Question

An certain brand of upright freezer is available in three different rated capacities: 16 ft3, 18 ft3, and 20 ft3. Let X = the rated capacity of a freezer of this brand sold at a certain store. Suppose that X has the following pmf.

$$ \begin{array}{l|ccc} x & 16 & 18 & 20 \\ \hline p(x) & 0.5 & 0.4 & 0.1 \end{array} $$

(a) Compute E(x), E(X2), and V(x).  

(b) If the price of a freezer having capacity X is 69X - 650, what is the expected price paid by the next customer to buy a freezer?

(c) What is the variance of the price paid by the next customer? 

(d) Suppose that although the rated capacity of a freezer is X, the actual capacity is h(X)=X-0.008x2. what is the expected actual capacity of the freezer purchased by the next customer? 


An certain brand of upright freezer is available in three different rated capacities: 16 ft3, 18 ft3, and 20 ft3. Let X = the rated capacity of a freezer of this brand sold at a certain store. Suppose that X has the following pmf. 16 18 20 p(x) 0.5 0.4 0.1 (a) Compute E(x), E(X2), and V(x). E(X)= 17.2 ft Ex2) 297.6 V(X) = 1.76 650, what is the expected price paid by the next customer to buy a freezer? (b) If the price of a freezer having capacity X is 69X $536.8 (c) What is the variance of the price paid by the next customer? (d) Suppose that although the rated capacity of a freezer is X, the actual capacity is h(X-X-0.008x? what is the expected actual capacity of the freezer purchased by the next customer? ft3



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Answer #1
Concepts and reason

A variable which can assume only countable number of real values and for which the value of the variable takes depends on chance is known as a discrete random variable.

If the random variable X is a one-dimensional discrete random variable taking at most a countable infinite number of values then its probabilistic behaviour at each real point is described by a function called the probability mass function.

It is denoted as, Р(х 3Dх)

Fundamentals

The probability mass function Р(X - х)
of a discrete random variable X is a function that should satisfy the following properties.

() ΣΡ(Χ = 3) =1
res
(2)P(X x)0
( 3)P(Xε Α) = Σ/(+)
χΕΛ

The mean and variance of the discrete random variable by using probability mass function is expressed as follows:

Mean E(X
-ΣΧΡ(Χ= )

VaranceE (χ) -[Ε(x)]
ΕΣΡ(Χ = ) -ΙΣΡ(X = 3)Τ

(a)

From the give information,

Let the random variable X represents the rated capacity of a freezer sold at a certain store.

Hence, the following table represent the probability distribution of the random variable X.

16 18 20
P(X x) 0.5 0.4 0.1

Hence,Е(x)
(mean), в (x°)
and V(x)
(variance) are computed as follows:

E(X)ExP(Xx)
=16(0.5)+18(0.4)+20(0.1)
=8+7.2 2
17.2

E (χ)-ΣΕΡ(X = 3)
=16 (0.5)+182 (0.4)+20° (0.1)
=128+129.6+40
-297.6

V(X)-в(x)-[в(x)Г
=297.6-(17.2)
1.76

(b)

From the given information, the price of a freezer having capacity X is69х - 650
.

The expected price paid by the next customer to buy a freezer is calculated as follows:

| E[69x-650] 69E[x]-650
=69 (17.2)-650
=536.8

(c)

From the given information, the price of a freezer having capacity X is.

The variance of price paid by the next customer to buy a freezer is calculated as follows:

V[69x-650]= (69x)-V (650)
69V[x]-0
=4761(1.76)
8379.36

(d)

If the price of freezer having capacity X ish(X)= X-0.0008X2
, then the expected price by the next year customer to buy a freezer is,

X-0.008X
E(x)-0.008E(x)
17.2-0.008 (297.6)
=17.2-2.3808
=14.8192

Ans: Part a

Therefore,E(X) 17.2
Е(x)- 297.6
and(x)1.76
.

Part b

Therefore,E[69X-650 536.8

Part c

Therefore,(69X-650 8379.36

Part d

Therefore,Eh(x)] 14.8192

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