scholarly journals Computational models for anti-air and antisubmarine warfare simulation

2013 ◽  
Vol 6 (12) ◽  
pp. 29
Author(s):  
Gustavo Pérez Valdés ◽  
Stefany Marrugo Llorente ◽  
José Gómez Torres
Keyword(s):  
Statistical Analysis ◽  
Design Process ◽  
Computational Models ◽  
Analysis Tool ◽  
Simulation Tool ◽  
Discrete Events ◽  
Simulation Process ◽  
Modeling Process ◽  
Statistical Analysis Tool ◽  
Antisubmarine Warfare

This paper describes the generation and simulation process of computational models oriented to the analysis of the operational situations (OPSIT) of anti-air warfare (AAW) and antisubmarine warfare (ASW), with the purpose of evaluating the effectiveness of different combinations of threats, weapons, and sensors of the Colombian Navy. A detailed description of the OPSITs modeling process is presented by using the selected discrete events simulation tool. The experiments design process and the statistical analysis of the results is also described, using a statistical analysis tool. All this to provide the Colombian Navy with a tool it can use to evaluate the systems that could be part of future units.

Setting Up and Running a Q-Methodology Study in an Online Survey Research Suite

2022 ◽  
pp. 417-451
Author(s):  
Shalin Hai-Jew
Keyword(s):  
Statistical Analysis ◽  
Survey Research ◽  
Quantitative Data ◽  
Q Methodology ◽  
Online Survey ◽  
Analysis Tool ◽  
Q Method ◽  
Statistical Analysis Tool ◽  
Q Sort ◽  
Basic Statistical Analysis

The q-method, as a graphic (visual) elicitation, has existed since the mid-1930s. Setting up a q-method, with q-sort capabilities, in an online survey platform, extends the reach of this method, even as data has to be processed in a quantitative data analytics suite. This chapter describes the setting up of a visual q-sort and the related debriefing on the Qualtrics Research Suite. The available data may be extracted and analyzed in a basic statistical analysis tool for factors and preference clusters.

Identification of critical brand community variables and constructs using importance-performance analysis and neural networks

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Matti Haverila ◽  
Kai Christian Haverila ◽  
Caitlin McLaughlin
Keyword(s):  
Neural Networks ◽  
Statistical Analysis ◽  
Online Survey ◽  
Customer Engagement ◽  
Analysis Tool ◽  
Brand Community ◽  
Content Type ◽  
Target Construct ◽  
Statistical Analysis Tool ◽  
And Performance

Purpose This paper aims to use a unique statistical analysis tool to examine the importance and performance of critical brand community constructs and indicators to make concrete recommendations for brand community managers going forward. Design/methodology/approach An online survey was used to gather 501 responses from North American members of the Qualtrics panel. The data was analyzed with partial least squares (PLS) modeling software SmartPLS and neural networks available in statistical software JMP by SAS. Findings Using the brand community motives by Madupy and Cooley (2010), the results of this paper indicated that there was significant room for improvement in customer engagement. Based on further analysis, entertainment and identification with the brand community were the most important constructs in driving community engagement so that the identification construct received a “do better” ruling meaning that the improvement of the indentification construct score would enhance significantly the score of the target construct engagement score. Originality/value For brand community managers, it is important to know the true importance of the critical brand community constructs and indicators, along with an assessment of current performance. This helps to increase satisfaction and relationship quality among brand community members. The current study uses unique statistical analysis tools to make such concrete recommendations.

scholarly journals Pengaruh Beban Kerja terhadap Kinerja Karyawan melalui Burnout Syndrome Pada PT. Perkebunan Nusantara X Pabrik Gula Tjoekir

2021 ◽  
Vol 9 (1) ◽  
pp. 355
Author(s):  
Ayuk Rahmadyah
Keyword(s):  
Statistical Analysis ◽  
Employee Performance ◽  
Partial Least Square ◽  
Least Square ◽  
Burnout Syndrome ◽  
Analysis Tool ◽  
Software Application ◽  
Study Results ◽  
Statistical Analysis Tool ◽  
Permanent Employees

