Sampling and Sampling Distributions

NB: We do not resell your papers. Upon ordering, we do an original paper exclusively for you.

NB: All your data is kept safe from the public.

Sampling is one of the main concepts that are used in modern statistics. This process can be described as the selection of elements from a certain set in which elements have some common qualities. This activity is based on the assumption that it is possible to understand the properties of a certain population by examining a part of this population (Allen 51).

This is the main premise that statisticians rely on. One should bear in mind that in this context the term population is applied not only to a certain group of people. It is used to describe a collection of entities, for example, automotive parts, households, products, or any other elements (Allen 51). Thus, one can say that this concept is applicable to various fields. This is one of the main issues that should be considered. Overall, researchers should take several steps in order to ensure the validity of their studies.

In particular, they should identify the characteristics of the population and choose the elements that have these characteristics. For example, one can speak about age, gender, occupation, marital status, and so forth. This strategy is particularly applicable to various demographic studies. However, the choice of these characteristics normally depends on the research questions that should be addressed. These are some of the main aspects that should be discussed.

It should be kept in mind that sampling is one of the most widespread techniques that are used in various sciences. For example, one can mention psychology, sociology, biology, material science, and many other academic fields. This technique began to be used in the nineteenth century, especially in demographic studies.

Nevertheless, in the twentieth century, various statistical tools became more sophisticated (Stigler 5). At present, the notion of sampling is widely used in various studies. Moreover, this technique can be applied in non-academic fields. For example, it is widely applied in various manufacturers. This is one of the reasons why this concept attracts close attention of many professionals.

Researchers should take into account that there are sampling errors that can undermine the validity of a study. In other words, they should ensure that the results derived in the course do not deviate from the tendencies that can be observed in the entire population. Provided that this precaution is not taken, the study of a sample can give an inaccurate description of the entire population. Apart from that, one should speak about such a concept as sampling distribution.

This notion can be described as the quantitative value of some attribute that can be used to characterize a population. For example, it is possible to mention such attributes as age, income level, or even attitudes of people. One should bear in mind that this probability distribution is usually based the study of a random sample (Allen 51). In this way, a researcher can gain an idea about the properties of the population or its behavior.

One should remember that sampling distribution lays the foundation for the so-called statistical inference. As it has been said before, a scientist can deduce the properties of the entire set by looking at its different elements or subsets. Apart from that, researchers rely on various tests which can demonstrate whether the results of the study are valid. These confidence tests can help a researcher to strengthen the validity of a study. This is one of the main points that can be made.

There is another issue that should be taken into account by people who use statistical methods. In particular, one should mention the estimation of sample size. It has to be representative of the entire population; otherwise the sample distribution cannot be called accurate. Additionally, much attention should be paid to the sampling methods that can be used. For example, researchers can select a sample in a random or systemic way.

The choice of strategies is also dependent on the goals that a scholar intends to attain. Thus, it is possible to argue that a person, who examines statistical data, should consider a great number of factors in order to gain accurate data. These issues should be considered by researchers.

Admittedly, the use of sampling distribution can provide only an approximate description of different phenomena. They cannot be used to understand every aspect of a certain population. Sometimes, it is necessary to conduct longitudinal studies in order to detect the changes in the properties of a population. Nevertheless, these tools can still be used to scientists who may study social, economic, or psychological phenomena. This is one of the main arguments that can be put forward.

On the whole, this discussion indicates that sampling and sampling distribution play an important role in modern statistics. It is critical for understanding the properties of a specific population. This technique is applicable to various fields in which it is necessary to analyze different kinds of quantitative data. At present, such concepts as sampling and sampling distributions play an essential role in the design of the research methodology.

Works Cited

Allen, Michael. Understanding Regression Analysis, New York: Springer, 2004. Print.

Stigler, Stephen. Statistics on the Table: The History of Statistical Concepts and Methods, Cambridge: Harvard University Press, 2002. Print.

Click Here To Order Now!

Sampling and Sampling Distributions

Do you need this or any other assignment done for you from scratch?

We have qualified writers to help you.

We assure you a quality paper that is 100% free from plagiarism and AI.

You can choose either format of your choice ( Apa, Mla, Havard, Chicago, or any other)