Moment generating function to calculate the mean and variance

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The discussion revolves around the confusion regarding the wording of questions related to moment generating functions, specifically the implications of the parameter λ. The user seeks clarification on why the questions specify ranges for λ, such as "0 < λ < 1" and "λ > 0," and how this affects the calculation of mean and variance. It is explained that these constraints ensure valid probability values, avoiding negative probabilities or those exceeding one. The user also confirms their understanding of the moment generating function and the geometric series involved in the calculations. Ultimately, the discussion highlights the importance of parameter constraints in statistical calculations.
snesnerd
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I attached a pdf. The questions are not really what is stumping me. Its the wording of the question I don't understand. When it says, "Assume that 0 < λ < 1. Note that your answers will be in terms of the constant λ." and "Assume that λ > 0. Note that your answers will be in terms of the constant λ." I don't understand what they want me to really do here when it says that. To show I know how to do the questions before anyone helps me, I will briefly explain the solution to each one.

1a. Multiply by e^tx. Its a geometric series so just use the formula for the geometric series.
1b. To find the mean of X take the derivative of the answer to 1a.
1c. To find the variance of X take the second derivative minus first derivative squared.

2a. Multiply by e^tx then integrate from 0 to infinity.
2b. Same idea as 1b.
2c. Same idea as 1c.

 

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snesnerd said:
I attached a pdf. The questions are not really what is stumping me. Its the wording of the question I don't understand. When it says, "Assume that 0 < λ < 1. Note that your answers will be in terms of the constant λ." and "Assume that λ > 0. Note that your answers will be in terms of the constant λ." I don't understand what they want me to really do here when it says that. To show I know how to do the questions before anyone helps me, I will briefly explain the solution to each one.

1a. Multiply by e^tx. Its a geometric series so just use the formula for the geometric series.
1b. To find the mean of X take the derivative of the answer to 1a.
1c. To find the variance of X take the second derivative minus first derivative squared.

2a. Multiply by e^tx then integrate from 0 to infinity.
2b. Same idea as 1b.
2c. Same idea as 1c.

I do not understand what your difficulty is. You have a distribution; it contains a parameter λ. You do not know the value of λ, but you are told it is between 0 and 1. The question asks you to determine the mean and variance. Of course there will be a λ in the answers, since there is a λ in the input. What is unclear about that?

RGV
 
1a) asks you to find the moment generating function of the distribution (1- \lambda)\lambda^x and you are told "1a. Multiply by e^tx." Okay, the moment generating function is, by definition, the expected value of e^{tx} and the expected value of any function is the sum of function values for each x times the probabilty of that particular x. Here, that would be
\sum_{x=0}^\infty (1- \lambda)\lambda^xe^{tx}= (1- \lambda)\sum_{n=0}^\infty (\lambda e^t)^x
which is, as they say, a geometric series with common multiple \lambda e^t. Use the fact that the sum of a geometric series is given by
\sum_{x=0}^\infty r^x= \frac{1}{1- r}.
 
Thanks everyone. I don't know why I was letting it confuse me, but it seems clarified now. One last question though. What purpose did it serve to tell me that in the first question, 0 < λ < 1, and in the second question λ > 0? Couldnt they of just said that λ is just a constant?
 
snesnerd said:
Thanks everyone. I don't know why I was letting it confuse me, but it seems clarified now. One last question though. What purpose did it serve to tell me that in the first question, 0 < λ < 1, and in the second question λ > 0? Couldnt they of just said that λ is just a constant?

No. In question 1 you need lambda between 0 and 1 in order to avoid negative probabilities or probabilities > 1. Question 2 is completely different; there you could have ANY positive value for lambda (but, again, a negative value would give nonsense such as negative probability, etc).

RGV
 
Gotcha. Thanks. Last question. The sum of the geometric series in the first question is

(1 - λ)/(1 - λe^t) right?

Since the first term is (1 - λ) and the common ratio is λe^t.
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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