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Quiz

MGMT 1050 Quiz: stats book summary notes pt2
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4 Pages
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Fall 2014

Department
Management
Course Code
MGMT 1050
Professor
Olga Kraminer
Study Guide
Quiz

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We presented an introduction to game theory by describing how to solve two-
person, zero-sum games. In these games, the two players end up with the sum of
the gain (loss) to one player and the loss (gain) to the other player always equal
to zero. We described the steps that can be used to determine whether a two-
person, zero-sum game results in an optimal pure strategy. If a pure strategy is
optimal, a saddle point determines the value of the game. If an optimal pure
strategy does not exist for a two-person, zero-sum 2 2 game, we showed how to
identify an optimal mixed strategy. With a mixed strategy, each player uses
probability to select a strategy for each play of the game. We showed how
dominance could be used to reduce the size of mixed strategy games. If the
elimination of dominated strategies can reduce a larger game to a 2 2 game, an
algebraic solution procedure can be used to find a solution. If the game cannot be
reduced to a 2 2 game, a linear programming model is needed to determine the
optimal mixed strategy solution.
Chapter 6 Time Series Analysis and Forecasting
an introduction to basic methods of time series analysis and forecasting. We first
showed that the underlying pattern in the time series can often be identified by
constructing a time series plot. Several types of data patterns can be
distinguished, including a horizontal pattern, a trend pattern, and a seasonal
pattern. The forecasting methods we have discussed are based on which of these
patterns are present in the time series.
We also discussed that the accuracy of the method is an important factor in
determining which forecasting method to use. We considered three measures of
forecast accuracy: mean absolute error (MAE), mean squared error (MSE), and
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Description
We presented an introduction to game theory by describing how to solve two-person, zero-sum games. In these games, the two players end up with the sum of the gain (loss) to one player and the loss (gain) to the other player always equal to zero. We described the steps that can be used to determine whether a two-person, zero-sum game results in an optimal pure strategy. If a pure strategy is optimal, a saddle point determines the value of the game. If an optimal pure strategy does not exist for a two-person, zero-sum 2 2 game, we showed how to identify an optimal mixed strategy. With a mixed strategy, each player uses probability to select a strategy for each play of the game. We showed how dominance could be used to reduce the size of mixed strategy games. If the elimination of dominated strategies can reduce a larger game to a 2 2 game, an algebraic solution procedure can be used to find a solution. If the game cannot be reduced to a 2 2 game, a linear programming model is needed to determine the optimal mixed strategy solution. Chapter 6 Time Series Analysis and Forecasting an introduction to basic methods of time series analysis and forecasting. We first showed that the underlying pattern in the time series can often be identified by constructing a time series plot. Several types of data patterns can be distinguished, including a horizontal pattern, a trend pattern, and a seasonal pattern. The forecasting methods we have discussed are based on which of these patterns are present in the time series. We also discussed that the accuracy of the method is an important factor in determining which forecasting method to use. We considered three measures of forecast accuracy: mean absolute error (MAE), mean squared error (MSE), and
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