Quantitative analysis (QA) is one of the most important tools in a business curriculum and is used principally in finance, accounting, marketing and operations. QA helps individuals to remain objective when solving complicated problems. Important topics in QA include:
o Decision tree
§ Simplifies decision making based on conditional probability
§ Start a business, etc. look at data or other people’s research to get probability
o Cash flow analysis
§ How much does an investment cost and how much cash will it generate each year?
§ Too much cash? What to do with it?
· Invest/Reinvest in company
· Acquire other businesses (strategically)
· Pay dividends
o NPV – Net Present Value
§ A dollar tomorrow is almost always worth less than a dollar today.
· Depends on the interest rate, inflation rate, opportunity costs
§ To compare different investments, convert them all to today’s dollar.
· Called the discount rate, and it is different for different risks – very subjective.
o IRR – Internal Rate of Return
§ Based on NPV
§ IRR of an investment is the interest rate that makes the sum of the net present value of an income stream equal zero in today’s dollars.
· 7% for 7 years will double your money.
o Normal distribution – Bell Curve
§ Determined by the mean and standard deviation
§ Variance is the distance between sigma and negative sigma, or within one standard deviation.
o Regression analysis and forecasting
§ Linear regression
· Uses historical data to extrapolate the relationship between variables
· Does not hold in the extreme
· Excel data table – completes a table based on a relationship and givens
o Business world does not tend us go as far as academics in finding the right curve for the data, usually just a straight line
· R Square – if too low it doesn’t fit the data too well (70% very high, 30% not bad)
· T Test – how strong X affects Y (-2<T<2 = data is significant)
· Both T and R have to be high for the equation to be a good forecasting tool.
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