Sampling and data

Descriptive statistic

Data:

• Data are values of qualitative (attributes) or quantitative (variable) from observations
• It is an abstract concept that can be viewed as the lowest level of abstraction, from which information and then knowledge are derived

Statistic:

• A statistic is a number that represents a property of the sample.
• The statistic is an estimate of a population parameter.

Parameter:

• A parameter is a numerical characteristic of the ==whole Population== that can be estimated by a statistic.

An attribute:

• a characteristic of an object which cannot be measured.
  • example: he is tall

Variable:

• something that may or does vary which can be measured
• A discrete variable:
  • a variable which can only take a countable number of values.
• Continuous variables:
  • may take on any value.

Census vs Sample survey:

• Census refers to data collection about everyone or everything in a Population.
  • This method gives a high degree of accuracy but is very expensive and time consuming.
• Sample survey:
  • Only part of total population is used for collecting data.
    • This method is less expensive than a census and the results can be obtained far more quickly.
  • But the results have a degree of inaccuracy, depending on the sample size and methods for conducting survey.

Types of errors:

• Sampling error
• Response error
• Non-response error occur when the survey fails to get a response to one, or possibly all, of the questions.

A Simple random sample is a sample selected in such a way that every item in the population has an equal chance of being included.

A sampling frame is the source material from which a sample is drawn. It is a list of all those within a population who can be sampled.

• A sampling frame should have the following characteristics:
  • Completeness
  • Accuracy
  • Up to date
  • Non-duplication
• Drawbacks of random sampling:
  • An unrepresentative sample may result.
  • The members of population selected may be scattered over a wide area.

Systematic sampling

There are more sampling method

• | Random sampling method | Desc | | --- | --- | | Simple random | All item has equal chance | | Quasi-random | includes: Systematic, Stratified, and Multistage sampling | | Systematic | pick every kth item where k=population size/sample size | | Stratified | stratum sample size = (size of stratum)×(sample size)÷(size population) then use another method to selects elements from each stratum | | Multistage | At each stage, a stratified random sample on a variable on which they could get information before sampling |
• | Non-random sampling method | Desc | | --- | --- | | Quota | select a predetermined number or proportion of units with specific characteristics in a non-random manner | | Cluster | the total population is divided into groups (or clusters) and a simple random sample of the groups is selected |
• Survey method: questionnaire and interview