RESEARCH METHODOLOGY

Important topics

Research Methods And Research Methodology

Is there any difference between research methods and research methodology?

Quantitative and Qualitative Methods

The basic and applied researches can be quantitative or qualitative or even both. Quantitative research is based on the measurement of quantity or amount. Here a process is expressed or described in terms of one or more quantities.
The result of this research is essentially a number or a set of numbers. Some of the characteristics of qualitative research/method are:

• It is numerical, non-descriptive, applies statistics or mathematics and uses numbers.
• It is an iterative process whereby evidence is evaluated.
• The results are often presented in tables and graphs.
• It is conclusive.
• It investigates the what, where and when of decision making

Whereas Qualitative research is concerned with qualitative phenomenon involving quality. Some of the characteristics of qualitative research/method are:

• It is non-numerical, descriptive, applies to reason and uses words.
• it aims to get the meaning, feeling and describe the situation.
• Qualitative data cannot be graphed.
• It is exploratory.
• It investigates the why and how of decision making

Types of Sampling

We may then consider different types of probability samples. Although several different methods might be used to create a sample, they generally can be grouped into one of two categories: probability samples or non-probability samples.

Probability Samples

The idea behind this type is random selection. More specifically, each sample from the population of interest has a known probability of selection under a given sampling scheme. There are four categories of probability samples described below

• Simple Random Sampling
• Stratified Random Sampling
• Systematic Sampling
• Cluster Sampling

Nonprobability Sampling

Social research is often conducted in situations where a researcher cannot select the kinds of probability samples used in large-scale social surveys. For example, say you wanted to study homelessness – there is no list of homeless individuals nor are you likely to create such a list. However, you need to get some kind of a sample of respondents to conduct your research. To gather such a sample, you would likely use some form of non-probability sampling.

To reiterate, the primary difference between probability methods of sampling and non-probability methods is that in the latter you do not know the likelihood that any element of a population will be selected for the study.

There are four primary types of non-probability sampling methods:

• Availability Sampling
• Quota Sampling
• Purposive Sampling
• Snowball Sampling

Discuss sampling with merits and demerits

According to Rosander,

The sample has many advantages over a census or complete enumeration. If carefully designed, the sample is not only considerably cheaper but may give results which are just accurate and sometimes more accurate than those of a census. Hence a carefully designed sample may actually be better than a poorly planned and executed census.

Though sampling is not new, the sampling theory has been developed recently. People knew or Though sampling is not new, the sampling theory has been developed recently. People knew or not but they have been using the sampling technique in their day to day life.

For example, a housewife tests a small quantity of rice to see whether it has been well-cooked and gives the generalized result about the whole rice boiling in the vessel. The result arrived at is most of the times 100% correct.

Merits of sampling are:

• It saves time: Sampling method of data collection saves time because fewer items are collected and processed.
  When the results are urgently required, this method is very helpful.
• It reduces cost: Since only a few and selected items are studied in sampling, there is a reduction in the cost of money
  and reduction in terms of man-hours.
• More reliable results can be obtained: Through sampling, more reliable results can be obtained because
  • there are fewer chances of sampling statistical errors. If there is sampling error, it is possible to estimate and control the results.
  • Highly experienced and trained persons can be employed for scientific processing and
    analyzing of relatively limited data and they can use their high technical knowledge and get more
    accurate and reliable results.
• It provides more detailed information: As it saves time, money and labour, more detail information can be collected in a sample survey.
• Sometimes only sampling method to depend upon: Sometimes it so happens that one has to depend upon sampling method alone because if the population under study is finite, the sampling method is the only method to be used.
  • For example, if someone’s blood has to be examined, it will become fatal to take all the blood out from the body and study depending upon the total enumeration method.
• Administrative convenience: The organization and administration of the sample survey are easy for the reasons which have been discussed earlier.
• More scientific: Since the methods used to collect data are based on scientific theory and results obtained can be tested, sampling is a more scientific method of collecting data.

