ABSTRACT
Analysis of variance is used to test the significance of the difference between the means of two or more samples, but due to the influence of uncontrollable random factors and controllable factors imposed on the results in the study, the data obtained in the study presents a fluctuating state. In this paper, the single factor analysis of variance in the least significant difference method is used to analyze the aroma components of the collected Hubei Qingzhuan tea and Yunnan Pu'er tea, and the T test is used to complete the paired comparison between each group, which improves the sensitivity of the test and makes each level It is also possible to detect the slight difference in the mean value among them, which provides a new way of thinking for the scientific and reasonable evaluation index system.
- Mengjun M, Zhiming G, Shi T, Fanyang C and Xiuliang T 2018 Hubei. argri. sci. 7 11-4Google Scholar
- Huihui L, Yun Z, Sheng B and Shenghong Z 2018 Modern. food. 9 6-9Google Scholar
- Pengcheng Z, Panpan L, Shengpeng W, Jing T, Ling F, Ling Z and Ziming G 2018 Food. indus. technol. 39 88-92Google Scholar
- Haibo Y, Junfeng Y, Guozhu Y, Yongquan X and Fang W 2009 Chinese.tea. 31 11-3Google Scholar
- Ziming G, Xueping W and Siwei G 2009 Hubei. argri. sci. 7 211-5Google Scholar
- Panpan L, Pengcheng Z, Ziming G, Xueping W, Guiyi G 2018 Modern. food. technol. 34 83-93Google Scholar
- Dongtao Z, Jun S, Naixing Y and Guixing C 2015 Chinese. J.Tea. 56 68-79Google Scholar
- Sisi Y, Zheng B, Yahui H, Xingfei L, Chunlan W and Wenfang Z 2014 Food. sci. 35 252-6Google Scholar
- Jiangxun L, Liping D, Chao W, Wei L, Tao L and Dongguang X 2014 Food. sci. 35 191-5Google Scholar
- Fei L, Yun W and Ting Z 2018 Tea sci. 38 9-19Google Scholar
- Yanan Z, Yiling O, Li Q, Youcheng L and Lizeng X 2019 Food. indus.techn.40 7Google Scholar
- Zhonghua L, Zengsheng W, Jianan H and Zhaopeng S 1991 Tea sci. S1 8Google Scholar
- Yinghua L, Juan L and Xinhe Y 2017 Agricult. process.19 50-3Google Scholar
- Jingming N, Junting F, Xiaoyuan Z, Jingjing S, Zhengzhu Z and Caiwang H 2016 Food. indus.techn.37 127-133Google Scholar
- Bao, X., Luo, Q., Li, S., Crabbe, M.J.C., Yue, X. Corporate social responsibility and maturity mismatch of investment and financing: Evidence from polluting and non-polluting companies (2020) Sustainability (Switzerland), 12 (12), art. no. 4972. DOI: 10.3390/su12124972Google Scholar
- Shao, X.-F., Gouliamos, K., Luo, B.N.-F., Hamori, S., Satchell, S., Yue, X.-G., Qiu, J. Diversification and desynchronicity: An organizational portfolio perspective on corporate risk reduction (2020) Risks, 8 (2), art. no. 51. DOI: 10.3390/risks8020051Google Scholar
- Al-Zubaidi, S.M., Madfa, A.A., Mufadhal, A.A., Aldawla, M.A., Hameed, O.S., Yue, X.-G. Improvements in Clinical Durability From Functional Biomimetic Metallic Dental Implants (2020) Frontiers in Materials, 7, art. no. 106. DOI: 10.3389/fmats.2020.00106Google Scholar
Recommendations
Analysis of variance based on fuzzy observations
Analysis of variance ANOVA is an important method in exploratory and confirmatory data analysis. The simplest type of ANOVA is one-way ANOVA for comparison among means of several populations. In this article, we extend one-way ANOVA to a case where ...
The Evaluation Index System and Empirical Analysis of Influential Factors of Pear Production in Hebei Province
CSO '14: Proceedings of the 2014 Seventh International Joint Conference on Computational Sciences and OptimizationIn this article Grey Correlation Model is used to analyze the main factors affected pear production in Hebei Province, the result shows that the influences in order are: effective irrigation area > cultivated area > inundated area > agricultural acreage ...
A new statistic in the one-way multivariate analysis of variance
In the multivariate one-way analysis of variance a test statistic based solely on the rank orders of the data is proposed. In the two group case the statistic simplifies to a test of Puri and Sen [19]. Monte Carlo simulation techniques are used to ...
Comments