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Papessa [141]
2 years ago
9

There are 5 Snickers, 10 Baby Ruths, 13 Milky Ways, 12 Twixs and17 Almond Joys in a bowl of candy. You reach into the bowl and r

andomly select 5 candy bars. Use this information to answer the next two questions. What is the probability you select exactly 2 Milky Way bars?
Mathematics
1 answer:
agasfer [191]2 years ago
8 0

Answer: 0.2415

Step-by-step explanation:

Given : There are 5 Snickers, 10 Baby Ruths, 13 Milky Ways, 12 Twixs and17 Almond Joys in a bowl of candy.

Total candy bars : 5+10+13+12+17=57

Probability of getting a Milky Way bar=p=\dfrac{\text{No. of Milky bars}}{\text{Total candy bars}}

\Rightarrrow\ p=\dfrac{13}{57}\approx0.23

Using Binomial distribution , the probability of getting success in x trials is given by:-

P(x)=^nC_xp^x(1-p)^{n-x}, where p uis probability of success in each trial and n is sample size.

If you randomly select n= 5 candy bars, then the probability you select exactly 2 Milky Way bars Will be :_

P(2)=^5C_2(0.23)^2(1-0.23)^{3}\\\\=\dfrac{5!}{2!(5-2)!}(0.23)^2(0.77)^3\\\\=0.241505957\approx0.2415

Hence, the probability you select exactly 2 Milky Way bars = 0.2415

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There are 200 students in the 7th grade class at Brookside Middle School. Of these students, 12% play volleyball and 15% play ba
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Answer: The charge was right.

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From past experience, a company has found that in carton of transistors: 92% contain no defective transistors 3% contain one def
jasenka [17]

Answer:

E(X) = 0*0.92 + 1*0.03 +2*0.03 +3*0.02 = 0.1500

In order to find the variance we need to find first the second moment given by:

E(X^2) = \sum_{i=1}^n X^2_i P(X_i)

And replacing we got:

E(X^2) = 0^2*0.92 + 1^2*0.03 +2^2*0.03 +3^2*0.02 = 0.3300

The variance is calculated with this formula:

Var(X) = E(X^2) -[E(X)]^2 = 0.33 -(0.15)^2 = 0.3075

And the standard deviation is just the square root of the variance and we got:

Sd(X) = \sqrt{0.3075}= 0.5545

Step-by-step explanation:

Previous concepts

The expected value of a random variable X is the n-th moment about zero of a probability density function f(x) if X is continuous, or the weighted average for a discrete probability distribution, if X is discrete.

The variance of a random variable X represent the spread of the possible values of the variable. The variance of X is written as Var(X).  

Solution to the problem

LEt X the random variable who represent the number of defective transistors. For this case we have the following probability distribution for X

X         0           1           2         3

P(X)    0.92     0.03    0.03     0.02

We can calculate the expected value with the following formula:

E(X) = \sum_{i=1}^n X_i P(X_i)

And replacing we got:

E(X) = 0*0.92 + 1*0.03 +2*0.03 +3*0.02 = 0.1500

In order to find the variance we need to find first the second moment given by:

E(X^2) = \sum_{i=1}^n X^2_i P(X_i)

And replacing we got:

E(X^2) = 0^2*0.92 + 1^2*0.03 +2^2*0.03 +3^2*0.02 = 0.3300

The variance is calculated with this formula:

Var(X) = E(X^2) -[E(X)]^2 = 0.33 -(0.15)^2 = 0.3075

And the standard deviation is just the square root of the variance and we got:

Sd(X) = \sqrt{0.3075}= 0.5545

8 0
2 years ago
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