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patriot [66]
3 years ago
8

The desired percentage of SiO2 in a certain type of aluminous cement is 5.5. To test whether the true average percentage is 5.5

for a particular production facility, 16 independently obtained samples are analyzed. Suppose that the percentage of SiO2 in a sample is normally distributed with σ = 0.32 and that x = 5.21. (Use α = 0.05.)(a) Does this indicate conclusively that the true average percentage differs from 5.5?State the appropriate null and alternative hypotheses.
Mathematics
1 answer:
Alexeev081 [22]3 years ago
3 0

Answer:

The null and alternative hypothesis are:

H_0: \mu=5.5\\\\H_a:\mu< 5.5

At a significance level of 0.05, there is enough evidence to support the claim that the population percentage of SiO2 is signficantly different from 5.5%.  

P-value = 0.000004.

Step-by-step explanation:

This is a hypothesis test for the population mean.

The claim is that the population percentage of SiO2 is signficantly different from 5.5%.

Then, the null and alternative hypothesis are:

H_0: \mu=5.5\\\\H_a:\mu< 5.5

The significance level is 0.05.

The sample has a size n=16.

The sample mean is M=5.21.

The standard deviation of the population is known and has a value of σ=0.26.

We can calculate the standard error as:

\sigma_M=\dfrac{\sigma}{\sqrt{n}}=\dfrac{0.26}{\sqrt{16}}=0.065

Then, we can calculate the z-statistic as:

z=\dfrac{M-\mu}{\sigma_M}=\dfrac{5.21-5.5}{0.065}=\dfrac{-0.29}{0.065}=-4.462

This test is a left-tailed test, so the P-value for this test is calculated as:

\text{P-value}=P(z

As the P-value (0.000004) is smaller than the significance level (0.05), the effect is significant.

The null hypothesis is rejected.

At a significance level of 0.05, there is enough evidence to support the claim that the population percentage of SiO2 is signficantly different from 5.5%.

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Answer:

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Step-by-step explanation:

the answer will be 5 because it starts at 0.

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3 years ago
In 1990, 1000 adults were randomly selected and each was asked if they smoked, 300
Oduvanchick [21]

Answer:

 The proportion of smokers was higher in 1990 than in 2000

Step-by-step explanation:

Solution

Recall that,

The total number of sample 1 (n1) = 1000

Total  sample 2 number  (n2) = 2000

The number of favourable events (X1) = 300

The number of favourable events (X2) = 500

so,

p₁ = X₁/n₁ = 300/1000 = 0.3

p₂ = X₂/n₂ =500/2000 =0.25

α = 0.05

We are interested in testing the hypothesis.

The  hypothesis (Null) ....>  H₀ : p₁ = p₂

Alternate hypothesis------ > H₁ : p₁ > p₂

Thus,

P = X₁ + X₂/ n₁ + n₂

P =300 + 500/1000 +2000

P =800/3000

=0.2667

Now,

Z₀ = P₁ - P₂/√ P (1 -P) (1/n₁ + 1/n₂)

Z₀ =  0.3 - 0.25/√0.2667  (1 - 0.2667) (1/1000 + 1/2000)

Z₀ = 0.4999999999999999/√ 0.2667 (0.7333000000000001) (0.001 +0.0005)

Then,

Z₀ = 0.4999999999999999/√0.00029335666500000004

Z₀ = 2.9193

so,

zα/2 = z0.05/2 =z0.025

zα/2 = 1.6448536269514722

Now, we apply the decision rule:

Decision Rule: Reject the null hypothesis if the statistic value test is higher than the critical value 1.6448536269514722

The statistic value, 2.9193 is greater than the critical value 1.6448536269514722,  then we will reject the null hypothesis.

Therefore, the proportion of smokers was higher in 1990 than in 2000

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The taxi and takeoff time for commercial jets is a random variable x with a mean of 8.9 minutes and a standard deviation of 2.9
Eva8 [605]

Answer:

a) 0.2981 = 29.81% probability that for 37 jets on a given runway, total taxi and takeoff time will be less than 320 minutes.

b) 0.999 = 99.9% probability that for 37 jets on a given runway, total taxi and takeoff time will be more than 275 minutes

c) 0.2971 = 29.71% probability that for 37 jets on a given runway, total taxi and takeoff time will be between 275 and 320 minutes

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

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

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

The Z-score 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. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Mean of 8.9 minutes and a standard deviation of 2.9 minutes.

This means that \mu = 8.9, \sigma = 2.9

Sample of 37:

This means that n = 37, s = \frac{2.9}{\sqrt{37}}

(a) What is the probability that for 37 jets on a given runway, total taxi and takeoff time will be less than 320 minutes?

320/37 = 8.64865

Sample mean below 8.64865, which is the p-value of Z when X = 8.64865. So

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

By the Central Limit Theorem

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

Z = \frac{8.64865 - 8.9}{\frac{2.9}{\sqrt{37}}}

Z = -0.53

Z = -0.53 has a p-value of 0.2981

0.2981 = 29.81% probability that for 37 jets on a given runway, total taxi and takeoff time will be less than 320 minutes.

(b) What is the probability that for 37 jets on a given runway, total taxi and takeoff time will be more than 275 minutes?

275/37 = 7.4324

Sample mean above 7.4324, which is 1 subtracted by the p-value of Z when X = 7.4324. So

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

Z = \frac{7.4324 - 8.9}{\frac{2.9}{\sqrt{37}}}

Z = -3.08

Z = -3.08 has a p-value of 0.001

1 - 0.001 = 0.999

0.999 = 99.9% probability that for 37 jets on a given runway, total taxi and takeoff time will be more than 275 minutes.

(c) What is the probability that for 37 jets on a given runway, total taxi and takeoff time will be between 275 and 320 minutes?

Sample mean between 7.4324 minutes and 8.64865 minutes, which is the p-value of Z when X = 8.64865 subtracted by the p-value of Z when X = 7.4324. So

0.2981 - 0.0010 = 0.2971

0.2971 = 29.71% probability that for 37 jets on a given runway, total taxi and takeoff time will be between 275 and 320 minutes

7 0
2 years ago
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