Confidence Intervals for Large Samples (Pop MEAN)

we can use sample mean as an estimate for __ mean

population mean

X bar - EBM | X bar + EBM

confidence interval

EBM stands for __

error bound mean

We can only use the norm. dist to calculate confidence interval if: 

1. __

2. __

1. population standard deviation is known 

2. if sample size is greater than or equal to 30 (large) = n

Z (alpha/2) * sigma/sq.rt of N

EBM formula

1- confidence level (0.90)

alpha calculation

alpha / 2 is half of the __ calculation

alpha

Norm.INV(confidence level, 0, 1) 

calculating Z alpha/2 in excel 

if we don’t have population standard deviation, we can use __ standard deviation

sample

How did the presenter calculate the lower and upper bounds of the confidence interval?

By subtracting and adding the margin of error from the sample mean

Suppose we are sampling from a population that is highly skewed. According to the Central Limit Theorem, what will happen to the shape of the sampling distribution of the sample mean as the sample size increases?

The sampling distribution will become closer to a normal distribution as the sample size increases.