Introduction
Designing of the research is done mainly to solve the problem of getting the various stages of the research under control. This control factor is very important for the researcher during any of the research operation. Preparation of the design for the research forms a very critical stage in the process of carrying out some research work or a research project.

Research Design in general terms can be referred to as the scheme of work to be done or performed by a researcher during the various stages of a research project.

With the help of the research design, one can very easily handle and operate research work as research design acts as a working plan, which is made by a researcher even before he starts working on his research project. By this, researcher gets a great help and guidance in achieving his aims and goals.

According to Russell Ackoff, research design is the process of making decisions before a situation arises in which the decision has to be carried out. It is actually a process of deliberate anticipation directed towards bringing an unexpected situation under control.

Russell Ackoff has in a great way explained about the research design in his book ‘Designs of Social Research’.

Meaning of research design
Like an architect prepares a blue print before he approves a construction – in the same way researcher makes or prepares a plan or a schedule of his own study before he starts his research work. This helps the researcher to save time and also save some of his crucial resources. This plan or blue print of study is referred to as the research design.

Research design is also called as the research strategy and the various steps or stages that a research design may include can be summarized as follows –
1. Research problem selection
2. Problem presentation
3. Hypothesis formulation
4. Conceptual clarity
5. Methodology
6. Literature survey
7. Bibliography
8. Collection of the data
9. Hypothesis testing
10. Interpretation of the result
11. Report writing

This specific presentation of the various steps in the process of research was given by Cook Jahoda.

Factors affecting research design
1. Availability of scientific information
2. Availability of sufficient data
3. Time availability
4. Proper exposure to the data source
5. Availability of the money
6. Manpower availability
7. Magnitude of the management problem
8. Degree of Top management’ s support
9. Ability, knowledge, skill, technical understanding and technical background of the researcher
10. Controllable variables
11. Un – controllable variables
12. Internal variables
13. External variables

Advantages of research design
1. Consumes less time.
2. Ensures project time schedule.
3. Helps researcher to prepare himself to carry out research in a proper and a systematic way.
4. Better documentation of the various activities while the project work is going on.
5. Helps in proper planning of the resources and their procurement in right time.
6. Provides satisfaction and confidence, accompanied with a sense of success from the beginning of the work of the research project.

Introduction and definition of scientific method
Research has been observed to play a very essential role not only in the general management but also in the various functional fields related to the management. This type of research in typical language is very often referred to as the Managerial research. This type of research acts as a great tool for the scientific methods hence now we will have a look and will try to understand the scientific methods.

According to George A. Lundberg, scientific method can be defined as the “method which consists of the systematic observation, classification and the interpretation of the data the main difference between our day to day generalization and the conclusions usually recognized as a scientific method lie in the degree of the formality, rigorousness, verifiability and the general validity of the later.”

Scientific method is a method, which is very systematic in nature and plays a very critical role in the field of investigation, evaluation, experimentation, interpretation and theorizing.

This type of method is also very effective in the cases of physical sciences as the various physical phenomenon can be easily verified and also evaluated but in case of the managerial factors (e.g. behavioral factors of an organization) cannot be absolutely verified and evaluated physically.

All this affects the scope of the scientific methods, so it can be said that the scientific methods are not able to verify and evaluate all the management related problems empirically. Also the scientific method affects the working schedule as it very greatly increases the demand for the time, resources, exposure and also the man – powers.

Characteristics of scientific method
1. Is a very systematic method, offering convenient working.
2. Helps in obtaining very accurate classification of facts.
3. This method is marked by the observation of heavy co relation and sequence.
4. Helps in the discovery of the scientific laws.
5. Depends and aims at achieving actual facts and not the desired ones.
6. Relies on the evidence.
7. Has a definite problem for solving, as every inquiry has a specific sense.
8. Results drawn from the scientific method are capable of being observed and then measured.
9. It links and tries to establish very general propositions.
10. Scientific results can be estimated with sufficient accuracy.
11. Scientific conclusions are very true in nature and working.
12. Observer’s own views find no place during the observation as the observation is made in a very true form.

The collection of the data is followed by the analysation of the data, which further is followed by the interpretation of the data. This step enables the researcher to interpret the results which have been obtained from the analysation of the data.

