Representative and Bias in sampling- How to reduce bias

What is representative sample?
A representative sample is a small quantity of something that accurately reflects the larger entity.
 For example In a classroom of 30 students, in which half the
students are male and half are female, a representative sample might include six students: three males and three females.
 Bias due to unrepresentative sample
Bias often occurs when the survey sample does not accurately represent the population. The bias that results from an unrepresentative sample is
called selection bias. Some common examples of selection bias are described below.
 Undercoverage: Undercoverage occurs when some members of the population
are inadequately represented in the sample
  Nonresponse bias:
Sometimes, individuals chosen for the sample are unwilling or unable to
participate in the survey. Nonresponse bias is the bias that results when respondents differ in meaningful ways from nonrespondents.
 Voluntary response bias: Voluntary response bias occurs when sample
members are self-selected volunteers, as in voluntary samples
 Bias due to measurement error
A poor measurement process can also lead to bias. In survey research, the
measurement process includes the environment in which the survey is conducted,
the way that questions are asked, and the state of the survey respondent.
 Response bias refers to the bias that results from problems in the measurement process. Some examples of response bias are given below.
Leading questions: The wording of the question may be loaded in some
way to unduly favor one response over another. For example, a satisfaction survey may ask the respondent to indicate where she is satisfied, dissatisfied, or very dissatisfied. By giving the respondent one response option to express
satisfaction and two response options to express dissatisfaction, this survey
question is biased toward getting a dissatisfied response.
 Social desirability: Most people like to present themselves in a favorable
light, so they will be reluctant to admit to unsavory attitudes or illegal
activities in a survey, particularly if survey results are not confidential.
Instead, their responses may be biased toward what they believe is socially desirable.
How to reduce Bias
1) Using representative samples is one of the most effective methods for
reducing sampling bias. A representative sample accurately depicts or represents the larger population, factors or instances under study according
to the characteristics or qualities under examination.
2) Using the representative sampling method alone is not enough to ensure the bias is negligible, especially when making inferences from the results of the sample regarding the larger population. Random sampling from the general population is also important. In random sampling, each member of the larger
population has an equal chance of being chosen
3) The size of the group can also be optimally calculated to reduce sampling bias.