Answer:
The CLT says that the distribution is approximately normal, with mean of 17 credits and standard deviation of 0.3571 credits.
Step-by-step explanation:
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.
Assume that the population mean is 17 credits and the populations standard deviation is 2.5 credits.
This means that [tex]\mu = 17, \sigma = 2.5[/tex]
What does the CLT say about the distribution of the sample mean of 49 students?
It is approximately normal.
The mean is 17.
Due to the sample of 49, n = 49, and the standard deviation is [tex]s = \frac{2.5}{\sqrt{49}} = 0.3571[/tex]
The CLT says that the distribution is approximately normal, with mean of 17 credits and standard deviation of 0.3571 credits.