Scientific methods of research

Component Of The Scientific Methods

     The main distinguish characteristics of scientific research are listed as follows:

Ø      Purposiveness

Ø      Rigor

Ø      Testability

Ø      Replicable

Ø      Precision and confidence

Ø      Objectivity

Ø      Generalizable

Ø      Parsimony

Ø      Purposiveness:

     Any scientific research should have a definite and specific purpose.  Without a purpose, a search will be a meaning less exercise.  It is like sailing in the waters without having a destination.

Ø      Rigor:

     It means carefulness, scrupulousness and the degree of exactitude in research investigation.  A good theoretical base and around methodological design would add rigor to a purposive study.

Ø      Testability:

     Scientific research lends itself to testing logically developed hypothesis to see whether or not the data support the educational conjectures or hypothesis that are developed after a careful study of problem situation.

Ø      Replicable:

     It means any scientific research if conducted again in similar circumstances by adopting same procedure would produce the same result.

Ø      Precision & Confidence:

     Precision refers to closeness of the finding to reality based on a sample.  In other words, precision reflects the degree of accuracy or exactitude of the results based on sample.

    

     Confidence refers to the probability that our estimation is correct.  That is, not merely enough to be precise but it is also important that we can confidently claim that 95% of our results would be true and there is only a 5% chance of our being wrong.  This is known as confidence level.

Ø      Objectivity:

     The conclusion drawn through the implementation of the results of data analysis should be objective.  That is they should be based on the facts of the finding derived from actual data and not on our own subjective or emotional value.

Ø      Generalizable:

     Generalizable refers to the scope of applicability of the research finding in one organizational setting to the settings of other organizations.  Obviously, the wider the range of applicability of the calculations generated by research, the more useful the research is to the users.  For instance, if a researcher’s finding that participation in decision making enhances organizational commitment are found to be true in a variety of manufacturing, industrial and service organizations and not merely to the particular organization studied by the researcher, than the Generalizable of the finding to the other organizational setting is enhanced.  Such study is said to be Generalizable.

Ø      Parsimony:

     Simplicity in explaining the phenomena or problem that occur and in generating solutions of the problem, in always preferred to complex research framework that consider an unmanageable umber of actors.  For instance if two or three specific variables in the work situation are indemnified, which when changed would raise the organizational commitment of the employees by 45% that would be more useful and variable to the manager than if it were recommended that he should change 10 different variables to increase organizational. 

  Commitment by 48%.  Therefore the achievement of a meaningful and parsimonious, rather an elaborate and cumbersome model of problem solution becomes a critical issues in research.

Types Of Scientific Methods:

     In the scientific research, two methods are implied.  These are as under:

Hypothetical-deductive Method:

     Deduction is the process by which we arrive at a reasoned conclusion by logical generalization of a known fact.  For example, we know that all high performers are highly proficient in their jobs.  If Ahmed is high performer, we than conclude that he is highly proficient in his job.

     The seven steps involved in the hypothetical-deductive method of research stem from the building blocks are listed as under.

Ø      Observation

Ø      Preliminary Information Gathering

Ø      Theory Formulation

Ø      Hypothesis

Ø      Further Scientific Data Collection

Ø      Data Analysis

Ø      Deduction

Ø      Observation:

     Observation is the first stage in which one senses that certain changes are occurring or some new behavior, attitudes and feelings are surfacing in one’s environment (i.e. the workplace).  When the observed phenomena are, seem to have potentially important consequences one would precede to the next step.

Ø      Preliminary Information Gathering:

     Preliminary information gathering involves the seeking of information in-depth, of what is observed.  This could be done by talking informally to several people in the work setting or to clients, or to the relevant sources, thereby gathering information on what is happening and why.  Through these unstructured interviews, one gets an idea or a feel of what is transpiring in the situation. 

Ø      Theory Formulation:

     Theory formulation, the next step, is an attempt to integrate all the information in a logical manner, so that the factors responsible for the problem can be conceptualized and tested.  Experience and intuition often guide the theoretical framework formulated.  In this step, the critical variables are examined as to their contribution or influence in explaining why the problem occurs and how it can be solved.  The network of associations identified among the variables would then be theoretically woven together with justification as to why they might influence the problem.