This study aims to determine and analyze the effect of mediation variable burnout syndrome between workload on employee performance in PT. Perkebunan Nusantara X Pabrik Gula Tjoekir. This research is a type of research with a quantitative approach, with a population of permanent employees in PT. Perkebunan Nusantara X Pabrik Gula Tjoekir and the technique sampling with a sample saturated with a sample of 89 employees. The statistical analysis used in this study is Partial Least Square (PLS) analysis techniques and with software SmartPLS3. The statistical analysis tool in this study using the Partial Least Square (PLS) whit the software application SmartPLS3. The study results explained that workload has a positive and significant effect on employee performance, the workload has a positive and significant effect on burnout syndrome, burnout syndrome has a negative and significant effect on employee performance, and workload has no significant effect on employee performance through burnout syndrome. This study implies that if the company wants to improve employee performance, it must maintain environmental conditions, provide a portion of the work according to competence, control employee performance, and periodic job evaluation.

scholarly journals Determinan harga saham sektor properti dan real estat di bursa efek indonesia

2017 ◽  
Vol 21 (2) ◽  
Author(s):  
Nuryasman Nuryasman ◽  
Yessica Yessica
Keyword(s):  
Regression Analysis ◽  
Exchange Rate ◽  
Statistical Analysis ◽  
Interest Rate ◽  
Stock Price ◽  
Sampling Method ◽  
Inflation Rate ◽  
Analysis Tool ◽  
Panel Regression ◽  
Statistical Analysis Tool

This study aims to examine the effect of exchange rate (USD/IDR), inflation and BI Rate to real estate and property stock that listed in BEI from January 2010 – December 2015 with 34 samples. Statistical analysis tool used was Eviews6 with the panel regression analysis and purposive sampling method. This study shows that together the USD / IDR exchange rate, inflation rate and SBI interest rate significantly influence the stock price. While partially only exchange rate USD / IDR and SBI interest rate which have significant effect to stock price.

Setting Up and Running a Q-Methodology Study in an Online Survey Research Suite

2019 ◽  
pp. 103-146
Keyword(s):  
Statistical Analysis ◽  
Survey Research ◽  
Quantitative Data ◽  
Q Methodology ◽  
Online Survey ◽  
Analysis Tool ◽  
Q Method ◽  
Statistical Analysis Tool ◽  
Q Sort ◽  
Basic Statistical Analysis

The q-method, as a graphic (visual) elicitation, has existed since the mid-1930s. Setting up a q-method, with q-sort capabilities, in an online survey platform, extends the reach of this method, even as data has to be processed in a quantitative data analytics suite. This chapter describes the setting up of a visual q-sort and the related debriefing on the Qualtrics Research Suite. The available data may be extracted and analyzed in a basic statistical analysis tool for factors and preference clusters.

The influence of drought on tree growth in Germany – from models to general statements

2015 ◽  
Vol 5 (3) ◽  
pp. 76-83
Author(s):  
Бек ◽  
Volfgang Bek ◽  
Нахтин ◽  
Marko Nakhtin ◽  
Мюллер ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Norway Spruce ◽  
Tree Ring ◽  
Tree Growth ◽  
Climate Scenario ◽  
European Beech ◽  
Decision Makers ◽  
Analysis Tool ◽  
Relative Increment ◽  
Statistical Analysis Tool

The scientific perspective on the climate-growth relationship is usually multivariate and too complex for decision makers, who need simpler statements. We analyse the relationships between the climate and tree growth with the help of 89 tree ring chronologies for Norway spruce, Scots pine and European beech in Germany. The statistical analysis tool CLIMTREG is used to discover climate-growth relationships and to model relative increment deviations caused by the force of climate scenario data.

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