According to C. William Emory, “Interpretation has two major aspects namely establishing continuity in the research through linking the results of a given study with those of another and the establishment of some relationship with the collected data. Interpretation can be defined as the device through which the factors, which seem to explain what has been observed by the researcher in the course of the study, can be better understood. Interpretation provides a theoretical conception which can serve as a guide for the further research work”.
Interpretation of the data has become a very important and essential process, mainly because of some of the following factors –

1. Enables the researcher to have an in – depth knowledge about the abstract principle behind his own findings.

2. The researcher is able to understand his findings and the reasons behind their existence.

3. More understanding and knowledge can be obtained with the help of the further research.

4. Provides a very good guidance in the studies relating to the research work.

5. Sometimes may result in the formation of the hypothesis.

In this step, the data which is collected is arranged according to some pattern or a particular format and this analysation of the data is mainly done to provide the data with a meaning.

In the beginning the data is raw in nature but after it is arranged in a certain format or a meaningful order this raw data takes the form of the information. The most critical and essential supporting pillars of the research are the analysation and the interpretation of the data.

Both these aspects of the research methodology are very sensitive in nature and hence it is required that both these concepts are conducted by the researcher himself or under his very careful and planned supervision. With the help of the interpretation step one is able to achieve a conclusion from the set of the gathered data.

Analysis of the data can be best explained as computing some of the measures supported by the search for relationship patterns, existing among the group of the data.

Research depends a great deal on the collected data but it should be seen that this collected data is not just a collection of the data but should also provide good information to the researcher during the various research operations. Hence to make data good and meaningful in nature and working, data analysis plays a very vital and conclusive role. In this step data is made meaningful with the help of certain statistical tools which ultimately make data self explanatory in nature.

According to Willinson and Bhandarkar, analysis of data ‘involves a large number of operations that are very closely related to each other and these operations are carried out with the aim of summarizing the data that has been collected and then organizing this summarized data in a way that helps in getting the answers to the various questions or may suggest hypothesis.’

Purpose of Analysis of data
The purpose of the scientific analysis was first explained by Leon Festinger and Daniel Katz and according to both of them; the purpose of the analysis of the data can be explained as follows –

1. Should be very productive in nature, with high significance for some systematic theory.
2. Should be readily disposed to the quantitative treatment.

Procedure for the Analysis of the data

Data collected can be used in the best possible effective manner by performing the following activities –
1. Carefully reviewing all the data collection.
2. Analyzing the data then with the help of certain suitable techniques.
3. Results obtained from the analysation of the data should then be related to the study’s hypothesis.

Analysation Steps
The various steps of the analysation of the data were given by Herbert Hyman and can be summarized as follows –

1. Tabulation of the data after conceptualization, relating to every concept of the procedure is done which ultimately provides an explanation based on the quantitative basis.

2. Tabulation in the same way is carried out for every sub group, which gives quantitative description.

3. To get statistical descriptions consolidating data for different aspects is brought into use.

4. Examination of such data is then done, which helps in improving the evaluation of the findings.

5. Different qualitative and non statistical methods are brought into the use for obtaining quantitative description but only if it is needed.

Types of Analysis
1. Descriptive Analysis –
• Also referred to as the One Dimensional Analysis.
• Mainly involves the study of the distribution of one variable.
• Depicts the benchmark data.
• Helps in the measurement of the condition at a particular time.
• Acts as the prelude to the bi – variate and multivariate analysis.
• Such an analysis may be based on the one variable, two variables or more than two variables.
• Helps in getting the profiles of the various companies, persons, work groups etc.

2. Casual analysis –
• Also referred to as the Regression Analysis.
• Has their root in the study of how one or more variables affect the changes in the other variable.
• Explains the functional relationship between two or more variables.
• Helps in experimental research work.
• Explains the affect of one variable on the other.
• Involve the use of the statistical tools.

3. Co – Relative Analysis –
• Involves two or more variables.
• Helps in knowing correlation between these two or more variables.
• Offers better control and understanding of the relationships between the variables.

4. Inferential Analysis –
• Involves tests of significance for the testing of the hypothesis.
• Helps in the estimation of the population values.
• Helps in the determination of the validity data which can further lead to draw some conclusion.
• Takes an active part in the interpretation of the data.

Introduction
After the collection of the data has been done, it has to be then processed and then finally analyzed. The processing of the data involves editing, coding, classifying, tabulating and after all this analyzation of the data takes place.

Data Processing
The various aspects of the data processing can be studied as follows

1. Editing of data: – This aspect plays a very vital role in the detection of the errors and omissions and then helps to correct these errors. By this step, there occurs a large amount of increase in the degree of accuracy, consistency and homogeneity. By this method, coding and tabulation of the data is done and also scrutiny in a very careful manner of the completed questionnaires takes place.

