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MOOC
Operations management deals with operational planning and control issues, and is needed in all sectors of the society. One of the challenges to operations manager is how to make use of the available resources in the best way for meeting a certain objective. Quantitative approaches are inevitably needed in tackling many of such problems. Operations Research (OR) deals with problem formulation and application of analytical methods to assist in decision-making of operational problems in planning and control. The techniques of OR are useful quantitative tools to assist operations managers, and has a wide applicability in engineering, manufacturing, construction, financial and various service sectors. Operations Research is an applied mathematics subject and is also a course in many engineering and management programmes. This course is designed for both students learning OR and learners who are practitioners in their respective professionals. The mathematical procedures for the OR techniques are introduced in details in the examples provided in the course. This helps learners to master the methodology and the techniques and apply them to achieve their goals through active learning. This course introduces two prominent OR techniques and their extended topics. The Simplex Method for Linear Programming (LP) has been considered one of the top 10 algorithms of the 20th century. LP is an optimization technique for solving problems such as finding the optimal product mix, production plan, and shipment allocation, in order to maximize the profir or minimize the cost. The Critical Path Method (CPM) is a popular technique employed by project managers in scheduling project activities. Some extended topics of CPM are also introduced to deal with certain special situations in project management. In reality, many systems operate under stochastic environment and the operational problems cannot be solved by the known analytical methods. To this end, the simulation approach is introduced in the last chapter of this course. Simulation is a powerful technique for tackling OR problems under such situations.
- Subjects:
- Statistics and Research Methods
- Keywords:
- Operations research
- Resource Type:
- MOOC
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MOOC
This course teaches the R programming language in the context of statistical data and statistical analysis in the life sciences. We will learn the basics of statistical inference in order to understand and compute p-values and confidence intervals, all while analyzing data with R code. We provide R programming examples in a way that will help make the connection between concepts and implementation. Problem sets requiring R programming will be used to test understanding and ability to implement basic data analyses. We will use visualization techniques to explore new data sets and determine the most appropriate approach. We will describe robust statistical techniques as alternatives when data do not fit assumptions required by the standard approaches. By using R scripts to analyze data, you will learn the basics of conducting reproducible research. Given the diversity in educational background of our students we have divided the course materials into seven parts. You can take the entire series or individual courses that interest you. If you are a statistician you should consider skipping the first two or three courses, similarly, if you are biologists you should consider skipping some of the introductory biology lectures. Note that the statistics and programming aspects of the class ramp up in difficulty relatively quickly across the first three courses. We start with simple calculations and descriptive statistics. By the third course will be teaching advanced statistical concepts such as hierarchical models and by the fourth advanced software engineering skills, such as parallel computing and reproducible research concepts.
- Subjects:
- Statistics and Research Methods and Mathematics and Statistics
- Keywords:
- Life sciences -- Statistical methods Mathematical statistics -- Data processing R (Computer program language)
- Resource Type:
- MOOC