Multivariate Statistical Modeling and Data Analysis.

1989 ◽  
Vol 84 (407) ◽  
pp. 847
Author(s):  
Joseph S. Verducci ◽  
H. Bozdogan ◽  
A. K. Gupta
Keyword(s):  
Data Analysis ◽  
Statistical Modeling ◽  
Multivariate Statistical

scholarly journals Multivariate statistical data analysis of cell‐free protein synthesis toward monitoring and control

AIChE Journal ◽  
2021 ◽  
Author(s):  
Carlos A. Duran‐Villalobos ◽  
Olotu Ogonah ◽  
Beatrice Melinek ◽  
Daniel G. Bracewell ◽  
Trevor Hallam ◽  
...  
Keyword(s):  
Protein Synthesis ◽  
Data Analysis ◽  
Statistical Data ◽  
Monitoring And Control ◽  
Statistical Data Analysis ◽  
Multivariate Statistical ◽  
Free Protein ◽  
And Control ◽  
Cell Free Protein Synthesis

Data Analysis in Context-Based Statistical Modeling in Predictive Analytics

2021 ◽  
pp. 96-114
Author(s):  
Selvan C. ◽  
S. R. Balasundaram
Keyword(s):  
Decision Making ◽  
Data Analysis ◽  
Statistical Modeling ◽  
Negative Correlation ◽  
Predictive Analytics ◽  
Mathematical Representation ◽  
Statistical Techniques ◽  
Key Factors ◽  
Dependent Variables ◽  
Future Outcomes

Data analysis is a process of studying, removing non-required data in the view level, and converting to needed patterns for sub decisions to make an aggregated decision. Statistical modeling is the process of applying statistical techniques in data analysis for taking proactive decisions depend requirements. The statistical modeling identifies relationship between variables, and it encompasses inferential statistics for model validation. The focus of the chapter is to analyze statistical modeling techniques in different contexts to understand the mathematical representation of data. The correlation and regression are used for analyzing association between key factors of companies' activities. Especially in business, correlation describes positive and negative correlation variables for analyzing the factors of business for supporting the decision-making process. The key factors are related with independent variables and dependent variables, which create cause and effect models to predict the future outcomes.

scholarly journals Data Analysis of Beach Sands’ Chemical Analysis Using Multivariate Statistical Methods and Heavy Metal Distribution Maps: The Case of Moonlight Beach Sands, Kemer, Antalya, Turkey

Symmetry ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1538 ◽  
Author(s):  
Fusun Yalcin
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Data Analysis ◽  
Chemical Analysis ◽  
Statistical Methods ◽  
Risk Index ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Distribution Maps ◽  
Beach Sands

Multivariate statistical methods are widely used in several disciplines of fundamental sciences. In the present study, the data analysis of the chemical analysis of the sands of Moonlight Beach in the Kemer region was examined using multivariate statistical methods. This study consists of three parts. The multivariate statistical analysis tests were described in the first part, then the pollution indexes were studied in the second part. Finally, the distribution maps of the chemical analyses and pollution indexes were generated using the obtained data. The heavy metals were mostly observed in location K1, while they were sorted as follows based on their concentrations: Mg > Fe > Al > Ti > Sr > Mn > Cr > Ni > Zn > Zr > Cu > Rb. Also, strong positive correlations were found between Si, Fe, Al, K, Ti, P. According to the results of factor analysis, it was found that four factors explained 83.5% of the total variance. On the other hand, the coefficient of determination (R2) was calculated as 63.6% in the regression model. Each unit increase in the value of Ti leads to an increase of 0.022 units in the value of Si. Potential Ecological Risk Index analysis results (RI < 150) revealed that the study area had no risk. However, the locations around Moonlight Beach are under risk in terms of Enrichment Factor and Contamination Factor values. The index values of heavy metals in the anomaly maps and their densities were found to be successful; and higher densities were observed based on heavy metal anomalies.

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