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.

1. Explanatory or Descriptive hypothesis – This type of the hypothesis generally involves data about the cause of the process or about the law on which it is based. Hypothesis involving data about the cause is explanatory in approach and the hypothesis involving laws acts descriptive in the approach.

2. Tentative hypothesis – Such a hypothesis is made, when one does not possess complete information and understanding about a certain process or phenomenon. Such a situation, when one is not able to understand the process may occur due to the technical difficulties. It is also possible to test two or more hypothesis simultaneously the hypothesis about the propagation of light, namely, wave theory and the corpuscular theory of light both describe the light’ s phenomenon but among both of these none of them is final hence these can be referred to as tentative in nature.

3. Representative fictions – Some hypothesis are based on the assumptions and depending on the nature of the case, it is not at all possible to prove these assumptions by the direct means such hypothesis is referred to as the representative fictions. The only positive point of these representative fictions is that they are very suitable in order to explain the whole phenomenon.

Problems faced during hypothesis formulation
Formulating a hypothesis is not at all an easy process and is faced with a large number of difficulties. According to Goode and Hatt, the various difficulties faced during the formulation of the hypothesis generally include the lack of the knowledge about the scientific approach of the method involved, as sometimes it becomes impossible to gather the complete information about a particular scientific method. One other major difficulty in the formulation of the hypothesis is the lack of clear theoretical background. Because of this problem of unclear and indefinite background of theory one is not able to arrive to a conclusion easily.

But with time answers to all such problems are available and these difficulties that arise during the hypothesis formulation can be easily removed by having complete and accurate information about the concepts of the subjects involved. Also the hypothesis should not be very long and should be timely in nature.

Introduction and Definition
Science mainly consists of two main factors on which its working depends first is the body of the knowledge and the other one is the method of the inquiry. The body of knowledge involves the various laws, theories, hypothesis etc. and the other factor of inquiry methodology consists of the various mechanisms that help a great deal in the addition of the theories etc to the body of the knowledge.

Hypothesis and the theories are generally responsible for the movement of knowledge from the unknown to the known. Hypotheses play a very important and a critical role in the assertion of a particular thing, as they are able to describe certain facts and are also able to explain the various relationships between these facts. As a result of this, hypotheses help a great deal in the investigation operations or activities.

On the institution of the problem to be answered in the process of the research, the researcher forms various tentative or possible solutions to these problems these proposed answers or the solutions are referred to as the hypothesis. But a very critical and essential point to be kept in mind here is that these propositions are not at all verified in nature.

So Hypothesis can be referred to as the interpretation of certain facts which is just a possible solution or a tentative answer to a problem and is completely or partly unverified in nature. Then afterwards on its establishment, it ceases to be a hypothesis and then finally becomes a theory or a principle. The word ‘Hypothesis’ has come from the Greek word hypo (means under)and tithenas (means to place) together these words indicate towards the support they provide to each other on the placement of the hypothesis under the evidence, which acts as a foundation.

According to George A Luniberg, hypothesis can be defined as a ‘tentative generalization, the validity of which remains to be tested. In this elementary stage, the hypothesis may be very hunch, guess, imaginative data, which becomes the basis for an action or an investigation.’

A very vital point that should be kept in mind about the hypotheses is that these are not theories these only have some linkage to the theory but hypothesis is not that much elaborated as the theory is. But it can be said that the hypothesis is derived from the theory.

Role and Functions of the hypothesis
1. Helps in the testing of the theories.
2. Serves as a great platform in the investigation activities.
3. Provides guidance to the research work or study.
4. Hypothesis sometimes suggests theories.
5. Helps in knowing the needs of the data.
6. Explains social phenomena.
7. Develops the theory.
8. Also acts as a bridge between the theory and the investigation.
9. Provides a relationship between phenomena in such a way that it leads to the empirical testing of the relationship.
10. Helps in knowing the most suitable technique of analysis.
11. Helps in the determination of the most suitable type of research.
12. Provides knowledge about the required sources of data.
13. Research becomes focused under the direction of the hypothesis.
14. Is very helpful in carrying out an enquiry of a certain activity.
15. Helps in reaching conclusions, if it is correctly drawn.

Sources of hypothesis
1. Observations made in routine activities.
2. Theories based on the scientific approach.
3. Analogies.
4. Knowledge obtained from the functional executives.
5. Results of the research and development department.
6. Experience of the investigator.

Characteristics of hypothesis
1. Should be very specific in nature.
2. Concept of the hypothesis should be clear.
3. Should be empirically testable.
4. Should be related to the devices and the techniques that are available.
5. Should relate to the body of the theory.
6. Should recognize the specific variables and their relations.

Introduction
Data mining can be defined as a tool, helping automatically in the discovery of the various patterns and the relationships in a data warehouse. With the help of the data mining, managers are able to find the various relations between the elements of the business and the find out concepts of the business. Hence, it can be said that data mining extracts trends and rules from data warehouse helping in the evaluation of the business strategies ultimately leading to the improvement in the various business operations.

Data mining very commonly is known as the knowledge discovery database and the various important results that it helps in achieving can be summed up as follows –
a. Discovery of the new associations.
b. Deviation detection.
c. Event clustering.
d. Pattern recognization.
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1. Casual and Scientific observation – An observation can be sometimes casual in nature or sometimes it may act scientifically. An observation with a casual approach involves observing the right thing at the right place and also at the right time by a matter of chance or by luck whereas a scientific observation involves the use of the tools of the measurement, but a very important point to be kept in mind here is that all the observations are not scientific in nature.

2. Natural Observation – Natural observation involves observing the behaviour in a normal setting and in this type of observation, no efforts are made to bring any type of change in the behavior of the observed. Improvement in the collection of the information and improvement in the environment of making an observation can be done with the help of natural observations.
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