What is Sampling? Reasons or need for sampling than census

http://www.reportbd.com/articles/97/1/What-is-Sampling-Reasons-or-need-for-sampling-than-census/Page1.html

Super Admin

By Super Admin

Published on 22 May 2008

What is Sampling? Reasons / need for sampling instead of census with examples.

What is Sampling? Reasons or need for sampling than census

What is Sampling:

Sampling: It is technique of drawing samples, I.e., it is a technique of collecting data only on a part of the population to reveal the characteristics of the entire population. Example-

Reasons for sampling instead of census / Need for sampling:

There are 6 reasons for sampling

(1) Economy

(2) Timeliness

(3) Large size of many population

(4) Inaccessibility of the entire population.

(5) Destructive nature of many Observation

(6) Reliability or accuracy.

(1) Economy:

Unit cost of collecting data in the case of census is significantly less then in the case of sampling for example: In case of census is taka 200, while in the case of sampling is taka 1,000 but due to the larger number of items the total cost involve in the case of census of census is significantly higher then in the case of sampling.

For example, We can find out the total cost of collecting information by multiplying the total population with the unit cost in case of census. Here total population = N

We can find out the total cost of collecting information by multiplying the sample size with the unit cost in case of census.

Here sample size=n.

10,00,000 x 200 = 20,00,00,000

5,000 x 1000 = 50,00,000

(2) Timeliness:

Unit time involve in the case of sampling then in the case census but due to the larger size of population total time involve in the case of census in significantly higher then in the case of census.

(3) Large size of many population:

In some cases the size of the population is extremely large. All of them are not treaseable due in traveling, disease, death, mental abnormality, prisoners etc. In that situation the only way to conduct the research is collecting data through a sample survey.

(4) Inaccessibility of the entire population:

In some cases the entire population may not be accessible. At that case sampling is necessary. Suppose in some cases the entire population is inaccessible because of aircraft crash.

(5) Destructive nature of many population:

Due to destructive nature of many of the population, the resources is completed to collect information only on a part of the population.

For example:

Blood test for a patient.

Life hours of a tube light.

(6) Reliability:

By using a scientific sampling technique one can minimize the sampling error and as qualified investigators are included, the non-sampling error committed in the case of sample survey is also minimum.

The amount of non-sampling error in the case of census is much higher than the total amount of sampling and non-sampling error committed in the case of a sample survey ( as less qualified investigator are involve in the case of census and the supervision, monitoring and quality control mechanism in the case of census.

The degree of errors has a relationship with reliability. If error decrease than the reliability increase sampling decrease both the sampling and non-sampling error. So, it enhance the reliability of information.

Sampling: It is technique of drawing samples, I.e., it is a technique of collecting data only on a part of the population to reveal the characteristics of the entire population. Example-

Reasons for sampling instead of census / Need for sampling:

There are 6 reasons for sampling

(1) Economy

(2) Timeliness

(3) Large size of many population

(4) Inaccessibility of the entire population.

(5) Destructive nature of many Observation

(6) Reliability or accuracy.

(1) Economy:

Unit cost of collecting data in the case of census is significantly less then in the case of sampling for example: In case of census is taka 200, while in the case of sampling is taka 1,000 but due to the larger number of items the total cost involve in the case of census of census is significantly higher then in the case of sampling.

For example, We can find out the total cost of collecting information by multiplying the total population with the unit cost in case of census. Here total population = N

We can find out the total cost of collecting information by multiplying the sample size with the unit cost in case of census.

Here sample size=n.

10,00,000 x 200 = 20,00,00,000

5,000 x 1000 = 50,00,000

(2) Timeliness:

Unit time involve in the case of sampling then in the case census but due to the larger size of population total time involve in the case of census in significantly higher then in the case of census.

(3) Large size of many population:

In some cases the size of the population is extremely large. All of them are not treaseable due in traveling, disease, death, mental abnormality, prisoners etc. In that situation the only way to conduct the research is collecting data through a sample survey.

(4) Inaccessibility of the entire population:

In some cases the entire population may not be accessible. At that case sampling is necessary. Suppose in some cases the entire population is inaccessible because of aircraft crash.

(5) Destructive nature of many population:

Due to destructive nature of many of the population, the resources is completed to collect information only on a part of the population.

For example:

Blood test for a patient.

Life hours of a tube light.

(6) Reliability:

By using a scientific sampling technique one can minimize the sampling error and as qualified investigators are included, the non-sampling error committed in the case of sample survey is also minimum.

The amount of non-sampling error in the case of census is much higher than the total amount of sampling and non-sampling error committed in the case of a sample survey ( as less qualified investigator are involve in the case of census and the supervision, monitoring and quality control mechanism in the case of census.

The degree of errors has a relationship with reliability. If error decrease than the reliability increase sampling decrease both the sampling and non-sampling error. So, it enhance the reliability of information.