Sampling Flashcards

1
Q

If we select n number of elements from a population in such a way that every set of n has the same chance of being selected. This is called what?

A

Random sampling

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2
Q

When we evaluate the element chosen and place it back into the population, this is called what?

When we don’t replace it’s called what?

Which is better?

A

Sampling with replacement

Sampling without replacement

Without replacement is better

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3
Q

Sampling where you know the chance that each element of the population will be included in the sample

A

Probability sampling

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4
Q

Probability sampling is this type of statistical strategy

A

Statistical inference

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5
Q

When we select elements because they are easy or convenient to sample

A

Convenience sampling

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6
Q

Voluntary response sampling is what?

A

Where participants select themselves

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7
Q

When a knowledgeable person selects population elements

A

Judgement sampling

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8
Q

The sampling distribution is approximately normal if the sample is large enough, even if the population is non-normal. This is called what?

A

Central limit theorem

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9
Q

What sample size is large enough?

A

If the sample size is at least 30 then the sample distribution is the sample mean will be approximately normal

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10
Q

An unbiased point estimate of a population parameter if the mean of all possible values of the sample statistic equals the population parameter. T or F

The sample mean is always unbiased

A

True

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11
Q

When given a choice between two estimates, choose the one with the smallest…

A

Standard deviation

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12
Q

If a finite population of size N I sampled randomly and without replacement , must use this to calculate the correct SD

Of N is less than what or is a finite population

  • if N < 20 x n then what formula
A

Finite population correction

Square root of N-n/ N - 1

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13
Q

The sample distribution of the sample propitiation has these 3 characteristics

= square root of p(1-p)/n

A
  1. Approximately normal (if n is large)
  2. Has a mean that equals p
  3. Has standard deviation
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14
Q

What is stratified random sampling and when is it appropriate?

A

Divide the population into non overlapping groups of similar units

Select a random sample from each strata

Combine the random samples to make full sample

Appropriate when the population consists of two or more groups

Units within a group are similar to each other.

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15
Q

A group of population into sub populations. Each grouping is representative of the population. A random sample is chosen from each group the. Combine to make a full sample

A

Cluster sampling

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16
Q

When is cluster sampling beneficial?

A

Populations spread over a large geographic area so that there are different sections and regions represented

17
Q

Select n units without replacement from a frame of N units, divide N by n and round down to a whole number.

Randomly select one unit within the first N/n interval and select every N/n unit after that.

This type of sampling is called what?

A

Systematic sampling

18
Q

Surveys that ask yes or no questions

A

Dichotomous survey questions

19
Q

Give the respondent a list of choices to select from is Called what type of survey?

A

Multiple choice

20
Q

Allow the respondent to answer in their own words is called what type of survey?

A

Open-ended questions survey

21
Q

Which survey is the least reliable?

A

Open-ended because you have to infer what they meant into groups.

22
Q

The population of interest is the

A

Target population

23
Q

Sample frame is what

A

A list of sampling elements

24
Q

Sampling error

A

Difference between population and sample

25
What will cause random sampling to not be representative? Random sampling SHOULD eliminate biases. But it is possible to still have them present
1. Under coverage - too few sample units or some of the population was excluded 2. Non response- when a sample unit cannot be contacted or refuses response 3. Response bias- responses of selected units are not truthful