Sampling Distribution Flashcards

0
Q

A sample

A

Is a part of a population used to represent the population

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1
Q

The population

A

Is the complete set of items of interest

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2
Q

Population parameters

A

Population mean μ

Population standard deviation σ

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3
Q

Statistics

A

Sample mean x

Sample standard deviation s

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4
Q

Statistics are used to…

A

Make inferences about population parameters

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5
Q

Statistics vary depending on….

A

The particular sample chosen

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6
Q

The sampling distribution is unbiased if…

A

It’s mean (x) is equal to the associated population parameter (μ)

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7
Q

Means are ______ measurements

Proportion are essentially ________ measurements

A

Quantitative

Qualitative

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8
Q

How to find the standard deviation of a sample proportion

A

_________

s= ✔️(p(1-p))/n)

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9
Q

To use normal approximation for a binomial proportion, np and n(1-p) should be at least ___

A

10

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10
Q

To use normal approximation for a binomial proportion, it is important that samples are _________

A

Simple random samples

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11
Q

To use normal approximation for a binomial proportion, the sample size should be no larger than…

A

10% of the population

This actually show indep, but the simple random sample requirement allows us to assume independence

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12
Q

How to find the standard deviation of a sample mean (x)

A

s= _σ__

(✔️n)

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13
Q

While giving the mean (x) and standard deviation (s) of a set of sample means, we do not describe….

A

The shape of the distribution

Because we can only conclude that the sample is normal if the population is normal

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14
Q

No matter how the original population is distributed, if……. The set of sample means is approximately normally distributed

A

n is large enough (30)

Aka central limit theorem

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15
Q

Distribution of the original population

A

May be uniform, bell-shaped, strongly skewed, etc.

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16
Q

Standard deviation of two sample proportions

A

s= p1(1-p1) + p2(1-p2)

✔️ n1 n2

17
Q

The mean of the set of difference of sample proportions equals….

A

p1-p2

The difference of the population proportions

18
Q

The standard deviation of a set of differences of sample means is approximately…

A

σ1^2 + σ2^2

✔️ n1 n2

19
Q

The more either population varies from normal, the greater should be the corresponding ______

A

Sample size

*but should still be less than 10% of the population

20
Q

When to use t distributions

A

When the population standard deviation (σ) is unknown and the original pop is normally distributed

21
Q

How to find t

A

t= __x-μ__

s/(✔️n)

22
Q

t distributions are associated with…

A

Degrees of freedom (df)

df= n-1

23
Q

He last row of Table B (for t distributions) is the ______

A

Normal distribution, which is the case of the t-distribution taken when n is infinite

24
Why are t distributions used so often?
The real world σ is almost always unknown
25
The issue of sample size refined by statisticians: | The t-distribution with an SRS with large n (>40)
Unnecessary to make any assumptions about parent population
26
The issue of sample size refined by statisticians: | The t-distribution with an SRS with medium n (15-40)
Sample should show no extreme values and little, if any, skewness; or assume parent population is normal
27
The issue of sample size refined by statisticians: | The t-distribution with an SRS with small n (<15)
Sample should show no outliers and no skewness; or assume parent population is normal
28
What are chi square models used for?
Tests (not confidence intervals)
29
Chi square parameter
Degrees of freedom | df= n-2
30
With chi square, if df is small the distribution is...
Skewed right
31
With chi square, if df is small the distribution....
Becomes more symmetric and bell-shaped. (Like a t distribution)
32
With chi square, for one or two df the peak occurs at ___
Zero
33
With chi square, for 3+ df! the peak is at...
df-2
34
Chi square distributions are _________ distributions
Continuous Applying it to counting data is just an approximation
35
Standard error of a proportion
SE(p)= _pq_ | ✔️ n
36
Standard error for means
SE(x)= _s_ | (✔️n)
37
If the population is not normally distribution, does the sampling distribution of x have a mean equal to the population mean?
Yes
38
The sampling distribution of p
The population proportion (p)
39
If data from a sample is skewed left, what happens when the sample size goes from n=50 to n=200?
The mean stays the same The standard deviation becomes smaller The shape becomes closer to normal
40
Why is the sample. Axiom not used as an estimator for the population maximum?
The sample maximum is biased
41
t distributions are always ______
Symmetric and mound shaped Like normal distributions