STATS: Sampling Distribution & Central Limit Theorem (CLT)

What is X̄ (X-bar) used to represent?

the mean of a sample 

Random different samples help estimate population __

parameter

For large sample sizes, the sample average has a normal distribution with a mean and standard deviation

central limit Theorem

knowing X - bar is normal helps us to calculate __ 

probabilities 

mean of X is equal to mean of __

X-bar

original (X) standard deviation / square root of N 

calculating standard deviation of X bar 

What information is needed to calculate the standard error of the mean?

sample size and population standard deviation

What does the Central Limit Theorem say about the distribution of sample means?

1. As the sample size increases, the distribution of sample means becomes approximately normal

2. This approximation holds even if the population distribution is not normal

Which of the following correctly describe the mean and standard deviation of the sampling distribution of sample means?

Mean = μ, Standard Deviation = σ ÷ √n