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MGS 3100 notes

by: Vraj Patel

MGS 3100 notes MGS 3100

Vraj Patel
GPA 3.6

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Business Analysis
Study Guide
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Popular in Business Analysis

Popular in Managerial Science

This 2 page Study Guide was uploaded by Vraj Patel on Thursday September 29, 2016. The Study Guide belongs to MGS 3100 at Georgia State University taught by Roth in Fall 2016. Since its upload, it has received 3 views. For similar materials see Business Analysis in Managerial Science at Georgia State University.

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Date Created: 09/29/16
MGS 3100 Chapter 1 Ø Ways of classify models: o Qualitative, quantitative models o Physical, analog and symbolic models o Deterministic and probabilistic o Inductive and ductive models Ø Quantitative o Data refers to measurable obersavations tools include: odometer,measuring tape , time, thermostat, beaker. o Balance sheet o Mathematical system modeling Ø Qualitative o Data refers to observation using five senses o Such as management expertise labor analysis Ø Models can classify as physical analog and symbolic o Analog behaves like system but looks different: example, time is an abstract representation. o Symbolic models are more tangible like flow in the water in the pipe. Only an approximation of what it represents, such as financial statements o Deterministic are predicable: every time you run you get the same results § Such as the sun will rise tomorrow o Probabilistic include elements of randomness § Models should be probabilistic because most things are uncertain § Most models include both, Example: gps is deterministic with a set route but the driver and the roads are probabilistic Ø Induction o Model: Observing something in the world, find common patterns, use that to build a model Ø Deduction o Reality: Once you have a model, known rule: you can now apply it too the world thus deducing something new. Ø These are linked together by observing and then creating a model and then applying it to the real world Ø Revenue: Total amount of money coming in Ø Expenses: costs: o Fixed: will not change based on anything o variable: will change with the unit sold o overhead: all ongoing business expenses such as, expenses like cooperate office. It’s a ongoing constant fee. Advertising, insurance. o Sunk: Independent of any event that may occur in the feature, you have already paid for them so you can’t let them determine the future. Ø What variable to include in your model o Relevant or irrelevant o Variables have to be relevant to be included in the model Ø A model is like the real thing, but it is not. Ø The sundial is a mathematic model: records the daily passage of the sun in the sky Chapter 2 Ø Good spread sheet practices o Easy to use and understand o Well organized o Don’t embed numbers in formulas o LABEL Ø Lock a cell $ for F4 Ø If statement, highlight those who are above certain criteria o When typing actual words use “” Ø Vlookup : o Highlight actual number first o Highlight table o Colon number index always 2 o Leave last one empty Chapter 3 Ø Basic profit model o Overview and terms, o Profits are key measure to tell the health of the company Ø Exogenous: input into model o Independent: revenue, cost. Ø Endogenous: output of model o Dependent: Value is change by one of the relationships: Profit Ø Break even: revenue equals expenses or profit equals 0 Ø Contribution Margin (cm per unit): cm= price/unit –variable costs/ unit Ø Cross over points: Point in the middle of two options from one being more profitable to the other. o How to calculate: Profit one equation = Profit two equation o Ø Special cases: Sometime you don’t always sell how much you make , or you don’t make enough and demand is still high Chapter 4 Ø Simulation: It is the imitation of the operation of a real world process or system over time o Model must be developed with key features o Simulation are used when things are uncertain o Why use? Less expensive, compress time, and safety Ø What do you need to know to create a simulation? o Depends on what we are simulating Ø Discrete Variables: can only take certain values Ø Continuous: can take values between two values Ø Likeyhood of event occurring o Probabilities are needed to run a simulation o Flipping a coin is a discrete variable 50% probability of each


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