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Decision theory in statistics is a series of quantitative methods that are used to make informed decisions. The problem that one can be able to solve would be able to formulate closely based on the initial conditions and choices or set of actions along with the outcomes. Basically, the outcome would be unfamiliar but can be expressed by a set of possible outcomes. Every outcome would be called the utility and would depend on the preferences of the person who is making the decisions. The final decision would follow the logic that is in the theory to increase the expected utility. The main reason to use decision theory is to make the right choices rationally by totally curtailing the routing calculations. Our statisticians would help the students in composing the assignments without crossing the deadlines. They use various methods that would result in finding out the ways through which decisions can be made when they blend with unknown variables along with the framework pertaining to the uncertain decision environment. This will use mathematics, psychology, and statistics to thoroughly evaluate the right procedure to make decisions.
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Two-Person Zero-Sum Games | Games in Normal Form |
Cooperative Games | Stochastic Games |
Nash Bargaining Solution | Multistage Bargaining |
Nash Equilibrium | Many-Player and Population Games |
Games in Extensive Form | Zero Sum Games |
Non-Zero Sum Games | Infinitely Long Games |
Infinitely Long Games | Pooling Games |
Folk Theorems | Mixed Strategies |
Finding Mixed-Strategy Equilibria for Two-Person Games | Extensive Games with Information Sets |
Perfect Recall | Metagames |
Nash Equilibria in Mixed Strategies | Behaviour Strategies |
Repeated Games | Perfect Nash Equilibrium |
Bargaining | Perfect Information and Imperfect Information |
Non-Cooperative Games | Max-Min Strategies |