Answer:
The 95% confidence interval obtained with a sample size of 64 will give greater precision.
Step-by-step explanation:
We are given the following in the question:
A 95% confidence interval is calculated with the following sample sizes
The population mean and standard deviation are unknown.
Effect of sample size on confidence interval:
- As the sample size increases the margin of error decreases.
- As the margin of error decreases the width of the confidence level decreases.
- Thus, with increased sample size the width of confidence level decreases.
If we want a confidence interval with greater precision that is smaller width, we have to choose the higher sample size.
Thus, the 95% confidence interval obtained with a sample size of 64 will give greater precision.
Answer:
By the Central Limit Theorem, the sampling distribution of the sample mean amount of money in a savings account is approximately normal with mean of 1,200 dollars and standard deviation of 284.6 dollars.
Step-by-step explanation:
Central Limit Theorem
The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean 
and standard deviation 
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean and standard deviation 
.
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
Average of 1,200 dollars and a standard deviation of 900 dollars.
This means that 
Sample of 10.
This means that 
The sampling distribution of the sample mean amount of money in a savings account is
By the Central Limit Theorem, approximately normal with mean of 1,200 dollars and standard deviation of 284.6 dollars.
C=d x pi
d= 24
C= 24 x 3.14
C=75.36 inches
hope this helps
Answer:
120 into a third and divide and the answer
Step-by-step explanation:
160
F(x)= -8x²
f(-3)= -8* (-3)²
f(-3)= -8 * 9
f(-3)= -72
