Study Unit 6 Flashcards
relevant range
range from highest to smallest measures in set for a linear relationship; can’t project beyond it
High-low method
generate regression line based on highest and lowest observations criticism- values may be abnormal high $600 for 1300 hours low $400 for 800 hours increase $200 for 500 hours variable cost=200/500=$.4 for low month VC= $.4*800=320 400 is total and 320 is VC, 80 is FC y=80+.4x
Perfect direct vs perfect inverse vs strong direct
direct r=1
inverse r= -1
strong direct r=.7
r=0
doesn’t mean there isn’t a relationship; relationship can’t be expressed as a linear equation
coefficient of determination
measure of fit between independent and dependent variables
-proportion of total variation in dependent variable that is accounted for by the indep variable
-closer r^2 is to 1 the more useful the indep var (x) is to predicting y
r^2=.64; 64% of new car sales explained by changes in income
standard error
how well linear equation represents the data
vertical distance between the data points in a scatter diagram and the regression line
-closer the data points are to line, lower the std error
learning curve analysis
reflects increased rate ppl perform tasks as they gain experience
- time req becomes shorter
- expressed as % of reduced time to complete task for each doubling of cumulative production
- 80% l.c. means doubling will reduce cumulative avg unti completion time by 20%
expected value
used by DM that is risk neutral
associating dollar amount w/ each possible outcome of probability distribution; outcome yielding the highest expected value is the optimal alternative
-decision alt is under mgr control
-state of nature is future event whose outcome mgr predicts
-payoff is financial result of comb of mgr decision and actual state of nature
calculated by multiplying probability of outcome by payoff and summing products
criticism- repetitive trials, decision involve 1 event
sensitivity analysis
how sensitive expected value calculations are to the accuracy of the initial estimates
- useful to determine if should spend adtl resources
- used in cap budgeting, small changes of interest rates or payoff amnts can make difference in profitability
simulation analysis
refinement of std probability theory
computer generates examples of results based on assumptions
-costly
monte carlo technique
simulation to generate indiv values for a random variable
perf of quant model under uncertainty investigated by random selection of values for variables in model & calculating the soln
Delphi technique
opinions from experts, summarize opinions, feeds summaries back to experst w/o revealing participants
-repeat until opinions converge to optimal solution
Time series analysis
trend analysis
process of projecting future trends based on past experience
regression model w/ time as independent variable