Knowledge And Research In Medicine Health And Social Care Essay


Research refers to search for knowledge. It is an art of scientific investigation. Redman and Mory define research as "Systematized effort to gain new knowledge". Research is an original contribution to the existing stock of knowledge. D.S. Lesinger and M.Stephenson in the Encyclopaedia of Social Sciences, define research as  "the manipulation of things, concepts or symbols for the purpose of generalizing to extend, correct or verify knowledge, whether that knowledge aids in construction of theory or in the practice of an art".

According to Clifford Woody "research comprises defining and redefining problems, formulating hypothesis or suggested solutions; collecting, organizing and evaluating data; making deductions and reaching conclusions; and at last carefully testing the conclusions to determine whether they fit the formulated hypothesis". Business research is an organized, systematic, databased, critical, objective, scientific inquiry or investigation into a specific problem undertaken with the purpose of finding solutions to it. Research provides the needed information that guides managers to make informed decisions to successfully deal with problems


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Research design provides the glue that holds the research project together. A design is used to structure the research, to show how all of the major parts of the research project -the samples or groups, measures, treatments or programs, and methods of assignment -work together to try to address the central research questions. A plan outlining how information is to be gathered for an assessment or evaluation that includes identifying the data gathering method(s), the instruments to be used/created, how the instruments will be administered, and how the information will be organized and analyzed. There are two primary requisites of a research process: the analytical plan must be sufficiently powerful to produce results that are both useful and statistically valid, and concomitantly; sampling plans and data collection procedures must assure the reliability of the input data.


Descriptive Approach:

Descriptive research uses a set of scientific methods and procedures to collect raw data and create data structures that describe the existing characteristics of a defined target population. For eg, the profile of the consumers, pattern of purchase behaviour etc. In descriptive research design the researcher looks for answer to the how, who, what, when and where questions concerning the different components of a market structure. The data and information generated through the descriptive designs can provide the decision makers with evidence that can lead to a course of action. Effectiveness of training programs can be evaluated by using Descriptive research designs since scientific methods like questionnaires are used and examined methodically about the development of training programs.

In this study, descriptive approach is used. This descriptive type of research approach is used to get valuable insights from the correspondent about the rate of satisfaction derived by the customers through service quality.


            Data sources can be broadly categorized into three viz., primary, secondary and tertiary.

Primary Data sources

Primary data refers to information gathered firsthand by the researcher for the specific purpose of the study. It is raw data without interpretation and represents the personal or official opinion or position. Primary sources are most authoritative since the information is not filtered or tampered. Some examples of the sources of primary data are individuals, focus groups, panel of respondents, internet etc. Data collection from individuals can be made through interviews, observation etc.

Secondary Data sources

Secondary data refers to the information gathered from already existing sources.  Secondary data may be either published or unpublished data.

The published data are available in the following forms;

Publications of the central, state and local governments

Publications of the foreign governments, international bodies and their subsidiary organizations

Technical and trade journals

Books, magazines and newspapers

Reports and publications of various business and industrial associations, stock exchanges, banks and other financial institutions

Reports prepared by research scholars, universities, economists in different fields

Public records and statistics, historical documents and other sources of published information.

Online and real time databases etc.,

Tertiary sources

Tertiary sources are an interpretation of a secondary source. It is generally represented by index, bibliographies, dictionaries, encyclopaedias, handbooks, directories and other finding aids like the internet search engines.

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Data collection method is an integral part of the research design. There are various methods of data collection; each method has its own advantages and disadvantages. Selection of an appropriate method of data collection may enhance the value of research and at the same wrong choice may lead to questionable research findings. Data collection methods include interviews, self-administered questionnaires, observation and other methods. The choice of a method depends on the following factors;

Nature, scope and objectives of the research

Availability of resources

Degree of accuracy required

Expertise of the researcher

Time span of the study  

Cost involved and the like

The various Methods are

Personal Interviews

Telephone Interviews



Warranty Cards

Store audits

Consumer panels



Sampling is an important concept, which is practiced in every activity. Sampling involves selecting a relatively small number of elements from a large defined group of elements and expecting that the information gathered from the small group will allow judgments to be made about the large group. The basic idea of sampling is that by selecting some of the elements in a population, the conclusion about the entire population is drawn.  Sampling is used when conducting census is impossible or unreasonable. . The process of selecting the right individuals, objects or events for the purpose of the study is known as sampling.

