• Proceedings of the Korean Statistical Society Conference
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• 2004.11a
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• pp.307-312
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• 2004

In our fast-moving information and knowledge society, skills and know-how rapidly become outdated. Virtual learning environments play a key role in meeting today's growing demand for customized educational and vocational training and lift-long teaming. The scope of multimedia-based and web-supported education is illustrated by means of an interdisciplinary multimedia project 'New Statistics' funded by the German government. The project output contains more than 70 learning modules covering the complete curriculum of an introductory statistics course. All modules are based on a statistical laboratory and on a multitude of Java applets, animations and case studies. The paper focuses on presenting the statistical laboratory and the applets. These components present the main project pillars and are particularly suitable for international use, independently from the original project framework. This article also demonstrates the application of Java applets and other multimedia developments from the educational world to official statistics for interactive presentation of statistical information.

• Research in Mathematical Education
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• v.26 no.3
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• pp.127-146
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• 2023

Statistical thinking has a broad definition but focuses on the context of regression modelling in the present study. To foster students' statistical thinking within the context, teaching should no longer be seen as transfer of knowledge from teacher to students but as a process of engaging with learning activities in which they develop ownership of knowledge. This study aims at collaborative learning contexts; students were divided into small groups in order to increase opportunities for peer collaboration. Each group of students was asked to do a regression project after class. Through doing the project, they learnt to organize and connect previously accrued piecemeal statistical knowledge in an integrated manner. They could also clarify misunderstandings and solve problems through verbal exchanges among themselves. They gave a clear and lucid account of the model they had built and showed collaborative interactions when presenting their projects in front of class. A survey was conducted to solicit their feedback on how peer collaboration would facilitate learning of statistics. Almost all students found their interaction with their peers productive; they focused on the development of statistical thinking with concerted effort.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.614-620
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• 2011

Delays in completing construction projects have significant financial and social impact to all parties involved in the construction process and in particular in developing countries. This is very evident in most construction projects in Libya and in both public and private sectors. The research study was initiated by Libyan Government and the main aim of the project is to develop a new strategy in reducing the impact of delay factors. In order to achieve this, a number of objectives have been set-to conduct a comprehensive literature survey, to conduct a comparative study of the delay factors in project completion in both Libya and UK using semi structured questionnaire and finally, to identify and analyse the causes of delay and ranked them using frequency of occurrence and severity. The critical causes of delay for construction projects were quite different between Libya and UK. For the former, the most critical causes of delay in Libyan construction industry were low skills of manpower, changes in the scope of the project, slowness in giving instruction and poor qualification of consultant, while for the latter they were financial problems, bad weather conditions on the job site and change in the scope of project. Statistical experiments including Paired Samples T-Test, was run to test the significance of the survey data in both countries Libya and UK. The statistical results confirmed the collected data from the survey were significant.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.3
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• pp.137-149
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• 2005

This study proposes a framework enhancing the accuracy of estimation for project duration by combining linear Bayesian updating scheme with the learning curve effect. Activities in a particular project might share resources in various forms and might be affected by risk factors such as weather Statistical dependence stemming from such resource or risk sharing might help us learn about the duration of upcoming activities in the Bayesian model. We illustrate, using a Monte Carlo simulation, that for partially repetitive projects a higher degree of statistical dependence among activity duration results in more variation in estimating the project duration in total, although more accurate forecasting Is achievable for the duration of an individual activity.

• Korean Journal of Construction Engineering and Management
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• v.6 no.1 s.23
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• pp.73-79
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• 2005

This paper, introduces a Stochastic Project Scheduling Simulation system (SPSS III) developed by the author to predict a project completion probability in a certain time. The system integrates deterministic CPM, probabilistic PERT, and stochastic Discrete Event Simulation (DES) scheduling methods into one system. It implements automated statistical analysis methods for computing the minimum number of simulation runs, the significance of the difference between independent simulations, and the confidence interval for the mean project duration as well as sensitivity analysis method in What-if analyzer component. The SPSS 111 gives the several benefits to researchers in that it (1) complements PERT and Monte Carlo simulation by using stochastic activity durations via a web based JAVA simulation over the Internet, (2) provides a way to model a project network having different probability distribution functions, (3) implements statistical analyses method which enable to produce a reliable prediction of the probability of completing a project in a specified time, and (4) allows researchers to compare the outcome of CPM, PERT and DES under different variability or skewness in the activity duration data.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.57-68
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• 2021