Editing of the data can be done in the following two stages:-

• Field Editing – In this step, the reporting firms are reviewed by the investigator and then the translation of what the latter has noted in the abbreviated form takes place. This stage of editing, views writing of the individuals and proper care is taken during this step, in order to avoid correction of the errors simply by the guess work.

• Central Editing – This step is done after the completion and the return of all the forms of schedules to the headquarters. In this type of editing, edition of all the forms is done carefully and thoroughly by a single person only in a small study and by a small group of persons in case of a large study. The errors may be corrected by the editor and he should be aware of the various instructions and the codes that are given to the interviewers while editing.

2. Coding of Data: – This step involves assignment of some symbols, either alphabetical or numerals or both, to the answers.By doing this coding of the data, analysation of the data can be performed in a much efficient manner but a very vital point to be kept in mind here is that there should be no errors while assigning the codes or should be at the minimum possible level.

3. Classification of Data: – The step of classification in general terms can be defined as the arrangement of the data into groups and classes depending on the resemblance and the similarities. With the help of the classification of the data, the entire data can be condensed and this condensation can be done in such an elegant way that the various important characteristics can be very easily noticed. The various features of the variables can be compared and the data in a tabular form can be prepared.
With the classification of the data, one can highlight the salient characteristics of the data at a glance.

Types of Classification –
a. Geographical Classification – Here classification of data takes place on the basis of a particular area or a particular region. For e.g. when we consider production of wheat state wise, this type of classification refers to the geographical classification.

b. Chronological classification – This type of classification involves classification of the data on the basis of the time of its occurrence.

c. Qualitative classification – Here classification of data takes place on the basis of some of the features, which are not having the ability of measurement. In a dichotomous or a simple type of the classification the division of the attribute or the feature takes place and two classes are formed after the division. One has the ability of possessing the attribute while the other does not possess the attribute.

d. Quantitative classification – In quantitative classification, the classification is done based on the attributes or the features that can be measured. Quantitative data can be further divided into two stages, namely discrete and continuous.

For a classification to be good in nature and working, it must possess the following set of features –

1. Data should be classified in such a way that it can be easily altered or changed with time, depending on the various situations and environment.

2. Classification of the data should be such that the data should be objective oriented.

3. A classification should never be rigid in nature, as in the case of the presence of rigidity, the classification of the data will not be able to correct the results.

4. Data classification should always be simple in nature and should also be very clear.

5. Should also be homogeneous i.e. data being kept in a particular class should be homogeneous in nature.

6. Stability forms a very major and a critical feature that should be present in a classification for it to be a good one. Stability in classification can be only achieved if minimum numbers of the changes are done in the data.

4. Tabulation of the Data – Classification of the data and the tabulation of the data have been observed to be interrelated. In this step of the tabulation of the data, data after it has been classified is then arranged in the form of the tables.

In general terms, it can be said that the tabulation of the data involves orderly arrangement of the data in columns and the rows and this step takes place after the classification of data has been done.
This step acts as the final step in the collection and compilation of the data and tabulating helps a great deal in the condensation of the data and also in the analysation of the relations, trends etc.. Tabulation can be of two types simple or complex.

Simple tabulation has the ability to answer questions based on one characteristic of the data while in the case of the complex tabulation two way tables or the three way tables are obtained two way tables are those which are having the ability to give information about two characteristics of the data and in the same way the three way tables are those which give information about three features of the data. But a very essential point to be kept in mind here is that in both these tables the characteristics should be interrelated.

Characteristics of a table –
1. Should be given a particular number, distinct in nature which will help in its easy reference.
2. Should have a clear and concise title and the title should always be above the body of the table.
3. Should be given captions and stubs, which should be clear and concise and easy to follow.
4. Units of measurements that may be used should always be indicated.
5. Should be relevant to the requirements of the research study.
6. Should be logical, clear and simple.
7. No abbreviations should be used.
8. Information about the source from where the data has been taken should be provided at the bottom of the table.
9. Should be very accurate in nature.
10. Explanatory footnotes with the help of reference symbols should be provided beneath the table.

Types of table –
1. Frequency table – This type of table is the simplest of all the other types of the table. This type of the table consists of the two columns. In one column, qualities or values of the different attributes are entered and in the other column, frequency of the occurrence against each category is entered.

2. Response table – In this type of the table, an answer table by the informant is recorded and this type of table involves the indication of the reaction in a positive or a negative manner.