Why Sampling?

There are several reasons for sampling. They are:

Lower cost: The cost of conducting a study based on sample is much lesser than the cost of conducting the census study.

Greater accuracy of results: It is generally argued that the quality of a study is often better with sampling data than with a census. Research findings also substantiate this opinion.

Greater speed of data collection: Speed of execution of data collection is higher with the sample. It also reduces the time between the recognition of a need for information and the availability of that information.

Availability of population element: Some situations require sampling. When the breaking strength of materials is to be tested, it has to be destroyed.

A census method cannot be resorted as would mean complete destruction of all materials. Sampling is the only process possible if the population is infinite.


           The sampling design can be broadly grouped on two basis viz., representation and element selection. Representation refers to the selection of members on a probability or by other means. Element selection refers to the manner in which the elements are selected individually and directly from the population. If each element is drawn individually from the population at large, it is an unrestricted sample. Restricted sampling is where additional controls are imposed, in other words it covers all other forms of sampling. The classification of sampling design on the basis of representation and element selection is shown below:

Element Selection

Representation Basis




Simple random



Complex random









Probability Sampling

            Probability sampling is where each sampling unit in the defined target population has a known nonzero probability of being selected in the sample. The actual probability of selection for each sampling unit may or may not be equal depending on the type of probability sampling design used. Specific rules for selecting members from the operational population are made to ensure unbiased selection of the sampling units and proper sample representation of the defined target population. The results obtained by using probability-sampling designs can be generalized to the target population within a specified margin of error.

As an alternative to the simple random sampling design, several complex probability sampling design can be used which are more viable and effective. Efficiency is improved because more information can be obtained for a give sample size using some of the complex probability sampling procedures than the simple random sampling design. The five most common complex probability sampling designs

Systematic sampling

Stratified random sampling

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Cluster sampling

Area sampling and

Double sampling

Non-probability Sampling

            In non-probability sampling method, the elements in the population do not have any probabilities attached to being chosen as sample subjects. This means that the findings of the study cannot be generalized to the population. However at times the researcher may be less concerned about generalizability and the purpose may be just to obtain some preliminary information in a quick and inexpensive way. Sometime when the population size is unknown, then non-probability sampling would be the only way to obtain data.  Some non-probability sampling technique may be more dependable than others and could often lead to important information with regard to the population. The common types of non probability sampling are






3.4 (1) Population and sampling unit

A population is an identifiable total group or aggregation of elements that are of interest to the researcher and pertinent to the specified problem. In other words it refers to the defined target population. A defined target population consists of the complete group of elements (people or objects) that are specifically identified for investigation according to the objectives of the research project. A precise definition of the target population is usually done in terms of elements, sampling units and time frames.

In this study the population is the customers who visit shoppers stop

Sampling unit

Sample unit is the smallest entity that will provide one response. The customer of Shoppers stops who visited the store represents the sampling unit of this survey.

3.4 (2) Sample size

A sample is a subset or subgroup of the population. It comprises some members selected from it. Only some and not all elements of the population would form the sample . One can say that the sample must be an optimum size that it is should be neither too excessively large nor too small Technically the sample size should be large enough to give a confidence interval of desired width and as such the size of the sample must be chosen by logical process before sample is taken from the universe . In order to extract much feasible result through the study a sample size of 150 has been taken for the study.

3.4 (3) Sampling Procedures:

Non probability sampling is used for the study. Non probability sampling is any sampling method where some elements of the population have no chance of selection, or where the probability of selection can't be accurately determined. It involves the selection of elements based on assumptions regarding the population of interest, which forms the criteria for selection. Hence, because the selection of elements is nonrandom, non probability sampling does not allow the estimation of sampling errors. It equally plays a major role in the field of Descriptive Research. The study follows convenient sampling in the selection of sample units.

MODE OF DATA COLLECTION Primary data collection method by questionnaire was used to collect data from the respondents. The questionnaire method was self administrated by the respondents.


