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Two types of coins are produced at a factory: a fair coin and a biased one that comes up heads 55percent of the time. We have one of these coins but do not know whether it is a fair coin or a biased one. In order to ascertain which type of coin we have, we shall perform the following statistical test: We shall toss the coin 1000 times. If the coin lands on heads 525 or more times, then we shall conclude that it is a biased coin, whereas if it lands on heads fewer than 525 times, then we shall conclude that it is a fair coin.

Short Answer

Expert verified

If the coin is actually fair, then the probability that we shall reach a false conclusion is 0.0606. If the coin were biased, then the probability that we shall reach a false conclusion is0.0525.

Step by step solution

01

Step 1. Given Information.

Here, it is given that -

Two types of coins are produced at a factory: fair and biased.

Each coin comes up heads 55%of the time.

Number of tosses = 1000

The coin is biased, if it lands on heads for more than 525times.

The coin is fair, if it lands on heads for less than 525times.

02

Step 2. Calculate mean and standard deviation of the fair coin.

The probability of getting head in a fair coin is p=0.5

Let Abe the event that the test concludes the coin is fair.

Let XAbe the number of heads in the test dependent on fair coin.

Number of times the coin is tossed = n= 1000

localid="1646632592661" μ=npμA=1000×0.5=500

localid="1646632650748" σ=np(1-p)σA=(1000×0.5)(1-0.5)σA=250σA=15.8114

03

Step 3. Calculate the probability that the researcher reaches a false conclusion when the coin is fair.

P(XA)=P(XA≥525-0.5)=P(XA≥524.5)

P(XA≥524.5)=PXA-μAσA=P524.5-50015.8114=P(Z≥1.5495)=1-φ(1.5495)=0.0606

Therefore, the probability that we reach a false conclusion when the coin is fair is0.0606.

04

Step 4. Calculate mean and standard deviation of the biased coin. 

The probability of getting head in a biased coin is=0.55

Let Bbe the event that the test concludes the coin is biased.

Let XBbe the number of heads in the test dependent on biased coin.

Number of times the coin is tossed = n=1000

μ=npμB=1000×0.55=550

σ=np(1-p)σB=(1000×0.55)(1-0.55)σB=247.5σB=15.7321

05

Step 5. Calculate the probability that the researcher reaches a false conclusion when the coin is biased.

P(XB)=P(XB<525-0.5)=P(XB<524.5)

P(XB<524.5)=PXB-μBσB=P524.5-55015.7321=P(Z<-1.6209)=0.0525

Therefore, the probability that we reach a false conclusion when the coin is biased is0.0525.

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