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Sampling
Sampling
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This material from Chapter 7
Flashcards
43 cards
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Practice quiz
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Questions
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Answers
1
Find the standard error
2%
1%
1.9%
1.96%
2
The Central Limit Theorem
20
30
25
1
3
What does the Central Limit Theorem state about samples from non-normal distributions?
If n > 20, the sampling distribution is normal
all sampling distributions are normal
If n > 30, the sampling distribution is normal
If n < 30, the sampling distribution is normal
4
How do you calculate the sample proportion (p hat)?
# of trials divided by # of successes
# of successes divided by the # of failures
# of trials multiplied by the # of successes
# of successes divided by # of trials
5
The sample proportion is:
an unbiased estimate of the population variance
an unbiased estimate of the population mean
an unbiased estimate of the population proportion
a biased estimate of the population proportion
6
What can effect the outcome of a stratified random sample?
All of the above
Non Response
Processing Error
Wording of the question
7
What is a sample?
the existence of an individual human being or animal
the condition or quality of being sad
moderate and comfortable heat
a small representation of something(work,food,etc.)
8
St. Andrew’s College received 900 applications for admission The Director would select a simple random sample of 30
it doesn't matter
assign a random number to all numbers then pick smallest 30
just pick the first 30
pick any 30
9
The Central Limit Theorem Says...
B
A
D
C
10
•Which of these is a Finite population? A)Organization B)membership roster C)Credit card
A and B
A only
All of the above
C and B
11
What does the central limit theorem talk about?
Sample means and sample proportions
None of the about
Sample means only
Sample proportions only
12
Replacing each sampled element before selecting subsequent elements is called sampling without replacement.
False
True
13
Why do Sample Proportions vary?
None of the above
The samples are composed of different people/entities
Population sizes vary
Trick question, sample proportions do not vary
14
Find the sample variance.
51.897
51.679
50.781
52.999
15
The sample proportion is:
an unbiased estimate of the population mean
an unbiased estimate of the population proportion
an unbiased estimate of the population variance
a biased estimate of the population proportion
16
Is the sampling distribution of the sample proportion approximately normal?
No
Yes
17
n = 25, p-hat = .45; Can I apply the Central Limit Theorem?
No
Only if the population is normal
Yes
Not enough info
18
The central limit theorem is important in statistics because it allows us to use the Normal
C
B
D
A
19
Which is not a factor when determining a sample size for a probability study?
population variance
degree of integrity
degree of precision
level of confidence
20
A collection of all the elements of interest.
A frame
A population
An element
A sample
21
Which of the following is FALSE about the Central Limit Theorem?
Distribution of sample mean is more peaked as n increases
It is only valid if the population distribution is Normal
The sample distribution becomes more Normal as n increases
As n increases, the center remains at μ
22
If n is large, the Central Limit Theorem tells us that the distribution of x-bar should...
Have a large amount of variablity
Be approximately normal
Not enough information is given
Be skewed
23
What does the Central Limit Theorem state about samples from non-normal distributions?
If n < 30, the sampling distribution is normal
If n > 20, the sampling distribution is normal
all sampling distributions are normal
If n > 30, the sampling distribution is normal
24
Was the tallest person in the sample a Male or Female?
Male
Female
25
The sample mean is:
an unbiased estimate of the population proportion
a biased estimate of the population variance
an unbiased estimate of the population mean
a biased estimate of the population mean
26
What is one way to decrease the standard error?
Increase sample size
Increase the standard deviation
Increase population
Use a population that is skewed
27
n = 25, μ = 65 inches, σ=3; Can I apply the Central Limit Theorem?
Only if the population is normal
Not enough info
Yes
No
28
You can reduce the chance of a sampling error by making the sample size ____
Larger
Smaller
29
How does doubling the sample size affect the standard deviation of the sampling distribution?
Decreases by a factor of sqrt(2)
Decreases by factor of 2
Increases by a factor of 4
Increases by a factor of sqrt(2)
30
How many girls are in our sample?
500
188
328
140
31
What is the sample proportion?
100/150=0.67
100/67=1.49
32
What does the central limit theorem say?
When n is large, the sampling distribution is not normal
When n is small, the sampling distribution is approx normal
When n is small, the sampling distribution is not normal
When n is large, the sampling distribution is approx normal
33
What two distributions are involved in the central limit theorem?
the original population and the sample means
sample means and non normal
the normal distribution and the probability distribution
conditional and multimodal
34
the entity on which data are collected?
A population
A frame
A sample
An element
35
Is the sampling distribution of the sample proportion approximately normal?
No
Yes
36
•With proper sampling methods, the sample results can not provide “good” estimates of the population characteristics.
True
False
37
•The sample results provide only estimates of the values of the population characteristics.
False
True
38
Sampling error happens:
Every time we take a sample
Only when we don't sample enough
Only if we get our sampling frame wrong
Only if our selection is biased
39
Recap: To know how variable a sample proportion is, what do we need to know?
The proportion and the size of the sample
The standard deviation and the mean
The proportion and the mean
The standard deviation and the sample size
40
A list of the elements that the sample will be selected from.
A sample
A population
An element
A frame
41
The Central Limit Theorem requires which two assumptions?
Again with the assuming?
Independence and Randomization
Randomization and Population Distribution
Independence and Population Distribution
42
What distribution do I use?
T
Z
Normal
Χ2 (Chi-Squared)
43
A subset of the population
A population
A sample
A frame
An element
