Sampling

Question 1

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?

Answer 1

Random sampling

Question 2

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?

Answer 2

Sampling with replacement

Sampling without replacement

Without replacement is better

Question 3

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

Answer 3

Probability sampling

Question 4

Probability sampling is this type of statistical strategy

Answer 4

Statistical inference

Question 5

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

Answer 5

Convenience sampling

Question 6

Voluntary response sampling is what?

Answer 6

Where participants select themselves

Question 7

When a knowledgeable person selects population elements

Answer 7

Judgement sampling

Question 8

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

Answer 8

Central limit theorem

Question 9

What sample size is large enough?

Answer 9

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

Question 10

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

Answer 10

True

Question 11

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

Answer 11

Standard deviation

Question 12

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

Answer 12

Finite population correction

Square root of N-n/ N - 1

Question 13

The sample distribution of the sample propitiation has these 3 characteristics

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

Answer 13

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

Question 14

What is stratified random sampling and when is it appropriate?

Answer 14

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.

Question 15

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

Answer 15

Cluster sampling

Question 16

When is cluster sampling beneficial?

Answer 16

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

Question 17

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?

Answer 17

Systematic sampling

Question 18

Surveys that ask yes or no questions

Answer 18

Dichotomous survey questions

Question 19

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

Answer 19

Multiple choice

Question 20

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

Answer 20

Open-ended questions survey

Question 21

Which survey is the least reliable?

Answer 21

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

Question 22

The population of interest is the

Answer 22

Target population

Question 23

Sample frame is what

Answer 23

A list of sampling elements

Question 24

Sampling error

Answer 24

Difference between population and sample

Question 25

What will cause random sampling to not be representative?

Random sampling SHOULD eliminate biases. But it is possible to still have them present

Answer 25

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