Ø      Hypothesis:

     Hypothesis is the next logical step after theory formulation.  From the theoretical network of associations among the variables certain testable hypothesis or educated conjectures can be generated.  For instance, at this point one might hypothesize that if a sufficient number of items are stocked on shelves customer dissatisfaction will be considerably reduced.  This is a hypothesis that can be tested to determine if the statement would be supported.

Ø      Further Scientific Data Collection:

     After the development of the hypothesis, data with respect to each variable in the hypothesis need to be obtained.  In other words, further scientific data collections needed to test the hypothesis that is generated in study.  For instance to test the hypothesis that stocking sufficient items will reduce customer dissatisfaction, one needs to measure the current level of customer satisfaction and collect further data on customer satisfaction levels whenever sufficient number of items are stocked and made readily available to the customers.

Ø      Data Analysis:

     In the data analysis step the data gathered are statistically analyzed to see of the hypothesis that were generated have been supported.  For instance, to see if stock levels influence customer satisfaction, one might want to do correlation analysis and determine the relationship between the two factors.  Similarly other hypothesis could be tested through appropriate statically analysis.

Ø      Deduction:

     Deduction the process of arriving at conclusion by interpreting the meaning of the results of the data analysis.  For instance, if it was found from the data analysis that increasing the stocks was positively correlated to increase customer satisfaction.  Than one can deduce that if customer satisfactions are to be increased, the shelves have to be better stocked.

Induction Method:

     Induction is a process where we observe certain phenomena and on this basis arrive at conclusions.  In other words in induction we logically establish a general proposition based on observed facts.  For instance, we see that the production process are the prime feature of factories or manufacturing plants.  We therefore conclude the factories exist for production purposes.  Both the deductive and inductive factories are applied in scientific investigation.

     The induction conclusion is an inferential jump beyond the evidence presented.  For example, we push the button of light switch but the light fails to go on.  Now we know from the known facts that lights must go on when we push the button and if the bulb burns out than light will not go on.  The nature of the induction is that the conclusion is only a hypothesis. 

Fact 1 is pushing the light switch results in no light.

Fact 2 is inserting a new bulb brings light when switch is pushed.

     Theories based on deduction and induction helps us to understand, explain, and / or predict business phenomena.  When research is designed to test some specific hypothesized outcome, as for instance, to see if controlling aversive mental puzzles.  The following steps ensue.  The problem sobbing.  The hypothesis generated that if the noise is controlled, mental puzzles can be solved more quickly and correctly.  The results of the study helps the researchers to deduce or conclude that controlling the aversive noise does indeed help the participants to improve their performance on mental puzzles.

Conceptualization:

A concept is a bundle of meaning or chrematistics associated with certain events such as objects, condition in situations and the like.  Concepts are classifying and categorizing objects or events that have common meaning beyond the single observation.  Suppose we say a person on road, what shall we conceptualize by this.  Maybe the person is running, walking, or just standing on the road.  The person maybe a man or woman and other characteristics related to this person come into out mind.

Sources Of Concept:

     Most of the concepts are developed through shared meaning of phenomena or share usage of over a period of time.  We acquired them through personal experience.  Some concepts are transformed into another language.  Ordinary concept makeup the bulk of communication even in research.  However, we can often run into difficult trying to deal with this problem is to borrow a word forms other language but it is not necessary that it practically work.  Therefore, we have to develop a new word of a new meaning to concept.

Importance In Research:

     Concepts are basic of all thoughts and communications, yet we pay little attention to what they are and problem encountered in their use.  In research problem, grow out of the need of concept precision and inventiveness.  We design hypothesis-using concepts.  We gather data using these measurement concepts.  We say even invent new concepts or new ideas.  The success of concepts depends on:

     i.        How clearly we conceptualize.

  ii.        How well they understand the concept we use.

     For example, when we conduct the survey we ask the question to public about their income.  This is a simple question but it carries lot of ambiguities.  We need to ask the income of each person within a timeframe, i.e. yearly, quarterly, monthly, weekly etc.Than it will become even clearer for the respondents to give answer.

Problem In Using Concepts:

     The use of the concepts presents difficulties that are accentuated in Research setting.  First people differ in the meaning that includes under the particular label.  The problem is so great in normal human communication that we often see cases where people use the same language but do not understand each other we have different meaning in our minds for leadership, motivation, personality, social class, and fiscal policy.

    

     Concepts describe progressive levels of abstraction that is the degree to which the concepts does or does not have objective references.  An abstraction as if personality is much not difficult to visualize.