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tia_tia [17]
3 years ago
10

A random sample of n measurements is drawn from a binomial population with probability of success . Complete parts a through d b

elow. a. Give the mean and standard deviation of the sampling distribution of the sample​ proportion, . The mean of the sampling distribution of is nothing. The standard deviation of the sampling distribution of is nothing.
Mathematics
1 answer:
Dima020 [189]3 years ago
4 0

Complete question :

A random sample of n = 83 measurements is drawn from a binomial population with probability of success 0.4 . Complete parts a through d below. a. Give the mean and standard deviation of the sampling distribution of the sample​ proportion, . The mean of the sampling distribution of is nothing. The standard deviation of the sampling distribution of is nothing.

Answer:

Mean = 33.2000

Standard deviation = 4.4632

Step-by-step explanation:

Given that :

Sample size (n) = 83

Probability of success (p) = 0.4

q = p' = (1 - p) = 1 - 0.4 = 0.6

The mean of the sampling distribution :

Sample size * probability of success

n * p = 83 * 0.4 = 33.2000

The standard deviation of the sampling distribution :

σ=√(sample size * probability of success * (1 - p))

σ = √n * p * (1 - p)

σ = √(83 * 0.4 * 0.6)

σ = √19.92

σ = 4.46318

σ = 4.4632

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Polymer composite materials have gained popularity because they have high strength to weight ratios and are relatively easy and
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Answer:

t=\frac{51.6-48}{\frac{1.1}{\sqrt{10}}}=10.349      

p_v =P(t_9>10.349)=1.34x10^{-6}  

If we compare the p value and the significance level given for example \alpha=0.05 we see that p_v so we can conclude that we reject the null hypothesis, and the the actual mean is significantly higher than 48 MPa at 5% of significance.

Step-by-step explanation:

1) Data given and notation      

\bar X=51.6 represent the sample mean

s=1.1 represent the standard deviation for the sample      

n=10 sample size      

\mu_o =48 represent the value that we want to test    

\alpha=0.05 represent the significance level for the hypothesis test.    

t would represent the statistic (variable of interest)      

p_v represent the p value for the test (variable of interest)  

State the null and alternative hypotheses.      

We need to conduct a hypothesis in order to determine if the mean score is higher than 48, the system of hypothesis would be:      

Null hypothesis:\mu \geq 48      

Alternative hypothesis:\mu > 48      

We don't know the population deviation, so for this case is better apply a t test to compare the actual mean to the reference value, and the statistic is given by:      

t=\frac{\bar X-\mu_o}{\frac{\sigma}{\sqrt{n}}} (1)      

t-test: "Is used to compare group means. Is one of the most common tests and is used to determine if the mean is (higher, less or not equal) to an specified value".  

Calculate the statistic      

We can replace in formula (1) the info given like this:      

t=\frac{51.6-48}{\frac{1.1}{\sqrt{10}}}=10.349      

Calculate the P-value      

First we find the degrees of freedom:

df=n-1=10-1=9

Since is a one-side upper test the p value would be:      

p_v =P(t_9>10.349)=1.34x10^{-6}  

Conclusion      

If we compare the p value and the significance level given for example \alpha=0.05 we see that p_v so we can conclude that we reject the null hypothesis, and the the actual mean is significantly higher than 48 MPa at 5% of significance.        

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Step-by-step explanation:

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Mean family size of Neighborhood Q:

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= 3.888888...

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The mean family size of Neighborhood Q is 3.88..  and the mean family size of Neighborhood S is 3.  Therefore, Neighborhood Q appears to have a bigger family size as it's average family size is bigger than that of Neighborhood S.

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Answer:

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