Respuesta :
Answer:
100% probability of selecting a sample of 65 one-bedroom apartments and finding the mean to be at least $2,095 per month
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 $2,275 and a standard deviation of $290.
This means that [tex]\mu = 2275, \sigma = 290[/tex]
Sample of 65:
This means that [tex]n = 65, s = \frac{290}{\sqrt{65}}[/tex]
Finding the mean to be at least $2,095 per month
This is 1 subtracted by the p-value of Z when X = 2095. So
[tex]Z = \frac{X - \mu}{\sigma}[/tex]
By the Central Limit Theorem
[tex]Z = \frac{X - \mu}{s}[/tex]
[tex]Z = \frac{2095 - 2275}{\frac{290}{\sqrt{65}}}[/tex]
[tex]Z = -5[/tex]
[tex]Z = -5[/tex] has a p-value of 0.
1 - 0 = 1
100% probability of selecting a sample of 65 one-bedroom apartments and finding the mean to be at least $2,095 per month