Demerits of sampling are:

• Illusory conclusion: If a sample enquiry is not carefully planned and executed, the conclusions may be inaccurate and misleading.
• Sample Not Representative: To make the sample representative is a difficult task. If a representative sample is taken from the universe, the result applies to the whole population. If the sample is not representative of
  the universe the result may be false and misleading.
• Lack Of Experts: As there is a lack of experts to plan and conduct a sample survey, its execution and analysis, and its results would be Unsatisfactory and not trustworthy.
• Sometimes More Difficult Than Census Method: Sometimes the sampling plan may be complicated and requires more money, labour and time than a census method.
• Personal Bias: There may be personal biases and prejudices concerning the choice of technique and drawing
  of sampling units.
• Choice Of Sample Size: If the size of the sample is not appropriate then it may lead to untrue characteristics of the population.
• Conditions Of Complete Coverage: If the information is required for every item of the universe, then a complete enumeration survey is better.

Reasons behind sampling errors

In statistics the word error is used to denote the difference between the true value and the estimated or approximated value. This error would always be there no matter that the sample is drawn at random and that it is highly representative

This error is attributed to fluctuations of sampling and is called sampling error. Sampling error exists because only a subset of the population has been used to estimate the population parameters and draw inferences about
the population.

Sampling errors are of two types: Biased Errors and Unbiased Errors

Biased Errors:
The errors that occur due to bias or prejudice on the part of the informant or enumerator in selecting, estimating measuring instruments are called biased errors.

Suppose, for example, the enumerator uses the deliberate sampling method in the place of simple random sampling method, then it is called biased errors. These errors are cumulative and increase when the sample size also increases.

These errors arise due to defect in the methods of collection of data, defect in the method of organization of data and defect in the method of analysis of data.

Unbiased Errors:

Errors which occur in the normal course of investigation or enumeration on account of chance are called unbiased errors.

They may arise accidentally without any bias or prejudice. These errors occur due to faulty planning of the statistical investigation.

To avoid these errors, the statistician must take proper precaution and care in using the correct measuring instrument. He must see that the enumerators are also not biased. Unbiased errors can
be removed with the proper planning of statistical investigations.

Both these errors should be avoided by the statisticians.
Sampling errors occur primarily due to the following reasons:

• Faulty selection of the sample: Some of the bias is introduced by the use of defective sampling technique for the selection of a sample e.g. Purposive or judgment sampling in which the investigator deliberately selects a representative sample to obtain certain results. This bias can be easily overcome by adopting the
  technique of simple random sampling.
• Substitution: When difficulties arise in enumerating a particular sampling unit included in the random sample, the investigators usually substitute a convenient member of the population. This leads to some bias since the characteristics possessed by the substituted unit will usually be different from those possessed by the unit originally included in the sample.
• Faulty demarcation of sampling units: Bias due to defective demarcation of sampling units is particularly significant in area surveys such as agricultural experiments in the field of crop cutting surveys etc. In such surveys, while dealing with borderline cases, it depends more or less on the discretion of the investigator whether to include them in the sample or not.
• Error due to bias in the estimation method: Sampling method consists of estimating the parameters of the population by appropriate statistics computed from the sample. Improper choice of the estimation techniques might introduce the error.
• Variability of the population: Sampling error also depends on the variability or heterogeneity of the population to be sampled.

Reference:
1. Dawson, Catherine, 2002, Practical Research Methods, New Delhi, UBS Publishers’Distributors
2. Kothari, C.R.,1985, Research Methodology- Methods and Techniques, New Delhi, Wiley Eastern Limited.
3. Kumar, Ranjit, 2005, Research Methodology-A Step-by-Step Guide for Beginners,(2nd.ed.), Singapore, Pearson Education.

4. RESEARCH METHODOLOGY S. Rajasekar School of Physics, Bharathidasan University, Tiruchirapalli – 620 024, Tamilnadu, India∗