy Analyzed for Neutrosophic Numbers of Rock Joint Roughness Coefficient Based on Neutrosophic Statistics , 2017, Symmetry.

[15]  Hon Keung Tony Ng,et al.  Improved tests for homogeneity of variances , 2017, Commun. Stat. Simul. Comput..

[16]  A. Oyeyiola,et al.  Statistical analyses and risk assessment of potentially toxic metals (PTMS) in children’s toys , 2017 .

[17]  M. Bouachrine,et al.  QSPR study of the retention/release property of odorant molecules in pectin gels using statistical methods , 2017 .

[18]  Jeanine L. Romano,et al.  Comparing the Performance of Approaches for Testing the Homogeneity of Variance Assumption in One-Factor ANOVA Models , 2017, Educational and psychological measurement.

[19]  Mohamed Abdel-Basset,et al.  A novel method for solving the fully neutrosophic linear programming problems , 2018, Neural Computing and Applications.

[20]  Muhammad Aslam,et al.  Design of Sampling Plan for Exponential Distribution Under Neutrosophic Statistical Interval Method , 2018, IEEE Access.

[21]  Mohamed Abdel-Basset,et al.  A hybrid approach of neutrosophic sets and DEMATEL method for developing supplier selection criteria , 2018, Des. Autom. Embed. Syst..

[22]  Muhammad Aslam,et al.  A New Sampling Plan Using Neutrosophic Process Loss Consideration , 2018, Symmetry.

[23]  M. Aslam Neutrosophic analysis of variance: application to university students , 2019, Complex & Intelligent Systems.

[24]  Mohamed Abdel-Basset,et al.  Neutrosophic Multi-Criteria Decision Making Approach for IoT-Based Enterprises , 2019, IEEE Access.

[25]  Mohamed Elhoseny,et al.  A novel model for evaluation Hospital medical care systems based on plithogenic sets , 2019, Artif. Intell. Medicine.

[26]  Florentin Smarandache,et al.  A hybrid neutrosophic multiple criteria group decision making approach for project selection , 2019, Cognitive Systems Research.

[27]  Mohamed Abdel-Basset,et al.  Cosine similarity measures of bipolar neutrosophic set for diagnosis of bipolar disorder diseases , 2019, Artif. Intell. Medicine.

[28]  Ahmed Aboelfetouh,et al.  An Integrated Neutrosophic-TOPSIS Approach and Its Application to Personnel Selection: A New Trend in Brain Processing and Analysis , 2019, IEEE Access.

[29]  Muhammad Aslam,et al.  Attribute Control Chart Using the Repetitive Sampling Under Neutrosophic System , 2019, IEEE Access.

[30]  Victor I. Chang,et al.  Evaluation of the green supply chain management practices: A novel neutrosophic approach , 2019, Comput. Ind..