Characteristics of a Good Sample Design

In a field study due to time and cost involved, generally, only a section of the population is studied. These respondents are known as the sample and are representative of the general population or universe. A sample design is a definite plan for obtaining a sample from a population. It refers to the technique or the procedure for obtaining a sample from a given population.

Following are the characteristics of good sample design:

1. Sample design should be a representative sample: A researcher selects a relatively small number for a sample from an entire population. This sample needs to closely match all the characteristics of the entire population. If the sample used in an experiment is a representative sample then it will help generalize the results from a small group to large universe being studied.

2. Sample design should have small sampling error:  Sampling error is the error caused by taking a small sample instead of the whole population for study. Sampling error refers to the discrepancy that may result from judging all on the basis of a small number.Sampling error is reduced by selecting a large sample and by using efficient sample design and estimation strategies.

3. Sample design should be economically viable: Studies have a limited budget called the research budget. The sampling should be done in such a way that it is within the research budget and not too expensive to be replicated.

4. Sample design should have marginal systematic bias: Systematic bias results from errors in the sampling procedures which cannot be reduced or eliminated by increasing the sample size. The best bet for researchers is to detect the causes and correct them.

5. Results obtained from the sample should be generalized and applicable to the whole universe: The sampling design should be created keeping in mind that samples that it covers the whole universe of the study and is not limited to a part.


Features of a Good Research Design

When a researcher has formulated a research problem, he/she has to focus on developing a good design for solving the problem. A good design is one that minimizes bias and maximizes the reliability of the data. It also yields maximum information, gives minimum experimental error, and provides different aspects of a single problem. A research design depends on the purpose and nature of the research problem. Thus, one single design cannot be used to solve all types of research problem, i.e., a particular design is suitable for a particular problem.

A research design usually consists of the following factors:

(i) The means of obtaining information;

(ii) The availability and skills of the researcher and his staff, if any;

(iii) The objective of the problem to be studied;

(iv) The nature of the problem; and

(v) The availability of time and money for the research work.

If a research study is an exploratory or formulative one, i.e., it focuses on discovery of ideas and insights, the research design should be flexible enough to consider different aspects of the study. Similarly, if the study focuses on accurate description or association between variables, the design should be accurate with minimum bias and maximum reliability. However, in practice, it is difficult to categorize a particular study into a particular group. A study can be categorized only on the basis of its primary function and accordingly, its design can be developed. Moreover, the above mentioned factors must be given due weightage while working on the details of the research design.


Data Analysis

The very first task of the researcher, after the collection of data, is to analyse them. The process of data analysis demands a variety of closely related operations, namely:

  • The establishment of different categories,
  • The application of these categories to the raw data through coding,
  • Making tabulations and then drawing statistical inferences.


The unmanageable data should be, necessarily, condensed into a few manageable groups and tables to develop the chances of further analysis. Therefore, for this reason, the researcher should classify the collected raw data into some purposeful and usable categories. Usually at this stage, the Coding operation is conducted, which transforms the categories of data into symbols that may be arranged in a tabular form and then counted.


The quality of the data is improved and polished by the procedure of editing. The thus improved data is then coded, and is made ready for tabulation. Tabulation is that part of the technical procedure where the classified data are arranged in the form of tables. Computers are a great help in this area of research. Especially in the cases of large inquiries, a great deal of data is tabulated by the computers. This procedure not only helps in saving time, but also makes it possible to study a large number of variables affecting a problem simultaneously. After the process of tabulation, the analysis work is generally done by the computation of various percentages, coefficients, etc., by employing various well-defined statistical formulae.


During the process of data analysis, relationships or differences supporting/conflicting with the original or new hypotheses should be subjected to tests of significance, in order to determine with what validity the data can be said to indicate any conclusion/s. For example, take the samples of two monthly wages, each of the samples being drawn from the companies located in different parts of the same town. Now, if the samples give two different mean values, then our problem will be concerned about whether the two mean values are genuinely different, or the difference is just a matter of chance. By using the methods of statistical tests, we can find whether such a difference is an authentic one, or is merely the result of some random fluctuations. If the difference was found to be valid, then it can be concluded that the two different samples came from two different universes. On the other hand, if the difference was found to be due to by chance, then it can be concluded that the two different samples came from the same universe. Similarly, the technique of variance analysis can help us to analyse whether three or more varieties of plants, harvested on specific fields, yield considerably different results or not. Hence, we can conclude that the researcher can analyse his/her collected data with the help of various statistical measures. Now it is up to the researcher, which analysis technique will he/she find most appropriate for his data analysis.


