3. Research Methods and Analysis:
Research- It is a careful investigation inquiry specially through search for new facts in any branch of knowledge.
Redman and Mory define research as “Systemised effort to gain new knowledge”.
Broadly Research methods are divided into two types.
(a) Qualitative and quantitative methods.
Quantitative Methods – A type of social research which employs quantifiable techniques or use mathematical theories and modals for the social research to create a generalised hypothesis.
Eg. Correlation, Regression, Chi-square, Survey Research etc.
Qualitative methods – Qualitative methods emphasize understanding of social phenomena through direct observation, communication with participants, or analysis of texts, and may stress contextual and subjective accuracy over generality
Eg. Historical method, Life history, longitudinal study, Participant observation.
Four main methods used in sociological research
(a) Usually generates richer and more in depth information than other methods.
(b) Participant observation can provide a broader understanding of social processes.
(a) can only be used to study relatively small groups and communities.
(b) Findings might only apply to the groups or communities studied; it is not easy to generalize on the basis of single fieldwork.
(a) Make possible the efficient collection of data on large number of individuals.
(b)Allow for precise comparisons to made between the answers of respondents.
(a) The material gathered may be superficial where a question is highly standardised, important differences between respondents viewpoints may be glossed over.
(b)Responses may be what people profess to believe rather than what they actually believe.
Experiments – Strengths
(a)The influence of specific variables can be controlled by the investigator.
(b) Are actually easier for subsequent researchers to repeat.
(a) Many aspects of social life cannot be brought into the laboratory.
(b) The responses of those studied may be affected by the experimental situation.
(a) Can provide source of in depth materials as well as data on large numbers, depending on the types of documents studied.
(b)Is often essential when a study is either wholly historical or has a defined historical dimension.
(a) The researcher is dependant on the sources that exist, which may be partial.
(c)The sources may be difficult to interpret in terms of how far they represent real tendencies- as in the case of some official statistics.
(b) Techniques of data collection.
(i)By Observation- This method implies the collection of information way of investigator’s own observation.
(ii) Through personal interviews- The investigators follows the rigid procedure and seeks answer to a set of pre conceived questions through personal interviews.
(iii) Through telephonic interviews- This method of collecting information involves contacting the respondents on the telephone itself.
(iv) By mailing of the questionnaires- The respondents and the researcher do not come in contact with each other if this method of survey is adopted. Questionnaires are mailed to the respondents with a request to return it after completing the same.
(v) Through schedules- Under this method the enumerators are appointed and given training. They are provided with the schedules containing relevant questions. These enumerators go to respondents with these schedules. Data are collected by enumerators by filling up the schedules by enumerators on the basis of replies given by the respondents.
(c) Variables, sampling, hypothesis, reliability and validity.
In logic, an argument is valid if and only if its conclusion is entailed by its premises, a formula is valid if and only if it is true under every interpretation, and an argument form (or schema) is valid if and only if every argument of that logical form is valid.
An example of a valid argument is given by the following well-known syllogism:
All men are mortal.
Socrates is a man.
Therefore, Socrates is mortal.
Reliability is the consistency of a set of measurements or of a measuring instrument, often used to describe a test. Reliability is inversely related to random error.
Reliability does not imply validity. That is, a reliable measure is measuring something consistently, but you may not be measuring what you want to be measuring. For example, while there are many reliable tests of specific abilities, not all of them would be valid for predicting, say, job performance. In terms of accuracy and precision, reliability is analogous to precision, while validity is analogous to accuracy.
An example often used to illustrate the difference between reliability and validity in the experimental sciences involves a common bathroom scale. If someone who is 200 pounds steps on a scale 10 times and gets readings of 15, 250, 95, 140, etc., the scale is not reliable. If the scale consistently reads "150", then it is reliable, but not valid. If it reads "200" each time, then the measurement is both reliable and valid. This is what is meant by the statement, "Reliability is necessary but not sufficient for validity."
