May 21, 2019
BUS 231 - Quantitative Methods/Bus Decisions Credits: 4
Lecture Hours: 4
Lab Hours: 0
Practicum Hours: 0
Work Experience: 0
Course Type: General
An introduction to management research methods used in business. Topics include probability, breakeven analysis, inventory control, statistics and transportation models.
Prerequisite: MAT 073 or intermediate Algebra or 2 years of H.S. algebra or department permission
- Examine how quantitative analysis is used in business.
- Explain the quantitative analysis approach.
- Describe the application of quantitative analysis in a real situation.
- Identify possible problems in using quantitative analysis.
- Illustrate how computers can be used to perform quantitative analysis.
- Analyze how probability concepts relate to analysis.
- Describe the two basic rules of probability and the foundations of probability analysis.
- Distinguish between mutually exclusive and collectively exhaustive events.
- Distinguish between events that are statistically dependent and those that are statistically independent.
- Apply formulas for joint, marginal, and conditional probabilities under both dependent and independent conditions.
- Use Bayes’ theorem to establish posterior probabilities.
- Examine how probability distributions relate to quantitative analysis.
- Illustrate through examples both discreet and continuous random variables.
- Explain the difference between discreet and continuous probability distributions.
- Calculate the expected value and variance of a discreet probability distribution.
- Use the binomial table to solve problems.
- State the 1, 2, and 3 standard deviation areas under the normal curve.
- Use the standard normal probability table.
- Express the meaning of Z in the normal distribution.
- Assess the roles of different families of forecasting techniques and when each should be used.
- Compare theories and applications of moving averages, exponential smoothing and trend time-series models.
- Adjust seasonal data.
- Describe the Delphi-decision making approach.
- Analyze data by computer and interpret the outputs.
- Summarize how businesses apply decision theory to their operations.
- List the steps of the decision-making process.
- Describe the types of decision-making environments.
- Use probability values to make decisions under risk.
- Make decisions under uncertainty, where there is risk but probability values are not known.
- Use computer to solve basic decision-making problems.
- Evaluate how useful decision trees and utility theory are to the decision process.
- Develop accurate and useful decision trees.
- Revise probability estimates using Bayesian analysis.
- Explain the importance and use of utility theory in decision making.
- Utilize computers to solve more complex decision problems.
- Investigate the relationship between variables in a regression model.
- Develop and interpret simple linear regression models.
- Use a multiple regression model to predict.
- Use dummy variables to model categorical data.
- Summarize how inventory control impact organizational operations and profitability.
- Explain the importance of inventory control.
- Use the economic order quantity (EOQ) to determine how much to order.
- Computer the reorder point (ROP) in determining when to order more inventory.
- Determine other inventory control quantities, including the optimal number of orders per year and the number of days between orders.
- Develop strategies which utilize several more complex inventory control models.
- Determine the economic order quantity without the instantaneous receipt assumption.
- Handle inventory problems that allow quantity discounts or have planned shortages.
- Illustrate the use of safety stock with known and unknown stockout costs.
- Perform ABC analysis and joint ordering.
- Relate graphical methods of linear programming to organizational decision making.
- Describe the basic assumptions of linear programming and the properties of linear.
- Formulate small to moderate sized LP problems.
- Solve graphically any LP problem that has only two variables by both the corner point and iso-line methods.
- Relate how simplex method of linear programming compares with graphical methods.
- Convert LP constraints to equalities with slack, surplus, and artificial variables.
- Set up and solve both maximization and minimization LP problems with simplex tableaus.
- Explain the meaning of every number in a simplex tableau.
- Contrast a variety of linear programming applications.
- Describe major applications areas from marketing and production.
- Identify major applications from labor scheduling and finance.
- Structure several linear programming
- Use the northwest corner method and Vogel?s approximation method to find initial solutions to transportation problems.
- Apply the stepping-stone and the MDOI methods to find optimal solutions to transportation problems.
- Solve facility location and other application problems with the transportation model.
- Analyze the differences between linear programming and integer programming.
- Understand and solve the 3 types of integer programming probems.
- Apply the branch and bound method to solve integer programming problems.
- Solve graphically a goal programming problem that has only two variables.
- Assess the importance of queuing theory to an organization?s decision making.
- Describe the trade-off curves for cost of waiting time and cost of service provided.
- Discuss the three parts of a queuing system ? the calling population, the queue itself and the service facility.
- Identify the basic queuing system configurations and assumptions of the common models.
- Analyze by computer a variety of operating characteristics of waiting lines.
- Appraise what role simulation plays in organizational decision making.
- Identify the seven steps of conducting a simulation.
- Explain advantages and disadvantages of simulation.
- Develop random number intervals and use them to generate outcomes.
- Explain how network models relate to project control.
- Describe how to plan, monitor, and control projects with the use of PERT.
- Determine earliest and latest starts, earliest and latest finishes, and slack times for each activity as well as overall project time.
- Find the shortest path through a network using the shortest-route technique.
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