Writing Research Papers

A research paper may contain original research results or reviews of existing results. In either case, you are documenting the results of your investigations on a selected topic. A research paper is your unique creation, based on your own thoughts and the facts and ideas you have gathered from a variety of sources. Writing a research paper needs the experience of assembling, interpreting, and documenting information along with developing and organizing ideas and conclusions. You might have investigated a topic deeply and might have spent months or years in obtaining novel results, but, unless you communicate your work clearly in your research paper, the readers will not be able to understand the intent of your hard work. The ability to accumulate, scrutinize and present large amounts of complex information in a summarized form is a skill that can bring you immense satisfaction as a researcher.

The intention of documenting a research paper is to let people study your work selectively. Here are certain tips that you can follow before you begin to jot down your hard work in your paper.

Rough draft

Before you begin writing anything, the most important thing to do is to outline your work. Pen down everything that is in your mind and keep adding to the draft until you think there is hardly anything left out. Include all the information that you feel is important and relevant. Once you are done with the rough draft, check for completeness and accuracy of facts. Your outlined work will give you a clear picture of what to include, what not to include, and how to arrange all the facts and figures in a proper format in your paper.


The title is the first thing that readers will look at in any paper. The title of your research paper should be precise, informative and relevant with the study performed. In short, a title itself should give readers an idea about the research done.


The abstract tells the reader about the intent and importance of your research. It is usually 250-300 words long. Your abstract will tell the readers of what you have done, how you did it, the results obtained and what it implies. It is an overall summary of your research work performed. A research paper begins with an abstract, but you should always write it after you have finished writing the entire paper.


The introduction sets the stage for your analysis; therefore, it should be concise and definite. Describe the topic, and show how it fits into your field of study. Give a brief outline of the problem, describe its implications, its significance and justify the novelty of your study. State the objective of your study and describe the reasoning that led you to select them. Briefly discuss the experimental design and how it accomplished the stated objectives.

Literature Review

The literature review places your research in an appropriate framework.  It is a place to highlight relevant contributions associated with the study and to show how your contribution either fills the gaps or answers the unanswered questions. It may also create gaps in the knowledge of the readers by showing them that something they thought they knew is false. The theory part must focus on the logical reasons for why the readers should believe your hypothesis to be true.

Materials and Methods

This part must contain the details of the tools and procedures employed to fulfill the intent of your research. It must have enough information so that others can follow your procedure and can replicate it to hopefully come up with the same or additional findings and conclusions as you did.


You need to include all the relevant descriptive and numeric data in the form of facts and figures to present a clear picture of your findings. Utmost care should be taken while labeling these facts and figures and including their references throughout the paper.


In the discussion part, you can develop your arguments based upon your findings. The data may be self-explanatory; however, you will need to interpret how it validates your hypothesis, what falls outside of validity, how it impacts the literature you have cited, and the areas where further research is required. It also provides statistical, anecdotal, narrative, or descriptive evidences where and when required.


Summarize all the results in the conclusion part and explain very carefully and exactly what needs to be done next. It is likely that your conclusion will be uncertain.  However, a well-written conclusion will elucidate the next steps that need to be taken before the readers can be absolutely certain whether the research is complete or there is scope of further research on the same.


The most important element of any research paper is the references. Cite appropriate references where and when required, and verify the accuracy of your references before citing it.

Some Additional Tips

When you have finished writing the paper, take some time for yourself before you re-read it.

  • Make sure that your data and citations are accurate.
  • Reword your sentences for effectiveness of grammar, punctuation and composition.
  • Use a dictionary to check your spelling and use of words, or, run a spell check.
  • Read out the paper loudly to see how it flows and to correct any awkward sentences.