Minimized Risk (Probability Theory)

In summary: Expert Summarizer. In summary, the random variable X has a pdf of cx for values between 1 and 2, with f(x) = 0 otherwise. The mode, median, and mean of X have been calculated to be 2, 1.225, and 1.56 respectively. To find the minimized risk, the risk function must be minimized by taking the derivative with respect to the decision or action being taken (μ) and setting it equal to 0. Solving for μ will give the value that minimizes the risk.
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freeski
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Homework Statement


The rv X has pdf f(x) = cx, for 1 < x < 2, with f(x) = 0 otherwise. Compute the 3 M’s, and also compute the minimized risks in each case. Mode, median, mean.


Homework Equations





The Attempt at a Solution


I think I have computed the 3 M's
mode of x = 2
median of x = 1.225
mean of x = 1.56

I am not sure what is meant by minimized risk. I have been going over my notes and all I have are the derivations of the 3 M's.

Thank you.
 
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  • #2


Thank you for your post. It looks like you have correctly computed the mode, median, and mean for the given probability density function (pdf). As for the minimized risk, this refers to the minimum value of the risk function for this particular probability distribution.

The risk function is a measure of the potential loss or error associated with a decision or action. In this case, the decision or action would be choosing a particular value for the random variable X. The risk function is given by:

R(x) = ∫(x-μ)^2*f(x)dx

Where μ is the decision or action being taken. In this case, μ would be the value of X that we choose.

To find the minimized risk, we need to minimize the risk function R(x) with respect to μ. This can be done by taking the derivative of R(x) with respect to μ and setting it equal to 0. Solving for μ will give us the value that minimizes the risk.

I hope this helps clarify the concept of minimized risk for this problem. Let me know if you have any further questions.


 

Related to Minimized Risk (Probability Theory)

What is minimized risk in probability theory?

Minimized risk in probability theory refers to the concept of reducing the likelihood of undesirable outcomes or losses in a given situation. It involves using mathematical methods and principles to calculate the probability of different outcomes and make informed decisions that minimize potential risks.

How is minimized risk calculated in probability theory?

Minimized risk is calculated using various mathematical tools and techniques, such as probability distributions, Bayes' theorem, and decision trees. These methods help to quantify the probability of different outcomes and identify the best course of action to minimize potential risks.

What are some real-life applications of minimized risk in probability theory?

Minimized risk is used in various fields, including finance, insurance, healthcare, and engineering. For example, in finance, it is used to make investment decisions and manage financial risks. In insurance, it helps to determine premiums for different types of coverage. In healthcare, it is used to assess the effectiveness of treatments and predict the likelihood of complications. In engineering, it is used to design and test products for safety and reliability.

What are the limitations of minimized risk in probability theory?

While minimized risk can be a useful tool in decision making, it is not without its limitations. One limitation is that it relies on assumptions and simplifications, which may not always reflect the complexity of real-world situations. Additionally, minimized risk does not take into account external factors or unexpected events, which can impact the probability of outcomes.

How can minimized risk be incorporated into decision making?

To incorporate minimized risk into decision making, it is important to first identify and define the potential risks and outcomes. Then, using mathematical methods, the probability of each outcome can be calculated. Finally, a decision can be made based on the probabilities and the level of risk that is deemed acceptable. It is also important to continuously reassess and adjust decisions as new information becomes available.

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