Statistical Concepts

Alkarkhi, Abbas F.M.; Alqaraghuli, Wasin A.A.

doi:10.1016/b978-0-12-814262-2.00003-0

Cited by 3 publications

(6 citation statements)

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“…Discriminant analysis is a multivariate method of categorising objects into groups based on the linear combination of separating features. While multiple linear regression can predict outcomes, its application is limited in cases involving categorical variables (Alkarkhi & Alqaraghuli, 2019). The discriminant analysis comprises two steps: (1) testing the statistical significance of multiple variables using a multivariate test and (2) investigating significant mean differences across the groups if statistical significance exists (Brunner & Giannini, 2011).…”

Section: Discriminant Analysismentioning

confidence: 99%

Factors Determining Online Activities and Technology Use Among Older Adults in Thailand

Kraiwanit,

Jangjarat,

Srijam

2023

JSSH

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In the digital era, the use of technological tools and platforms has become increasingly prevalent among people, including older adults, for various daily activities such as social interactions, online payments or shopping, entertainment, and information seeking. The prudent use of technology by older adults provides several benefits, allowing them to undertake useful or convenient activities easily. Moreover, older adults with functional and up-to-date technological skills have better employment prospects, enabling them to remain financially independent, economically active, and contribute to the national economy. This study investigates whether demographic factors and internet-related behaviour influence online activities among older adults in Thailand. Data were collected through an online survey, and discriminant analysis was utilised to evaluate the hypothesis. The study’s findings suggest that gender, education, career, income, time spent online, online media platforms, and preferred online content can predict older citizens’ online activities but not marital status. Therefore, to ensure older Thai citizens remain active, well-informed, and connected, this study recommends increasing education, improving the appeal and reliability of digital news and information, and providing income support for older adults.

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Section: Discriminant Analysismentioning

confidence: 99%

Factors Determining Online Activities and Technology Use Among Older Adults in Thailand

Kraiwanit,

Jangjarat,

Srijam

2023

JSSH

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“…Statistical analysis or chemo-metrics can be employed after the curing process to observe the vanilla microbiome. A multivariate statistical approach; principal component analysis (PCA) can be used to minimize the dimensionality of a set of observations made up of a lot of interconnected variables 27,28 . Moreover, De Vrieze, et al 29 mentioned that 16S ribosomal RNA-based analysis could be established as an accepted technique for pro ling bacterial or fungi communities.…”

Section: Introductionmentioning

confidence: 99%

The isolation and identification of Bacillus velezensis ZN-S10 from vanilla (V. planifolia), and the microbial distribution after the curing process

Manyatsi,

Lin,

Jou

2024

Preprint

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The market value of vanilla beans (Vanilla planifolia) is constantly increasing due to their natural aroma and flavor properties that improve after a curing process, where bacteria colonization plays a critical role. However, a few publications suggest that bacteria play a role in the curing process. Hence, this study aimed to isolate Bacillus sp. that could be used for fermenting V. planifolia while analyzing their role in the curing process. Bacillus velezensis ZN-S10 identified with 16S rRNA sequencing was isolated from conventionally cured V. planifolia beans. The isolate (1 mL− 1 of 10− 7 CFU mL− 1) fermented and colonized non-cured vanilla pods. PCA results revealed distinguished bacterial communities of fermented vanilla and the control group, suggesting colonization of vanilla. Phylogenetic analysis showed that ZN-S10 was the dominant Bacillus genus member and narrowly correlated to B. velezensis EM-1 and B. velezensis PMC206-1, with 78 and 73% similarity, respectively. The bacterial taxonomic profiling of cured V. planifolia had a significant relative abundance of Firmicutes, Proteobacteria, Cyanobacteria, Planctomycetes, and Bacteroidetes phyla according to the predominance. Firmicutes accounted for 55% of the total bacterial sequences, suggesting their colonization and effective fermentation roles in curing vanilla.

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“…What is more, many weight‐determination methods either measure weights in a single step or do not take into account the interaction of evaluation indexes, making these methods (more or less) ineffective. For instance, principal component analysis is a critical technique for high‐dimensional data reduction and exploratory analysis, as well as the foundation and an essential component of many multivariate data‐processing systems 1 (Alkarkhi & Alqaraghuli, 2018). When principal component analysis is adopted, dimension reduction on the original variables should be performed.…”

Section: Introductionmentioning

confidence: 99%

“…1 1 It is a multivariate method for describing the relationship between multiple response variables and explaining total variation in data. This method is particularly advantageous when the variables under investigation have a high (positive or negative) correlation or when the number of independent variables is large (Alkarkhi & Alqaraghuli, 2018). …”

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Evaluation of China's regional innovation capability based on simulated annealing projection pursuit model and nested fuzzy evaluation model

Lin

2022

Expert Systems

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Regional innovation capability is an important indicator of both regional innovative and long‐term development. The purpose of this study is to build an evaluation index system for regional innovation capability in order to identify regional differences and support innovation more effectively. After establishing a reasonable evaluation value for regional innovation capability, a combination of simulated annealing optimized projection pursuit (SA–PP) and N‐layer nested fuzzy comprehensive evaluation models is used to assess China's regional innovation capabilities. The results show that the SA–PP model effectively mitigates the risk of erroneous evaluation results caused by index weight uncertainty, resulting in a more reasonable, robust, and intelligent assessment of regional innovation capability. Furthermore, the nested fuzzy comprehensive evaluation model is capable of easily resolving the evaluation factor set's heterogeneity and multilayer problems. The most significant influences on China's regional innovation capability are knowledge acquisition and enterprise innovation. The comprehensive score of the proposed combinational evaluation model manifests that provinces with strong regional innovation capabilities are mainly concentrated in the southeast coastal regions. The research results allow for precise weight determination and object ranking.

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Statistical Concepts

Cited by 3 publications

References 0 publications

Factors Determining Online Activities and Technology Use Among Older Adults in Thailand

Factors Determining Online Activities and Technology Use Among Older Adults in Thailand

The isolation and identification of Bacillus velezensis ZN-S10 from vanilla (V. planifolia), and the microbial distribution after the curing process

Evaluation of China's regional innovation capability based on simulated annealing projection pursuit model and nested fuzzy evaluation model

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