The questionnaire method was used for data collection which consists of forms of paper containing related questions to certain specific objective regarding which the researcher collects the data. This method of data collection through questionnaire is quite popular particularly in case of enquiries.


Formulation of Questionnaire:

The questionnaire uses both, the structured and unstructured type. In the structured type, the questions are final in their form and structure. The responses are indicated and the respondent has to only indicate the choice. It is formulated in such a manner that the respondent takes minimum time for answering the questions. In unstructured type, there is no such rigidity with regard to the answer for questions. There is scope for the respondents to give more information on any question.

Dichotomous questions:

When a question has two possible responses, it is considered dichotomous. Surveys often use dichotomous questions that ask for a Yes/No, True/False or Agree/Disagree response. There are a variety of ways to lay these questions out on a questionnaire. These are mainly used to collect demographic and behavioral data where two answers logically exist.

Multiple choice questions:

Multiple choice questions were provided with answers to the respondents to help them choose an alternative.

Likert scale:

A Likert item is simply a statement which the respondent is asked to evaluate according to any kind of subjective or objective criteria; generally the level of agreement or disagreement is measured on a five point or seven point scale. In the questionnaire five point scale is used.

Text open ended questions:

An open-ended question is designed to encourage a full, meaningful answer using the subject's own knowledge and/or feelings. It encourages a short or single-word answer. Open-ended questions also tend to be more objective and less leading than closed-ended questions. It is a statement which implicitly asks for a response.

Period of study:

The study has been undertaken for 12 weeks. During this period the work was done extensively to bring out with utmost sincerity.

Pilot study

Pilot studies are a crucial element of a good study design. The term 'pilot studies' refers to mini versions of a full-scale study, as well as the specific pre-testing of a particular research instrument such as a questionnaire or interview schedule. Before going for the actual field work, the rough draft of the questionnaire was pre- tested with 20 respondents, which resulted in necessary modifications and improvements.

3.8. Tools for Analysis


Here tables, Bar charts and Pie charts are used in presenting data


Percentage refers to a special kind of ratio percentage are used in making comparison between two or more series of data. Percentage is used to describe the relationship and also be used to compare relative terms of two or more series of data.


A hypothesis is a supposition made as a basis for reasoning. It is defined as "a hypothesis in statistics is simply a quantitative statement about a population". The hypothesis test is carried out with Null hypothesis (H0) says that there is no significant difference between the two variables and the other is Alternative hypothesis (H1) which says that there is significant difference between the two variables.


Chi square is a non parametric test used more frequently by marketing researcher to the hypothesis. The objective of chi square test is to determine whether real or significant difference exists among the various groups.


Ψ 2 = ∑ [(O-E) 2 / E]


O - Observed frequencies

E - Expected frequencies

3.8.5. Factor analysis:

Factor analysis is a statistical method used to describe variability among observed variables in terms of fewer unobserved variables called factors. The observed variables are modeled as linear combinations of the factors, plus 'error' terms. The information gained about the interdependencies can be used later to reduce the set of variables in a dataset. Factor Analysis is a statistical technique that is used for many purposes including revealing patterns of inter correlation ship among variables, and ; reducing a large number of variables to a smaller number of statistically independent variables that are each linearly related to the original variables.

3.8.6. Cross tabulation:

Cross-tabulation is about taking two variables and tabulating the results of one variable against the other variable. A cross-tabulation gives a basic picture of how two variables inter-relate. It helps to search for patterns of interaction.


            Analysis of Variance (ANOVA) is a statistical method of testing the null hypothesis that the means of several populations are equal. To use ANOVA certain conditions must be met.

The samples must be randomly selected from normal populations

Populations should have equal variances

The distance from one value to its group's mean should be independent of the distance of other values to that mean


Every study has its own limitation .This research was conducted with sincere efforts aiming to reduce mistakes

The usual hindrance in collection of data like non response, error and inconsistent response

The study was based on the questionnaire method hence it is limited to the data collected

The study is not universal. One of the major limitations was the time factor. Since the time was very limited it was very difficult to study large samples.

It is only limited to Chennai. Hence, the conclusions would not be a generalized one.