Individual Simulation Paper RES 342 May 6‚ 2012 Intro The body of the simulation was about the soil in Ralph’s fields and what was making Ralph’s crops fail every year. Through this simulation I chose to use the two-way ANOVA and nonparametric test to help me evaluate the effects of the diverse factors on two response variables‚ which were productivity and client satisfaction. My findings helped me to narrow down and identify the areas that needed most improvement. Three Lessons Learned
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and controlling of the project costs. The Project Manager and Project Sponsor will review the following earned value measurements: 1. Schedule Variance (SV) 2. Cost Variance (CV) 3. Schedule Performance Index (SPI) 4. Cost Performance Index (CPI) 5. To Complete Cost Performance Index (TCPI) 6. Estimated Actual Cost at Completion (EAC) Schedule Variance (SV) is a measurement of the schedule performance for a project‚ and is calculated by subtracting the Planned Value (PV) from Earned Value (EV)
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[pic] ASSIGNMENT FRONT SHEET Course Title: M921- Managing Service Operations in the Evolving Business Environment Faculty: A. Gervaix Student Class: MBA - group B Assessment Title: Benihana Simulation Analysis Due Date: September 21‚ 2012 Due Time: Midnight Word Count: Statement of Authorship I certify that this assignment is my own work and contains no material which has been accepted for the award of any degree or diploma in any institute‚ college or university
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Introduction: The simulation developed a knowledge of pricing by managing a rental car operation in Florida and developing a pricing strategy keeping the competitor in mind. The simulation involved three regions Oriando‚ Tampa and Miami‚ which vary in market dynamics‚ size and customers. The focus is competition between two car rental companies and the simulation last up to 12 months. I had to set weekday and weekend price for the entire three regions for each month and make a fleet decision. Description:
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class and religious affiliation. The results and an excerpt from the results section of this fictional study follow. Observed (and Expected) Frequencies (NOTE: Expected frequencies are in parentheses.) Excerpt: "Based on a chi-square test for independence‚ the working class differed from the middle class in the distribution of religious identification‚ χ2(4‚ N = 100) = 11.73‚ p < .05." Of the total population‚ the percentage of agnostics‚ atheists‚ and others wasAnswer | | | |
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Benihana Simulation Analysis Harvard Business Publishing has created a computer simulation to replicate the operations management decisions facing Benihana. Benihana is a teppanyaki style restaurant franchise that focuses on bringing a theatrical dinning experience to its patrons. The layout of the restaurant consists of two seating areas: the bar and the dining area. The goal of this simulation is to maximize utilization‚ throughput time and the nightly profit using different batching‚ bar sizing
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consider the system complexity that in many cases is hard to capture. If the system’s simulation is appropriate‚ we can then provide practical feedback to real systems‚ time compression or expansion‚ higher control‚ and lower costs. Thus‚ one question emerges: why is it necessary to simulate traffic (road network)? In order to give an answer to this query we have to keep in mind the system’s complexity. Traffic simulation is necessary because this kind of application domain is inherently complex‚ usually
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Global Supply Chain Management Simulation Debrief Slides ©© Enspire Enspire Learning Learning and and Harvard Harvard Business Business School School (revised Dec 2010) 1 Board Members’ Objectives Member Objective Betty Forecasting: choice of options (consensus vs. mean) Doug Forecasting: choice of options (role of risk) Yvonne Stocking Levels: Weighing the costs of over/understocking Meryl Production flexibility: accurate response/ sourcing strategy (focus on flexibility) Paul Production
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Chapter 16 Completely Randomized Factorial ANOVA This tutorial describes the procedures for computing F tests for a completely randomized factorial analysis of variance design. The reading-speed data in Table 16.4-2 of the textbook are used to illustrate the procedures. 1. Enter a description of the data in the SPSS Data Editor following steps 1–4 described in the Frequency Distribution tutorial for Chapter 2. Use rows 1‚ 2‚ and 3 of the SPSS Data Editor Variable View window to describe
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A 4(amount of alcohol: 0‚ 2‚ 4‚ 6 pints) X 2(type of lighting: dim‚ bright) within subjects Factorial ANOVA was conducted on attactiveness scores of chosen mate. Mauchly’s test indicated that the assumption of sphericity had been assumed for the main effect of alcohol amount‚ χ²(5) = 4.70‚ p > .05 and alcohol amount and lighting type interaction effect‚ χ²(5) = 2.58‚ p > .05. There was a significant main effect of type of lighting on attractiveness of chosen mate‚ F (1‚ 25) = 23.42‚ p
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