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Sampling Distributions Chapter 7

Transcript of Sampling Distributions - mooreschools.com · sampling distribution remains mound shaped and...

Page 1: Sampling Distributions - mooreschools.com · sampling distribution remains mound shaped and symmetrical (taller/thinner)for all sample sizes. We can conclude the sampling distribution

Sampling

Distributions

Chapter 7

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First, a word from our textbook

A statistic is a numerical value computed from

a sample. EX. Mean, median, mode, etc.

A parameter is a numerical value determined

by the entire population and is assumed that

the value is fixed,unchanging and unknown.

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Introduction to Statistics and

Sampling Variability

Consider a small population consisting of the

board of directors of a day care center.

Board member and number of children: Jay Carol Allison Teresa Anselmo Bob Roxy Vishal

5 2 1 0 2 2 1 3

Find the average number of children for the entire

group of eight:

= 2 children

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Discovery question ONE:

How is the parameter of the population

related to a sampling distribution based on

the population?

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Introduction to Statistics and

Sampling Variability

Board member and number of children: Jay Carol Allison Teresa Anselmo Bob Roxy Vishal

5 2 1 0 2 2 1 3

List all possible samples of size 2. Calculate the

average number of children represented by the

group.

Samples:

3.5x

Jay Carol

5 2

Jay Allison

5 1 3x

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Answer question ONE:

the average of all possible values for a

sampling distribution will equal the population

parameter

x

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Variability of a statistic

What is the relationship between the population parameter and each sample statistic?

The observed value of a statistic will vary from sample to sample. This fact is called sampling variability.

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Sampling distributions

If we calculated using only the first 3

columns of values, would we get the same

results? Explain.

How did the spread change from the

population to the sampling distribution?

Explain.

If we created a distribution based on a

sample size of 4 comment on the mean,

spread and shape of the sampling

distribution.

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Definition

In summary, a sampling distribution is the

distribution of all possible values for a given

sample size for a fixed population.

Sampling distribution applet

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Discovery question TWO:

For a normal population, how will the shape

and spread of a sampling distribution change

as we increase the sample size?

Population distribution = 16 = 5

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Discovery question TWO:

16X 16

X

16X

16X

3.535X

1.581X

1.25X

1X

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Answer question TWO:

For a normal population, the shape of the

sampling distribution remains mound shaped

and symmetrical (taller/thinner)for all sample

sizes. We can conclude the sampling

distribution remains approximately normal.

The standard deviation for the sampling

distribution is equal to the population

standard deviation divided by the square root

of the sample size.

Xn

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Sample means

parameter statistic

mean x

standard deviation s

Formulas:

x Xn

sampling

distribution

x

X

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Example ONE

The average sales price of a single-family

house in the United States is $243,756.

Assume that the sales prices are normally

distributed with a standard deviation of

$44,000.

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Draw the normal distribution. Within what

range would the middle 68% of the houses

fall?

$243,756

$243,756

$44,000

$287,756 $199,756

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Draw the sampling distribution for a sample

size of 4 houses. Within what range would the

middle 68% of the samples of size 4 houses

fall?

$243,756

$243,756x

$44,000x

$265,756 $221,756

$44,000

4x

$22,000x

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Draw the sampling distribution for a sample

size of 16 houses. Within what range would

the middle 68% of the samples of size 16

houses fall?

$243,756

$243,756x

$254,756 $232,756

$44,000

16x

$11,000x

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Draw the sampling distribution for a sample

size of 25 houses. Within what range would

the middle 68% of the samples of size 25

houses fall?

$243,756

$243,756x

$252,556 $234,956

$44,000

25x

$8,800x

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Example TWO

Suppose the mean room and board

expense per year at a certain four-year

college is $7,850. You randomly select 9

dorms offering room and board near the

college. Assume that the room and board

expenses are normally distributed with a

standard deviation of $1125.

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Draw the population distribution.

$7,850

$7,850

1125

$8,975 $6,725 $10,100 $11,225 $5,600 $4,475

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$7,850

$1125

$8,180

( 8180)P x

What is the probability that a randomly

selected dorm has room and board of less

than $8,180?

$7,850 $8,975 $6,725 $10,100 $11,225 $5,600 $4,475

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What is the probability that a randomly

selected dorm has room and board of less

than $8,180?

$7,850 $1125

( 8180)P x

Given normal distribution

xz

8180 7850

11250.29

.6141

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Draw the sampling distribution for a sample

size of 9 dorms.

$7,850

$7,850x

1125$375

9x

$8,225 $7,475 $8,600 $8,975 $7,100 $6,725

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What is the probability that the mean room

and board of the nine dorms is less than

$8,180?

$7,850

$7,850x

1125$375

9x

$8,225 $7,475 $8,600 $8,975 $7,100 $6,725

$8,180

( 8180)P x

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What is the probability that the mean room

and board of the nine dorms is less than

$8,180?

$7,850x

1125$375

9x

( 8180)P x

Given normal distribution

xz

n

8180 7850

3750.88

.8106

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What is the probability that the mean cost of a

sample of four dorms is more than $7,250?

$7,850x

1125$562.50

4x

( 7250)P x

Given normal distribution

xz

n

7250 7850

562.51.067

1 .1423 .8577