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:

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

Sample from Given Distribution