sampling

Question 1

sampling frame

Answer 1

which is a list of all
individuals belonging to the population

Question 2

sampling design

Answer 2

describes exactly how to choose a sample from the
sampling frame

Question 3

Non-probability samples

Answer 3

which are biased sampling designs

Question 4

Probability samples,

Answer 4

which are unbiased sampling designs

Question 5

In general, we classify sampling designs as:
* Non-probability samples, which are biased sampling designs

Answer 5

These designs over- or under-emphasize some characteristics of the population based
on the procedure used to select individuals for the sample.
* All individuals in the population do not have an equal chance of being sampled.
* As a result, the sample will likely not be representative.

Question 6

• In general, we classify sampling designs as:
• Non-probability samples, which are biased sampling designs
• Probability samples, which are unbiased sampling designs

Answer 6

All individuals in the population have an equal chance of being sampled.
* This means that, on average, the sample will be representative of the population.

Question 7

Biased Designs types

Answer 7

convience sampling and voltuary smapling

Question 8

convenience sample

Answer 8

A convenience sample is a sample obtained by selecting individuals in
the population that are easiest to reach.

Question 9

voluntary response sample

Answer 9

A voluntary response sample consists of the people who choose to
respond to a broad invitation

Question 10

Unbiased Designs
* Today, we will present three common unbiased sampling designs

Answer 10

. Simple random sample (SRS)
2. Stratified random sample
3. Cluster sampling

Question 11

Simple Random Sample (SRS)

Answer 11

selects
individuals from the sampling frame
through pure randomization.
* A SRS of size n consists of n individuals from
the population chosen in such a way that:
* (1) each individual has the same chance of
being selected
* (2) each combination of n individuals has equal
chance of being selected

Question 12

The most likely result of a simple random
sample is a

Answer 12

The most likely result of a simple random
sample is a representative subset, as we
see in the example.
* However, just due to chance, it is possible
that we obtain a sample that is not
representative.

Question 13

Stratified random sampling

Answer 13

eparates the population into mutually
exclusive groups (strata) and then draws simple random samples from
each stratum

Question 14

Cluster Sampling

Answer 14

Although we cannot obtain a sampling frame that includes all
individuals in the population, we hope to be able to obtain a sampling
frame of mutually exclusive groups (called clusters) that include all
individuals in the sampling frame.

Question 15

A cluster is believed to be a

Answer 15

A cluster is believed to be a representative group from the population, not
grouped by any feature believed to affect the variable of interest.