Select Page

The Topic Sampling Error is Relevant For UGC NET Commerce & Management as Follows:

Introduction

Sampling Error occurs solely as a result of using a sample from a population rather than conducting a census of the population. It refers to the difference between a sample statistics used to estimate a population parameter and the actual but unknown value of parameter. Sampling errors are inherent and unavoidable.

Definitions

• Sampling: The process of selecting a part of the population.
• Population: The entire group of people of interest from whom the researcher needs to obtain information.
• Sample: A selected part of the population is called sample. It should be a true representative of the whole population.
• Sample size: The number of people in the selected sample is known as sample size.
• Statistics: Any value calculated from sample is called statistics.
• Parameter: Any value calculated from population is called parameter.
• Sampling frame: It means the list of individual or people included in the same. It reflects who will be included in the sample.
• Sampling technique: It refers to technique or procedure used to select the members of the sample.

Errors in Sampling

Error: Statistical error is the difference between a value obtained from a data collection process and the true value for the population.

Data can be affected by two types of error:

1. Sampling error

2. Non-Sampling error

How Sampling Error occurs ?

It can occur when:

• The proportions of different characteristics within the sample are not similar to the proportions of the characteristics of whole population.
• The sample is too small to accurately represent the population.
• The sampling method is not random.
• Sampling error are absent in a complete enumeration survey.

How Sampling Error can be reduced?

• Unbiased sampling: Sampling error can be measured and controlled in random samples where each unit has a chance of selection, and that chance can be calculated.
• Increase the sample size: Increasing the sample size will reduce the sample error.
• Cross check: Biased responses should be avoided
• Example: If we are taking a sample of men & women and we know that 51 % of the total   population are women & 49% are men, then we should aim to have similar populations in our   sample.
• Appropriate sampling design: Specific sampling plan should be formulated and suitable sampling   procedure should be adopted.

Practice Question

The difference between a statistic and parameter is called

A. Probability

B. Sampling error

C. Random

D. Non-random.

Solution: B

Worried About the Upcoming UGC Examination. You can Check out our Free & Paid Online Courses for UGC NET Commerce & Management here:
https://courses.everstudy.co.in/s/store