The distribution of the values obtained from a simple random sample of size n from the same population is incorrect.
<h3>What is
sampling distribution?</h3>
The sampling distribution of a statistic of size n is the distribution of the values obtained from a simple random sample of size n from the same population.
The sampling distribution is the process of getting a sample through simple random techniques from the sample population.
So, it is incorrect that the distribution of all values of the statistic when all possible samples of the same size n are taken from the same population.
Learn more about sampling distribution here:
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Answer:
g is right its 66 cents
Step-by-step explanation:
you would divide 82.49 by 125 and then round to the nearest hundredth
Answer:
4 runners
Step-by-step explanation:
I divided 1/4 by 1/16 and got 4 as an answer.
Hope this helps :)
(Correct me if i am wrong)
Answer:
μ > 21.21
Test statistic = 1.217
Kindly check explanation for more details
Step-by-step explanation:
The null hypothesis, H0 : μ = 21.21
Alternative hypothesis, H1 : μ > 21.21
The test statistic :
(xbar - μ) ÷ (s/sqrt(n))
(21.212 - 21.21) ÷ (0.01 / √2)
= 1.217
The critical value :
From the t distribution :, one tailed = 2.434
Decision region :
Reject H0 if test statistic > critical value
1.217 < 2.434 ; We fail to reject the null ` ; and conclude that there is not enough evidence to support the claim.
