Merits and Demerits of interview techniques

Interview method is the most popular method for collecting primary data. It is widely used in every fields or sectors. The interview technique is one of the important and powerful tool for collecting the primary data in social research. The technique involves presentation of oral-verbal stimuli and reply in terms of oral-verbal responses. It is a direct method of data collection. The interview technique can be used through personal interviews and through telephone interviews.

The major merits of interview technique can be summarized as:

•  More accurate information can be obtained.
• Personal information can as well be obtained easily under this method.
• Due to personal presence of the interviewer, there is flexibility in the inquiry.
• Additional supplementary information can also be obtained.
• The interviewer can usually control which person will answer the questions.
• Generally non-response remains very low in this method.
• Observation method can as well as applied to recording verbal answers to various questions.
• Representative and wider distribution of sample is possible by using the method.
• The interviewer contact the informants personally, they can exercise their intelligence, skill, tact etc. to extract correct and relevant information by cross examination of the information, if necessary.
• The language of the interview can be adopted to the ability or educational level of the person interviewed and as such misinterpretations concerning questions can be avoided.

Interview techniques have many  merits but it have also many demerits. The main demerits of this techniques are given below:

• It is a very expensive method, specially when large and widely spread geographical sample is taken.
• There remains the possibility of the bias of interviewer as well as that of the respondent.
• This method is relatively more-time consuming, specially when the sample is large.
• Certain types of respondents may not give true answers to the questions.
• The presence of the interviewer on the spot may over-stimulate the respondent.
• Training and supervising of the interviewers is more complex.
• Systematic errors may arise.

Primary Data: Sources of Data Collection

Depending upon the sources, mainly there are two types of data i.e. primary data and secondary data. Primary data are those data which are collected afresh and for the first time on the account of concerned investigation. The primary data is thus original in character. Researcher or his staff collects the necessary data from field of inquiry. In the initial stage, the primary

data are raw in nature. After collecting the data, they are presented, edited, tabulated and analyzed at the central office of the investigator. On the basis of analyzed data, specific conclusions of the investigation is made.

There are different methods of collecting primary data. The main methods of them are:

1. Observation Method
2. Interview Method
3. Information Through Correspondents
4. Mailed Questionnaire Method
5. Through Schedules
6. Other Methods

1. Observation Method: In this method, the data are gathered by investigator on observing some events as they occur without asking from the respondents. The investigator watched each and every activities of the concerned units and note them  for taking information. The concerned units may be people, animal, objects etc. This is the most commonly used method specially in studies relating to behavioral sciences and animal sciences. The observation methods are also further classified into (a) Participant and Non-participant Observation, (b) Structured and Unstructured Observation, (c) Controlled and Uncontrolled Observation, (d) Behavioral and Non-behavioral Observation.

2. Interview Method: The interview is perhaps the most popular method of primary data collection in social research. It has been and still used in all kinds of practical situations. It is the direct method of collection of data. The interview is probably man's oldest and most often used device for obtaining information. The interview technique is a verbal method of obtaining data related with the research problem. A person who asks questions is known as interviewer and a person who gives the reply of the questions is known as interviewee.

Interview method can be used as personal interview (direct or indirect), telephone interview, Internet interview, focus group interview etc. Generally there are two types of interviews. They are

1. Structured and Unstructured
2. Standardized and Unstandardized

Structured and standardized interview use a set of predetermined questions whereas unstructured and unstandardized interviews do not use predetermined questions. In the later case, the interviewer is allowed much freedom to ask supplementary questions if it is necessary. The unstructured, unstandardized interview is an open situation in contrast to the structured, standardized interview which is closed situation.

Types of sampling techniques

Non-Probability sampling techniques: This types of sampling techniques in which every unit of the population has not an equal chance of being included in the sample is known as non-probability sampling. The sample are selected on the basis of personal knowledge, opinion and discretion of the sampler. This type of sampling method is also known as non-random sampling. For the opinion surveys, this sampling method is mainly used. There are different types of non-probability sampling methods. They are:

1. Judgement or purposive sampling: In this method, the investigator selects sample items on his own judgement. The choice of selecting sample is nothing to left in chance in this method.
2. Convenience sampling: In this method, the samples are selected on the basis of the convenience of the investigator. It is also known as chunk sampling.
3. Quota sampling: In this method, the population is divided into different groups, known as quota. After doing this, the researcher collects information from quota. Quota sampling is the most systematic and scientific method in comparison with other non-probability sampling method.

Types of sampling techniques

Generally there are two types of sampling techniques which are described below:

1. Probability (Random) sampling technique
2. Non-probability (non-random) sampling technique

1. Probability (Random) sampling

A type of sampling technique in which every unit of the population has an equal chance of being selected in the sample is known as probability sampling. In this method, selection of the sample is based on the theory of probability. This type of sampling is also referred as random sampling. Here, the term random does not means the haphazard or without any purpose. It is a systematic process.

Probability sampling is further sub-divided in the following types:

a) Simple random sampling

b) Stratified sampling

c) Systematic sampling

d) Cluster sampling

e) Multi-stage sampling

1. Simple random sampling: The simplest and most common method of sampling is simple random sampling. In this method, each and every unit of the population has equal chance of being included in the sample. It is also sometimes referred as unrestricted random sampling.

If a unit is selected and noted and then returned to the population before the next drawing is made and this procedure repeated many times, gives to required to many sample. This procedure is generally known as simple random sampling with replacement (SRSWR). If the selected unit is not returned to the population before the next drawing is made, this is known as simple random sampling  without replacement (SRSWOR).

2. Stratified sampling: Stratified sampling is a type of restricted random sampling. In this technique, first the whole population is divided into homogeneous groups under certain criterion. These groups are called strata. Then the sample is drawn from each stratum. Proper care should be taken while making strata.

In stratified sampling, the allocation of the sample to different strata is done by the consideration of three factors: stratum size, the variability within the stratum and the cost in taking observations per sample in the stratum. A good allocation is one where maximum precision is obtained with minimum resources. Mainly there are four methods of allocation of samples sizes to different strata in a stratified sampling. There are equal allocation, propotional allocation, Neyman allocation and optimum allocation.

3. Systematic sampling: A sampling technique in which only the first unit is selected with the help of random numbers and the rest get selected automatically according to some pre-designed pattern is known as systematic sampling.

4. Cluster sampling: The entire population is divided into the smallest unit. A group of such unit is known as a cluster. When the sampling unit is cluster, the procedure is called cluster sampling. Generally the cluster sampling is used when the sampling frame for elementary units of the population is not available.

5. Multi-stage sampling: A type of sampling which consists in first selecting the clusters and then selecting a specified number of elements from each selected cluster is known as two-stage sampling. The selection procedure can extended to any number of stages. Hence, in general, it is known as multi-stage sampling. This type of sampling has been commonly used in large-scale surveys.