Westonci.ca is your go-to source for answers, with a community ready to provide accurate and timely information. Our platform provides a seamless experience for finding reliable answers from a network of experienced professionals. Our platform offers a seamless experience for finding reliable answers from a network of knowledgeable professionals.
Sagot :
Answer:
0.0062 = 0.62% probability that the sample mean is less than $650.
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 [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the z-score of a measure X is given by:
[tex]Z = \frac{X - \mu}{\sigma}[/tex]
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 estabilishes that, for a normally distributed random variable X, with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]s = \frac{\sigma}{\sqrt{n}}[/tex].
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
Mean of $675 and a standard deviation of $80.
This means that [tex]\mu = 675, \sigma = 80[/tex]
A random sample of 64 families in this city paying for childcare is selected.
This means that [tex]n = 64, s = \frac{80}{\sqrt{64}} = 10[/tex]
Find the probability that the sample mean is less than $650.
This is the pvalue of Z when X = 650.
[tex]Z = \frac{X - \mu}{\sigma}[/tex]
By the Central Limit Theorem
[tex]Z = \frac{X - \mu}{s}[/tex]
[tex]Z = \frac{650 - 675}{10}[/tex]
[tex]Z = -2.5[/tex]
[tex]Z = -2.5[/tex] has a pvalue of 0.0062
0.0062 = 0.62% probability that the sample mean is less than $650.
The probability that the sample mean is less than $650 is 0.62%.
The z score is given by:
[tex]z=\frac{x-\mu}{\sigma/\sqrt{n} } \\\\where\ x=raw\ score,\sigma=standard\ deviation,\mu=mean,n=sample\ size\\\\\\Given \ \mu=675,\sigma=80,n=84, hence:\\\\For\ x<650:\\\\z=\frac{650-675}{80/\sqrt{64} } =-2.5[/tex]
From the normal distribution table:
P(x < 650) = P(z < -2.5) = 0.0062 = 0.62%
The probability that the sample mean is less than $650 is 0.62%.
Find out more at: https://brainly.com/question/15016913
We hope this information was helpful. Feel free to return anytime for more answers to your questions and concerns. Thanks for using our platform. We aim to provide accurate and up-to-date answers to all your queries. Come back soon. Get the answers you need at Westonci.ca. Stay informed with our latest expert advice.