Successfully adapting to digital and customer-oriented transformation, the concept of lean manufacturing professes the philosophy of creating greater benefit while minimizing losses. These losses are operations that do not add value in the production process to ensure the efficiency, flexibility, and profitability of projects. In the context of broad automation and digitalization of all sectors of the economy, mechanisms for combining automation technologies and lean production are becoming available. Moreover, when it comes to the efficient use of financial, human, or material resources, it is clear that the use of Industry 4.0 technologies can be an effective tool for achieving the goals of lean production, as many of them pursue the same goal. In this context, this article aims to study the effectiveness of the implementation of project management concepts at the global level and identify the main factors influencing its effectiveness to ensure the achievement of lean production through LEAN technologies and Industry 4.0 technologies. To achieve this goal, several statistical indicators were selected and several statistical methods of analysis were used: pairwise correlation, regression analysis, methods of comparison, synthesis, and generalization. Statistical analysis was conducted according to a survey conducted by the Project Management Institute (PMI) in 2020. An economic-mathematical model of dependence of project effectiveness in different regions of the world on the level of implementation of project management approaches is built, which shows that the increase in project effectiveness by 85% is due to financial losses, technical training, and consumer orientation. These results allow project managers to develop appropriate strategies to improve project management approaches at all levels. It is established that LEAN technologies and technologies of Industry 4.0 have several tools that have a positive effect on minimizing losses following the concept of lean production. Besides, given that the technology of Industry 4.0 is focused on the automation of Lean Production technology, a mechanism for the introduction of lean production using these technologies and methods.

• Education of Primary School Mathematics
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• v.12 no.1
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• pp.31-38
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• 2009

This paper aims to develop a program which cultivates statistical ability for elementary students. For this purpose, I examined the relationship between mathematical thinking and statistical thinking. I developed statistical programs including classification, discussion of data, generating statistical problem and project program. As result, this study suggests implications for further elementary statistical education.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.50-56
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• 2022

Change Orders generally impact cost and schedule performance of highway projects. However, highway projects that do not have any change orders also face cost growth and schedule delays. This study seeks to determine the cost and schedule performance of Texas DOT projects by collecting project data for 120 highway projects completed between 2016 to 2020. For the study, we selected project data that has zero or negative change orders which were then grouped and analyzed based on their Project Types i.e., maintenance works; structural works; restoration and rehabilitation works; and safety works. The study found that performance of Maintenance and Safety type projects had less cost and schedule growth among the data analyzed. Statistical tests also found that even though the projects have no change orders, Rehabilitation and Restoration type projects experienced significant schedule growth compared to others. However, the data did not show any significant cost and schedule growth for the projects when statistical tests were performed on overall data. The study concluded that highway projects are experiencing schedule growth even though the projects had no change orders. Results from the study can help planners, engineers, and administrators to gain better insight on how different types of highway projects are performing in terms of cost and schedule and eventually derive appropriate solutions to minimize cost and schedule growth in such projects.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.935-940
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• 2005

This paper presents the results of a statistical analysis using historical data of cost contingency. As a result, a model that predicts and estimates an accurate cost contingency value using the least squares estimation method was developed. Data such as original contract amounts, estimated contingency amounts set by maximum funding limits, and actual contingency amounts, were collected and used for model development. The more effective prediction model was selected from the two developed models based on its prediction capability. The model would help guide project managers making financial decisions when the determination of the cost contingency amounts for multiple projects is necessary.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.276-287
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• 2021

Project Management Information System (PMIS) is a special purpose information system that is created to provide useful information for project managers and participants to make effective and efficient decision making during projects. The use of PMIS is increasing in project based industries such as construction, defense, manufacturing, software development, telecommunication, etc. It is generally known that PMIS helps to improve the quality of decision making in project management, and consequently improves the project management performance. However, it is unclear what are the difference of PMIS impacts between industries, and still need to be studied further. The purpose of this study is to compare the impact of PMIS on project management performance between industries. We assume that the effects of PMIS will be different depending on the industry types. Five hypotheses are established and tested by using statistical methods. Data were collected by using a survey questionnaire from those people who had experience of using PMIS in various project related industries such as construction, defense, manufacturing, software development and telecommunication. The survey questionnaire consists of 5 point scale items and were distributed through e-mails and google drive network. A total of 181 responses were collected, and 137 were used for analysis after excluding those responses with missing items. Statistical techniques such as factor analysis and multiple regression are used to analyze the data. Summarizing the results, it is found that the impacts of PMIS quality on the PM performance are different depending on the industry types where PMIS is used. System quality seems to be more important for improving the PM performance in construction industry while information quality seems more important for manufacturing industry. As for the ICT and R&D industries, PMIS seems to have relatively lesser impact compared to construction and manufacturing industries.