Parameter V Statistic
A parameter describes what?
A population.
What is a sampling distribution?
The distribution of a statistic from all possible samples of the same size.
The CLT says the sampling distribution of x-bar becomes approximately what shape?
Normal
The mean of the sampling distribution of p-hat is?
p
The mean of the sampling distribution of x-bar is?
M (mew)
A statistic describes what?
A sample.
True or False: Different random samples usually give different sample means/proportions.
True.
What sample size is usually considered “large enough” for CLT?
n≥30
The standard deviation of p-hat is:
Square root of p(1-p)/n
The standard deviation of the sampling distribution of x-bar is?
population standard deviation/square root of n
True or False: A statistic is usually known and fixed.
False (a parameter is fixed; a statistic varies).
As sample size n increases, sampling variability generally does what?
Decreases.
True or False: CLT applies even if the population is not normal, as long as n is large.
True.
What condition checks independence when sampling without replacement?
The 10% condition
What is the standard deviation of x-bar called?
The standard error
What symbol is commonly used for the population proportion?
p
What does the center of the sampling distribution of p-hat equal?
p
If the population is already normal, do you need n≥30 for x-bar to be normal?
No, it will be normal for any sample size.
What two conditions must be true for the sampling distribution of p-hat to be approximately normal?
np≥10 and n(1−p)≥10
What z-score formula is used for sample means?
z= x-bar - (mew) / pop. std. dev/ square root of n
What symbol is commonly used for the sample proportion?
^
p
What does the center of the sampling distribution of x-bar equal?
If n increases, what happens to the spread of the sampling distribution of x-bar?
It gets smaller.
What z-score formula is used for proportions?
z= p-hat - p / (p(1-p)/n
If the population is not normal and n is small, what should you do before using normal calculations?
You cannot assume normality (must use CLT only if n≥30 or verify population is normal).