On May 10, A decides to use the mower for recreation. The mower is not designed to cut anything thicker than grass; while trying to mow the brush, A hears several loud and unusual noises coming from underneath the mower. On June 15, B asks A to return the mower, and A does so. Upon returning the mower, A states that he forgot to bring it back until B asked about it.

Index to Module One Notes 1. Introduction to Quantitative Analysis 1. Structuring the Decision Problem 1. Decision Making without Probabilities 1. Decision Making with Probabilities 1. The Value of Information 1. Introduction to Quantitative Analysis This is a course about the use of quantitative methods to assist in decision making.

The subject matter makes up the discipline known as decision sciences, or you might hear it called management science or operations research. We will be covering a number of descriptive and prescriptive mathematical models that have proven useful to managers, generally since World War II, although some of the models date back to the early 's.

Mathematical models are simply representations of reality that provide a framework for a scientific approach to the study of managerial problems.

Models also help us gain insight into relationships such as the relationship that exists between an objective and a constraint. For example, we will be using linear programming prescriptive models to represent the relationship between a profit maximization objective and one or more limited resource constraints.

Suppose a company manufactures two products, X and Y. The mathematical expression for maximizing profit is simply: That's right, make an infinite number of Y's!

But the real world presents constraints to every operation. Suppose that it takes 4 hours of labor to assemble an X, and 20 hours of labor to assemble each Y. If there are hours of labor available in the next production period, we can expand the problem as follows: If we wanted to continue our strategy of making all Y's and no X's, we see that we could make 7 Y's by using all of the hours of labor.

We could make all X's and no Y's. To be sure we have the best or optimal solution that maximizes our profit criteria, we would need the mathematical model to check the profit contribution of all other product mix combinations. Obviously, this is a small problem that can be solved by observation.

Imagine what the linear program problem formulation looks like for an auto manufacturer which much select between perhaps 10 models of one make of car subject to a multitude of labor, equipment, and market constraints. For these large problems we need a more formal problem solving process.

The scientific approach to the study of managerial problems incorporates a problem solving process. The text presents a seven-step process: Identify and define the problem 2. Determine the set of alternative solutions 3.

Determine the criterion or criteria that will be used to evaluate the alternatives. Evaluate the alternatives using an appropriate quantitative method or model. Choose an alternative 6.

Implement the selected alternative the decision 7. Evaluate the results and determine if a satisfactory solution has been obtained. Decision-making is concerned with the first five steps and will be our focus through this course.

The first three steps are concerned with structuring the problem, and the next two with analysis. When the manager adds qualitative considerations to the selection process, and follows through with implementation and evaluation, the problem solving process is complete.

We will start off the course with descriptive models that describe outcomes for selected alternatives, and in that manner assist the decision-maker in selecting between alternatives.

These models include decision analysis, forecasting, project management, and queuing or waiting line models. For example, I hope you will enjoy the module on queuing or waiting lines simply because most of us probably have "war stories" about waiting in lines some where at some time.

Did you know that there are descriptive models that predict how many customers will be standing in a given line, and for how long, given that we know the customer arrival rate and system service rate inputs? I hope you will also enjoy the forecasting module where simple mathematical techniques are used to discover patterns such as trend and seasonality in our data.

In the forecasting module, we drive home how important it is to measure and report the reliability of a forecast - almost as important as the forecast itself.parties engaged in numerous negotiating sessions, but they were unable to come to an agreement. I) mid-term bargaining, 2) seniority, 3) scheduling and shift bidding, 4) presented any financial data or/or analysis of the Township's finances.

Here is the best resource for homework help with PROC Negotiations at Webster University. Find PROC study guides, notes, and practice tests from PROC Mid Term Exam, SP2, Grading Matrix. 5 pages. Negotiation Case 2_ Joe Tech and Robust Routers - Role 1.

4 pages. negotiation agenda has "significant elements of conflict and considerable potential for integration" Leverage/Power -The benefits the negotiator brings to the table - the more the offer is valued by the other party, the greater the power the negotiator has.

As of 8/22/ Fall Class Schedule Page 1 of 4 Monday, Aug.

20 - Classes Begin The University of Mississippi - School of Law Friday, Nov. 16 - Last day of Law classes Friday, Aug. 31 - Add/Drop/Receive Refund. 12 ANGRY MEN NEGOTATION ANALYSIS 3 Major Case Issues (List) There were about seven Major Case issues that I picked out of the film: 1.

The switchblade seemed to be the damming evidence to some of the Jurors. However, when Juror No. 8 presented his own personal identical bade the uniqueness of the blade was no longer in question.

%(48). KOREAN DEFENSE PROCUREMENT FROM FOREIGN COUNTRIES AND INTERNATIONAL COOPERATION PLAN Seok Kim Mr. Kim is the DCS contracting official of Contract Management.

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