Finding the p.m.f and mean

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In summary, the conversation discusses two problems related to probability and statistical inference. The first problem (2.5-13) involves finding the probability mass function of x, where x is the number of flips of a fair coin required to observe heads-tails on consecutive flips. The solution involves a pattern in which a head is followed by a tail, and the mean, variance, and standard deviation are also determined. The second problem (2.5-17) involves determining the average number of boxes of tea that must be purchased to obtain a complete collection of 10 different animals randomly placed in the boxes. This problem is related to a geometric distribution, but the question of how to find the probability p remains.
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Homework Statement


2.5-13. Let x equal the number of flips of a fair coin that are required to observe heads-tails on consecutive flips
(a) Find the p.m.f. of x
(b) Determine the values of the mean, variance and standard deviation.

2.5-17. From 1999-2002 Red Rose Tea randomly placed one of 10 English porcelain miniature animals in a 100-bag box of Red Rose Tea, selecting from 10 endangered North American animals.
(a) On the average, how many boxes of tea must be purchased by a customer to obtain a complete collection consisting of 10 different animals.


Homework Equations





The Attempt at a Solution



2.5-13
(a) I wasn't sure what pattern the question was asking for, but judging from the answer given by the book
f(x) = (x-1)/2^x , for x = 2,3,...
I guess it meant a pattern in which a head is followed by a tail. But I don't get where the (x-1) comes from or is it by inspection from each trial.

(b) The mean is given by E(x) = The summation of x(f(x)) where x starts from 2 to infinity.
The problem is how do I sum x(f(x)). It is not a geometric series, is it?

2.5-17
(a)I'm guessing this is a geometric distribution in which X = # of purchases needed to get one success(all ten animals). The question is, how do I figure out the probability p?

In case this helps, the problems are from chapter 2.5 from "Probability and Statistical Inference 7th ed. by Hogg and Tanis".
 
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The answers to 2.5-13 are given in the book, but 2.5-17 does not have an answer given.Thanks for the help!
 

What is a p.m.f?

A p.m.f, or probability mass function, is a function that gives the probability that a discrete random variable is equal to a certain value. It is often represented in the form of a table, graph, or formula.

How do you calculate the p.m.f?

The p.m.f is calculated by dividing the number of times a specific value occurs by the total number of observations. For example, if you roll a six-sided die 100 times and get 20 ones, then the p.m.f for getting a one would be 20/100 or 0.2.

What is the mean of a p.m.f?

The mean of a p.m.f is also known as the expected value and is a measure of central tendency. It is calculated by multiplying each possible value by its corresponding probability and then summing up the results. For example, if the p.m.f for rolling a six-sided die is (1/6, 1/6, 1/6, 1/6, 1/6, 1/6), then the mean would be (1*1/6 + 2*1/6 + 3*1/6 + 4*1/6 + 5*1/6 + 6*1/6) = 3.5.

What is the relationship between the p.m.f and mean?

The p.m.f and mean are closely related as they both provide information about the distribution of a random variable. The p.m.f gives the probabilities of each possible value, while the mean gives a single value that represents the center of the distribution.

How can the p.m.f and mean be used in real-world applications?

The p.m.f and mean can be used in a variety of real-world applications, such as in statistics, finance, and engineering. They can help in making predictions, estimating risk, and understanding the likelihood of certain events. For example, a company may use p.m.f and mean to analyze sales data and make decisions about future product launches.

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