Report/Thesis Preparation

After the research process, the researcher is required to prepare a report in order to present details about his research work. He may refer the target journal or university guidelines on how to prepare a report, but certain general points need to be considered while writing a report/thesis:

  1. The layout of a report should basically consist of:
  • Preliminary pages – These pages include the title of the report, the date, acknowledgements, and foreword. Then, it contains a table of contents followed by a list of tables and a list of graphs and charts, if any.

 

  • Main text – The main text of the report should have the following:

Introduction: This section includes brief details about objectives of the research, methodologies adopted, scope as well as limitations of the study.

Summary of findings: After Introduction, statement of findings and recommendations is provided in non-technical language.

Main report: Here, the main details of the research are presented logically in a sequence of easy-to-identify subsections.

Conclusion: At the end of the main text, the researcher should sum up his findings and results clearly and precisely.

 

  • End matter – Finally, appendices for technical data and bibliography (i.e., list of consulted books, journals, reports, etc.) should be provided in the end. Index can also be given specially in a published research report.

2.  Writing style should be concise, objective and in simple language, while avoiding vague terms such as it seems, there may be, and the like.

3.  Charts and illustrations should be used in the report only if they provide clear and precise information.

4.  Calculated confidence limits and constraints faced during the research process may also be mentioned in the report.

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The Research Process

Hypothesis Testing

Once the data analyzing process is complete, the researcher is ready to test the hypothesis, which was formulated earlier. Hypothesis testing involves systematic methods, which are used to evaluate the data and aid the decision-making process. Various statistical measures are used to test the data: parametric analysis (Ttest, ANOVA, Regression, etc.) and non-parametric analysis (ChiSquare, Kruskal Wallis, Mann“Whitney, etc.). These testing methods differ depending on the types of measurements and tools used for those measurements. One must choose the appropriate statistical method in order to obtain meaningful results. Based on the results of the calculations, hypothesis testing will result in either the hypothesis being accepted or rejected. The hypothesis is ruled out or modified if its predictions are incompatible with the experimental tests.

 

Generalizations and Interpretation

This is the final stage of the scientific research process. While testing, if the hypothesis is upheld several times, the researcher may form generalizations, i.e., build theories based on it. Generalizations give an indication of the actual achievement of the researcher. In case, the researcher had no hypothesis while starting the experiment he tries to explain his findings on the basis of some already established theory. This is known as interpretation. It is a process, which makes it easier to understand the factors that explain what was observed by the researcher during the course of his study. It also provides a theoretical conception, which serves as a guide. Interpretation may lead to new questions, thus leading to further researches.

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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.

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Execution of the Project

After the researcher has collected the data, the next step in the research process is the execution of the project (i.e., implementation phase of the project). This step is very important in the research process as it ensures that the research is being executed systematically and in time. If the execution of the research proceeds on correct lines, then the collected data would be adequate and dependable. If structured questionnaires are to be used for the survey, then data, i.e., both questions and the possible answers, may be machine-coded for easy and convenient usage. If interviewers are to collect data, then they should be accordingly selected, and proper training should be given to them. The researcher should ensure that the survey is under statistical control, i.e., the collected information is in agreement with the pre-defined standard of accuracy.

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Collecting the Data

Collecting data forms a key aspect of any type of research study. Data are mainly collected to obtain information regarding a specific topic. These data can be documented for future use, can be shared as information, and help in making decisions about important issues. Inaccurate data collection can have a negative impact on the results of a research study, and eventually make the study invalid. The primary data that is collected should be relevant to the study and research problem. Primary data can be collected either through experiments or through surveys.

EXPERIMENTS

In this, an independent variable is changed or manipulated to see how it affects a dependent variable, keeping in control the effects of some extraneous variables. Here, the emphasis is on specific hypotheses about the influence of one variable over another. There are two types of experiments:

  • Laboratory Experiments: Here the variables are manipulated and measured in an artificial setting.
  • Field Experiments: Here the variables are manipulated and measured in a natural setting.

SURVEYS

Surveys are generally used to know about the trends in opinions, experiences, and behavior of people. It includes the following methods:

  • Observation: It is a fundamental and highly important method in all qualitative inquiry. In this case, the researchers take note of peoples behavior, objects, etc. through their own investigations without interviewing or communicating with them. Observation as a method includes both seeing and hearing. The obtained data is relevant to the present only. It is not complicated by the past behavior or future attitudes of the participants. But, this method has its limitations. It can be used only when there are fewer participants. Also, the information gathered is very limited.
  • Interviews: This is particularly used when detailed information is required from certain people. The one-to-one interviews yield the highest response rates in survey research. To get the best results, the researcher needs to establish rapport with potential participants by gaining their confidence. The researcher first puts forth a few general topics to uncover the participants views, and then goes ahead with systematic questioning pertaining to the research topic. It depends a lot on the skills of the interviewer. But, these interviews can yield biased results also: the interviewer may misinterpret some response; the interviewee may not give his/her true opinion or avoid difficult questions; the interviewer might unintentionally provoke the interviewee; the surroundings might be creating discomfort to the interviewee, etc. It is also very time consuming. This method includes two types of interviews: Personal and Telephonic.
  • Questionnaires: A questionnaire is a set of systematically structured questions used by a researcher to obtain the required information from the participants. It may include check lists, attitude scales, projective techniques, rating scales and a variety of other research methods. Questionnaires can be paper-based or electronic. Through this method, accurate and relevant data can be obtained very quickly and easily. Participants feel free to respond as they remain anonymous. But, at the same time, data processing and analyzing for large number of responses can be time consuming.
  • Schedules: Schedule is a set of questions, which are asked and filled by the interviewer or enumerators in a face-to-face situation. The specially appointed enumerators go to the respondents, put forward their questions and record their responses. They also explain the objective of the research, and clear doubts regarding the questions, if any. This method is very useful for extensive enquiries. It is usually adopted by governmental agencies or big organizations. Population census is usually done through this method.
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