- An
**element**is an object on which a measurement is taken. - A
**population**is a collection of elements about which we wish to make an inference. **Sampling units**are non-overlapping collections of elements from the population that cover the entire population.- A
**sampling frame**is a list of sampling units. - A
**sample**is a collection of sampling units drawn from a sampling frame. **Parameter**: numerical characteristic of a population**Statistic**: numerical characteristic of a sample

- Sampling can save money.
- Sampling can save time.
- For given resources, sampling can broaden the scope of the data set.
- Because the research process is sometimes destructive, the sample can save product.
- If accessing the population is impossible; sampling is the only option.

**Random Sampling vs Non-random Sampling**

**Random sampling**

- Every unit of the population has the same probability of being included in the sample.
- A chance mechanism is used in the selection process.
- Eliminates bias in the selection process
- Also known as probability sampling

**Nonrandom Sampling**

- Every unit of the population does not have the same probability of being included in the sample.
- Open the selection bias
- Not appropriate data collection methods for most statistical methods
- Also known as nonprobability sampling

**Random Sampling Techniques**

*Simple Random Sample*

- Uses a random number table or a random number generator to select n distinct numbers between 1 and N, inclusively.
- Easier to perform for small populations

*Stratified Random Sample*

- Population is divided into non-overlapping subpopulations called strata
- A random sample is selected from each stratum
- Proportionate -- the percentage of thee sample taken from each stratum is proportionate to the percentage that each stratum is within the population
- Disproportionate -- proportions of the strata within the sample are different than the proportions of the strata within the population

*Systematic Random Sample*

- Systematic sampling is often used instead of random sampling. It is also called an Nth name selection technique.
- After the required sample size has been calculated, every Nth record is selected from a list of population members.

*Cluster (or Area) Sampling*

- Population is divided into nonoverlapping clusters or areas
- Each cluster is a miniature, or microcosm, of the population.
- A subset of the clusters is selected randomly for the sample.

**Nonrandom Sampling Techniques**

*Convenience Sampling*: sample elements are selected for the convenience of the researcher

*Judgment Sampling*: sample elements are selected by the judgment of the researcher

*Quota Sampling*: sample elements are selected until the quota controls are satisfied

*Snowball Sampling*: survey subjects are selected based on referral from other survey respondents

source:

http://www.uky.edu/~kdbrad2/EPE773/Notes/PowerPoint/Chapter5.ppt.

http://www.aueb.gr/users/koundouri/resees/uploads/Chapter07.ppt.

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