Flashcards in Exam 2 - Central Limit Theorem Deck (12):

0

## Sampling distribution of x-bar is the distribution of

### Values taken by x- bar from all possible samples of the same size from the same population

1

## Center : the mean of the sampling distribution of x-bar equals the

### Population mean, mu

2

## Spread: the standard deviation of the sampling distribution of x- bar equals

### Sigma over square root of n

3

## Shape: population normal - the shape of the sampling distribution of x- bar is

### Normal

4

## Shape: population non-normal- the shape of the sampling distribution of x-bars is

### Approximately normal when n is large

5

##
Central Limit Theorem:

If......

Then...,,

###
If you take a large SRS of size n from any population

Then

The sampling distribution of x- bar is approximately Normal

6

## As n increases shape gets more

### Normal

7

## n is considered to be large if it is

### Bigger than 30, n>30

8

## CLT allows us to use ........ ..... ......to compute approximate probabilities on x-bar

### Standard normal table

9

## T/F Increased sample size does not affect the shape of the population, only the shape of sampling distribution.

### True

10

##
How to predict sampling distribution of x- bar in statistical practice?

1. Take

2. Use sample

###
1. Take only 1 sample of size n

2. Use sample results to make inference about population

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