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ankoles [38]
3 years ago
8

An instructor gives her class a set of 10 problems with the information that thefinal exam will consist of a random selection of

5 of them. If a student has figured out how to do 7of the problems, what is the probability that he or she will answer correctly(a) all 5 problems?(b) at least 4 of the problems?
Mathematics
1 answer:
Elza [17]3 years ago
5 0

Answer:

(a)  0.0833

(b) 0.5

Step-by-step explanation:

We are given that an instructor gives her class a set of 10 problems from which random selection of 5 questions will come in the final exam and a student knows how to solve 7 of the problems from those 10 total problems.

(a) To calculate the probability that the student will be able to answer all 5 problems in the final exam, we consider that:

Student will be able answer all 5 problems in the final exam only when these 5 problems came from those 7 questions which he knows how to solve.

So the ways in which he answer all 5 problems correctly in the final exam      

                      =  ^{7}C_5

and total ways in which he answer 5 problems from the set of 10 problems

                      = ^{10}C_5

So, the Probability that he or she will answer correctly to all 5 problems

                           = \frac{^{7}C_5}{^{10}C_5}  = \frac{7!}{5!\times 2!}\times \frac{5!\times 5!}{10!} = 0.0833

                                               

(b) Now to calculate the probability that he or she will answer correctly at least 4 of the problems in the final exam is given by that [He or she will be able to answer correctly 4 problems in the exam + He or she will be able to answer correctly all 5 problems in the exam]

So the no. of ways that he or she will be able to answer correctly 4 problems in the exam = He or she answer correctly 4 questions from those 7 problems which he knows how to solve and the remaining one question from the other 3 questions we he don't know to solve = ^{7}C_4 \times ^{3}C_1

And the no. of ways that he or she will answer correctly all 5 questions in the final exam = ^{7}C_5

Therefore, the required probability =  \frac{(^{7}C_4 \times ^{3}C_1)+^{7}C_5}{^{10}C_5} =((\frac{7!}{4!\times 3!}\times \frac{3!}{1!\times 2!})+\frac{7!}{5!\times 2!})\times \frac{5!\times 5!}{10!} = 0.5 .

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Read 2 more answers
A fair coin is to be tossed 20 times. Find the probability that 10 of the tosses will fall heads and 10 will fall tails, (a) usi
lbvjy [14]

Using the distributions, it is found that there is a:

a) 0.1762 = 17.62% probability that 10 of the tosses will fall heads and 10 will fall tails.

b) 0% probability that 10 of the tosses will fall heads and 10 will fall tails.

c) 0.1742 = 17.42% probability that 10 of the tosses will fall heads and 10 will fall tails.

Item a:

Binomial probability distribution

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

C_{n,x} = \frac{n!}{x!(n-x)!}

The parameters are:

  • x is the number of successes.
  • n is the number of trials.
  • p is the probability of a success on a single trial.

In this problem:

  • 20 tosses, hence n = 20.
  • Fair coin, hence p = 0.5.

The probability is <u>P(X = 10)</u>, thus:

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

P(X = 10) = C_{20,10}.(0.5)^{10}.(0.5)^{10} = 0.1762

0.1762 = 17.62% probability that 10 of the tosses will fall heads and 10 will fall tails.

Item b:

In a normal distribution with mean \mu and standard deviation \sigma, the z-score of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

  • It measures how many standard deviations the measure is from the mean.  
  • After finding the z-score, we look at the z-score table and find the p-value associated with this z-score, which is the percentile of X.
  • The binomial distribution is the probability of <u>x successes on n trials, with p probability</u> of a success on each trial. It can be approximated to the normal distribution with \mu = np, \sigma = \sqrt{np(1-p)}.

The probability of an exact value is 0, hence 0% probability that 10 of the tosses will fall heads and 10 will fall tails.

Item c:

For the approximation, the mean and the standard deviation are:

\mu = np = 20(0.5) = 10

\sigma = \sqrt{np(1 - p)} = \sqrt{20(0.5)(0.5)} = \sqrt{5}

Using continuity correction, this probability is P(10 - 0.5 \leq X \leq 10 + 0.5) = P(9.5 \leq X \leq 10.5), which is the <u>p-value of Z when X = 10.5 subtracted by the p-value of Z when X = 9.5.</u>

X = 10.5:

Z = \frac{X - \mu}{\sigma}

Z = \frac{10.5 - 10}{\sqrt{5}}

Z = 0.22

Z = 0.22 has a p-value of 0.5871.

X = 9.5:

Z = \frac{X - \mu}{\sigma}

Z = \frac{9.5 - 10}{\sqrt{5}}

Z = -0.22

Z = -0.22 has a p-value of 0.4129.

0.5871 - 0.4129 = 0.1742.

0.1742 = 17.42% probability that 10 of the tosses will fall heads and 10 will fall tails.

A similar problem is given at brainly.com/question/24261244

6 0
2 years ago
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