Hypothesis- Hypothesis is made in order to find out correct explanation of a phenomena through investigation. On the basis of the hypothesis, facts are observed and collected. When by verification, the hypothesis is found to be true, a theory is obtained.
Functions of a hypothesis.
1.To adequately explain all the facts connected with it.
2.It enables us to direct the enquiry on the correct lines.
3.Hypothesis determines the method of verification and as well as the procedure of enquiry.
4.It leads to the discovery of laws. It explains facts and laws and thus seeks to verify language.
5.Hypothesis leads to conclusion which is very significant for the advancement of knowledge.
Conditions for a valid hypothesis.
1.The most important condition for the valid hypothesis is that it should be empirically verifiable.
2.A hypothesis must answer the problem that initiated enquiry.
3.A valid hypothesis generally does not go against the traditionally established knowledge.
4.A hypothesis must be clear definite and certain.
5.A valid hypothesis suggests an explanation which appears reasonably true in the present state of knowledge.
An experiment in most simple terms may be defined as controlled observation of the phenomena. In an experiment certain conditions are arranged and controlled for the purpose of carefully observing, manipulating, and drawing inferences from the phenomena or the events.
The two important feature of an experiment are (1)Variable (2)Control.
A variable is an event or condition which have different values. Ideally it is an event or condition which can be measured and which varies quantitatively.
Variables can be classified into Independent variables and Dependant variables
In the design of experiments, an independent variable's values are controlled or selected by the experimenter to determine its relationship to an observed phenomenon (i.e., the dependent variable). In such an experiment, an attempt is made to find evidence that the values of the independent variable determine the values of the dependent variable. The independent variable can be changed as required, and its values do not represent a problem requiring explanation in an analysis, but are taken simply as given. The dependent variable, on the other hand, usually cannot be directly controlled
- Independent variables answer the question "What do I change?"
- Dependent variables answer the question "What do I observe?"
- Controlled variables answer the question "What do I keep the same?"
- Extraneous variables answer the question "What uninteresting variables might mediate the effect of the IV on the DV?"
Sample- A sample is a small proportion of population selected for observation and analysis.
Sampling- It is the process of selecting a sample from the population.
The sampling theory: W.G. Cochran has said- “The purpose of sampling theory is to make sampling more efficient. It attempts to develop methods of sample selection and estimation that provide at the lowest possible cost estimates and precise enough for our purpose.
Bases of Sampling
1.Underlying homogeneity amidst complexity.
2.Possibility of representative selection.
3.Absolute accuracy not essential.
Importance of sampling
1.When the population is very large it can be satisfactorily covered through sampling.
2.It saves a lot of time energy and money.
3.Especially when the units of an area are homogenous sampling technique is really useful.
4.When the data is unlimited then the use of this technique is really useful.
5.When cent percent accuracy is not required the use of this technique becomes inevitable.
Types of Sampling
Deliberate Sampling- Deliberate sampling is also known as purposive or non probability sampling. This sampling method involves purposive or deliberate selection of particular units of the universe for constituting a sample which represents the universe.
Simple random sampling- This type of sampling is also known as chance sampling or probability sampling where each and every item in the population has an equal chance of inclusion in the sample and each one of the possible samples in case of finite universe has the same probability of being selected.
Systematic sampling- In some instances the most practical way of sampling is to select every 15th name on a list, every 10th house on one side of a street and so on. Sampling of this type is known as systematic sampling.
Stratified Sampling- If the population does not constitute homogenous group then stratified sampling technique is applied so as to obtain representative sample. In this technique the population is stratified into non overlapping sub population or strata and sample items are selected from each stratum. If the items selected from each stratum is based on random sampling then the entire procedure is called stratified random sampling.
Quota sampling- If cost of stratified random sampling is too high then the interviewers are simply given quota to be filled from different strata, the actual selection of items for sample being left to the interviewers judgement. This is called quota sampling.