Flashcards in Exam 2- sampling distributions Deck (29):

0

## Theoretical sampling distribution of x- bar is

### The distribution of all x- bar values from all possible samples of the same size from the same population

1

## Approximate sampling distribution of x- bar is

### The distribution of x- bar values obtained from repeatedly taking SRSs of the same size from the same population

2

##
Center

The mean of the sampling distribution of x- bar .... the mu....

### Equals ..... Population mean

3

## Mean =mu is valid for

### All sample sizes and populations of all shapes

4

##
Spread

The standard deviation of the sampling distribution of x- bar .....

###
Equals the standard deviation of the population divided by the square root of n

Valid for all sample sizes and population of all shapes

5

##
Shape

For non-normal population

### Shape of sampling distribution of x-bar is approximately normal when n is large

6

##
Shape

For normal population

### Shape of the sampling distribution if x- bar is exactly normal for any n

7

## Mean ...... equals mu regardless of population shape or sample size

### Exactly

8

## Standard deviation of x- bar is always ..... Than the standard deviation of the population for samples of any size where ....

### Less. n>1

9

## Standard deviation of c- bar gets ....as n increases at rate ....

### Smaller.... Square root of n

10

## To cut standard deviation in half

### Quadruple sample size

11

## Shape is normal if population is .....for any sample size

### Normal

12

## Shape is approximately normal if we take a ...... ....... ....... from a non- normal population

### Large random sample

13

## The population distribution of a variable is

### The distribution of values of the variable among all the individuals in the population

14

## The sampling distribution of a statistic is

### The distribution of values taken by the statistic in all possible samples of the same size from the same population

15

## The population distribution describes the ..... that make up the population

### Individuals

16

## A sampling distribution describes how .... Varies in many samples from the population

### Statistic

17

## What is distribution of random variable?

### A list of all possible values of a variable together with how often each value occurs

18

## The probability of an event can be defined as

### The fraction of time the event will occur if random phenomenon is related many time

19

## Central Limit Tgeorem

### If you take a large SRS of size n from any population then the sampling distribution of x- bar is approximately not mail

20

## The central limit theorem on x- bar requires

### A large random sample

21

## A correlation of r=0 indicates

### That x and y are not linearly related

22

## T/F probabilities on individuals can only be computed using the standard Normal table if the population is Normally distributed

### True

23

## What does the probability distribution of a random variable gives us?

### All possible values if the random variable together with their probabilities

24

## T/F because there is a probability assigned to each event, the probability model is correct

### T

25

## T/f because all probabilities are between zero and one, and because the sum of all probabilities is 1, the probability model is correct

### True

26

## The law of the large numbers refers to the .... Of a ..... Not to the sampling distribution of x- bar

### Mean of a sample

27

## What does the Law of Large numbers tell us?

### As sample size increases, the variable x-bar from a random sample gets closer and closer to mu

28