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diamong [38]
4 years ago
15

Batting Average Problem Milt Famey has a baseball batting average of 300, which means that his probability of getting a hit at a

ny one time at bat is 0.3. Suppose that Milt comes to bat 5 times during a game.
a. Calculate the probabilities that he gets exactly 0, 1, 2, 3, 4, and 5 hits.
b. What is Milt's mathematically expected number of hits in these 5 at-bats?
Mathematics
1 answer:
Fofino [41]4 years ago
6 0

Answer:

a) P(X=0)=(10C0)(0.3)^0 (1-0.3)^{5-0}=0.168  

P(X=1)=(10C1)(0.3)^1 (1-0.3)^{5-1}=0.360  

P(X=2)=(10C2)(0.3)^2 (1-0.3)^{5-2}=0.309  

P(X=3)=(10C3)(0.3)^3 (1-0.3)^{5-3}=0.132  

P(X=4)=(10C4)(0.3)^4 (1-0.3)^{5-4}=0.028  

P(X=5)=(10C5)(0.3)^5 (1-0.3)^{5-5}=0.00243  

b) And we know that the expected value for a binomial distribution is given by:

E(X) = np = 5*0.3= 1.5

Step-by-step explanation:

Previous concepts  

The binomial distribution is a "DISCRETE probability distribution that summarizes the probability that a value will take one of two independent values under a given set of parameters. The assumptions for the binomial distribution are that there is only one outcome for each trial, each trial has the same probability of success, and each trial is mutually exclusive, or independent of each other".  

Solution to the problem  

Let X the random variable of interest, on this case we now that:  

X \sim Binom(n=5, p=0.3)  

The probability mass function for the Binomial distribution is given as:  

P(X)=(nCx)(p)^x (1-p)^{n-x}  

Where (nCx) means combinatory and it's given by this formula:  

nCx=\frac{n!}{(n-x)! x!}  

Part a

P(X=0)=(10C0)(0.3)^0 (1-0.3)^{5-0}=0.168  

P(X=1)=(10C1)(0.3)^1 (1-0.3)^{5-1}=0.360  

P(X=2)=(10C2)(0.3)^2 (1-0.3)^{5-2}=0.309  

P(X=3)=(10C3)(0.3)^3 (1-0.3)^{5-3}=0.132  

P(X=4)=(10C4)(0.3)^4 (1-0.3)^{5-4}=0.028  

P(X=5)=(10C5)(0.3)^5 (1-0.3)^{5-5}=0.00243  

Part b

For this case We want to find the extecped number of hits in the 5 at-bat

And we know that the expected value for a binomial distribution is given by:

E(X) = np = 5*0.3= 1.5

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Step-by-step explanation:

Let x be the number of quarts of 100% fruit juice

Let y be the number of quarts of 20% fruit juice

The equation for amount of quarts is ;

x+y=6

x=6-y-------------------equation 1

The equation for the amount of quarts of fruit juice to get 80% fruit juice will be;

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{x(100%)+y(20%) }/6=80%

Multiply both parts of the equations by 6

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Use equation 1 in 2

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Answer:

a) The 99% confidence interval would be given (0.523;0.577).

We are 99% confident that this interval contains the true population proportion.

b) n=\frac{0.55(1-0.55)}{(\frac{0.03}{2.58})^2}=1830.51  

And rounded up we have that n=1831

Step-by-step explanation:

Data given and notation  

n=2341 represent the random sample taken    

X represent the people that they have watched digitally streamed TV programming on some type of device

\hat p=0.55 estimated proportion of people that they have watched digitally streamed TV programming on some type of device  

\alpha=0.01 represent the significance level

Confidence =0.99 or 99%

z would represent the statistic for the confidence interval  

p= population proportion of people that they have watched digitally streamed TV programming on some type of device

The population proportion present the following distribution:

p \sim N (p, \sqrt{\frac{p(1-p)}{n}}

Part a) Confidence interval

The confidence interval would be given by this formula

\hat p \pm z_{\alpha/2} \sqrt{\frac{\hat p(1-\hat p)}{n}}

For the 99% confidence interval the value of \alpha=1-0.99=0.01 and \alpha/2=0.005, with that value we can find the quantile required for the interval in the normal standard distribution.

z_{\alpha/2}=2.58

And replacing into the confidence interval formula we got:

0.55 - 2.58 \sqrt{\frac{0.55(1-0.55)}{2341}}=0.523

0.55 + 2.58 \sqrt{\frac{0.55(1-0.55)}{2341}}=0.577

And the 99% confidence interval would be given (0.523;0.577).

We are 99% confident that this interval contains the true population proportion.

Part b) What sample size would be required for the width of a 99% CI to be at most 0.03 irrespective of the value of p??

The margin of error for the proportion interval is given by this formula:  

ME=z_{\alpha/2}\sqrt{\frac{\hat p (1-\hat p)}{n}}    (a)  

And on this case we have that ME =\pm 0.03 and we are interested in order to find the value of n, if we solve n from equation (a) we got:  

n=\frac{\hat p (1-\hat p)}{(\frac{ME}{z})^2}   (b)  

And replacing into equation (b) the values from part a we got:

n=\frac{0.55(1-0.55)}{(\frac{0.03}{2.58})^2}=1830.51  

And rounded up we have that n=1831

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4 years ago
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