Sampling Errors

As per the sampling errors formula, it is regarded as a type of statistical error occurring when the analyst it not selecting any sample for representing the entire population data. In return, it is also the error that occurs when the results revealed in the sample are not representing the fact that the results are obtained from the complete set of population.

In an analysis, sampling is performed by choosing the number of observations from some larger population. The given choice can help in producing both non-sampling as well as sampling errors.

Getting an Understanding of Sampling Errors

A sampling error can be referred to as the deviation in the given sampled value in contrast to the true value of population. This generally occurs because the given sample does not serve to be the representative of the given population or might be biased in some manner. It is important to know that even randomized samples can result into sampling errors as it only represents the approximation of the population from which the samples have been obtained.

Sampling errors are easily eliminated when the given size of the sample would be increased. At the same time, the minimization can also occur by ensuring that the sample is appropriately able to represent the entire population. For instance, let us assume that the XYZ company is providing some subscription-based service –allowing consumers to make the monthly fee payment for streaming videos along with other programming across the Internet.

The organization might wish to survey the available homeowners who would be watching around 10 hours of streaming or programming across the internet every week and paying for the existing video programming or streaming service. XYZ might be looking forward to determining the specific percentage of population that might be interested in the low-valued subscription service. If XYZ is not thinking carefully about the given sampling process, then there might be the occurrence of several types of sampling errors.

Sampling Errors Formula

Here,

• Z is the score value for the given confidence interval,
• Alpha denotes the given population Standard Deviation, and
• n is the sample size

An error that is population-specific implies that the company is not getting an understanding of the particular consumer type who must be involved in the given sample. For instance, if XYZ goes ahead with creating a population of individuals between the age Range of 15 & 25 years, most of the consumers would not be making the purchasing decision about the video programming or streaming service as they might not be working full-time.

On the other hand, if the company would be putting together the sample of adults who are working and making purchasing decisions, then the consumers in the given group might not be watching 10 hours of video streaming on a weekly Basis.

Sampling errors might also result in distortions with regarded to the results of the given sample.