Research methodology pdf notes free download

Baldry, D. Sarshar, M. Bhattacherjee, A. Textbook collection. Book 3. Date oaf access: 25 November Carmichael, R. The logic of Discovery. The Monist, 32 4 , Date of access: 24 November Cough, N. Blank spots, blind spots and methodological questions in postgraduate research. Creswell, J. Educational research: planning, conducting, and evaluating qualitative approaches to research, 5th edition.

Curry, L. Qualitative and mixed methods provide unique contributions to out- comes research. Circulation, 1 , De Vaus, D.

Denzin, N. Introduction: the discipline and practice of qualitative research. In Denzin, N. The SAGE handbook of qualitative research, 4th edition. Thousand oaks, CA: Sage, Glesne, C. Becoming qualitative researches: An introduction. Understanding Reliability and Validity in Qualitative Research. The Qualitative Report, 8 4 , Date of access: 24 November Hancock B. An Introduction to Qualitative Research. Trent Focus Group, Nottingham.

Labaree, R. University of Southern California. Date of access: 23 November Lai, E. Critical thinking: a literature review. Date of access: 19 November Lincoln, Y. Naturalistic inquiry. Beverly Hills, CA: Sage. Maree, K. First steps in research. Pretoria: Van Schaik Publishers. Pautasso, M. PLoS Computational Biology, 9 7 , Pedaste, M. Phases of inquiry-based learning: Definitions and the inquiry cycle. Educational Research Review. Randolph, J.

A guide to writing the dissertation literature review. Thomas, P. Multiple choice questions: These questions contains more than two alternatives e. Why have you preferred this brand of two wheeler? Examples of leading questions are : Are you against giving too much power to the trade unions? Dont you that yesterdays T. Drama was thrilling? Here the respondent would react to the word than the Question.

Example: Have you tried to get special favours from a business establishment by pressuring them? Yes c Ambiguous questions: An ambiguous question is one that does not have a clear meaning. It may mean different things to different people example. Are you interested in a small house?

What does the word interested mean to own or hire? What does the word small mean No Determine the type of collecting data Interview Questionnaire Determine the content of individual questions. Is question necessary Does respondent have the information Respondent remembers the same Several questions needed instead of one Determine the type of questions -open ended -closed -dichotomous -pictorial -multiple choice Decide on wordings of questions Decide question sequence -Physical appearance -easy to access -easy to understand -motivate Preliminary Draft Revision and final draft.

Enumerators go to respondents, ask them questions from the proforma in the same order in which the questions are listed and record the replies on the space given. Enumerators should be trained Example: Population census. Relatively cheaper as it is sent Costlier, as the investigators has by mail to the targeted to be appointed, trained and meet every informant at the Coverage Wide coverage possible, as it Relatively limited coverage as can be sent to any place by post the investigator can not be sent to every place Time taken for apply It can not be established as the It is possible to plan the enquiry respondent may reply at his and depute the investigators convenience accordingly and collect.

Degree of response Less, as all the respondents, do Relatively not respond good, as the. Not good, as the respondents Relatively answers the questions the way it investigator is understood. It is possible to cover a wide This is not possible as the range of sample elements as the investigator has to personally questionnaire is sent only be contact each respondent post.

It is not likely to high, as it Relatively accuracy is better in depends on the structure of the this method, as the investigator questionnaire itself can determine the accuracy on the field and adopt appropriate methods to ensure accuracy. Field control and monitoring This is not possible as the There is good scope for.

There is not way to test the If the investigator is trained and extent of bias of the information experienced then there is very given by the respondent little scope for bias in. Generally speaking secondary data is collected by some organization to satisfy its own need but it is being used by various departments for different reasons. For example, census figures taken are used by social scientists economists for social planning and research.

The sources for secondary data or the sources for doing desk research will be gathered by the following ways: Internal Sources: Registers, Documents, Annual Reports, Sales Reports, previous Research papers , Sales records, invoices etc.

The choice between the two depends on Nature and Scope of Research Availability of financial resources Availability of time Degree of accuracy desired Status of the researcher individual, govt.

It is difficult to plan a major study or project without adequate knowledge of its subject matter, the population it is to cover, their level of knowledge and understanding and the like. What are the issues involved?

What are the concepts associated with the subject matter? How can they be operationalise? What method of study is appropriate? How much money it will cost? This is called pilot study. The size scope and design of the pilot study is a matter of convenience, time and money. It should be large enough to fulfill the following functions.

Functions of Pilot Study: It provides a better knowledge about problem. It helps to identification and operationalisation of concepts relating to the study. It assists in discovering the nature of relationship between variables and in formulating hypothesis. It helps the researcher to develop an appropriate plan of analysis It provides information for estimating the probable cost and duration of the main study and of its various stages Pre-Test Pre test is a trial test of a specific aspect of the study such as method of data collection instrumentinterview schedule mailed questionnaire or measurement scale pre-testing has several Purposes.

They are: A research Hypothesis is a predictive statement icapable of being tested by scientific methods, that relates an independent variable with some variable. Hypothesis is usually considered as the principal instrument for research. Its main function is to suggest new experiments and observations. Definition of Hypothesis: A research hypothesis is a predictive statement capable of being tested by scientific methods, that relates an independent variable to some dependent variable.

The feature of a hypothesis statement are as follows: It should be clear and precise It should be capable of tested It should state the relationship between variables It should be limited in scope and must be specific It should be stated in simple terms. Basic Concepts: Null Hypothesis: The random selection of the samples from the given population makes the tests of significance valid for us.

For applying any test of significance we first set up hypothesis Such a statistical hypothesis, which is under test. Is usually a hypothesis of no difference and hence is called Null Hypothesis. It is usually denoted by Ho Alternate Hypothesis: Any hypothesis which is complementary to null hypothesis is called and alternate hypothesis. It is usually denoted by Ha For example if the null hypothesis is that there is no relationship between the eye colour of husbands and wives is rejected then automatically the alternate hypothesis is that there is relationship between the eye color of husbands and wives is accepted.

Type I error: We commit this error when we reject a null hypothesis which is true. Type II error: This error is committed when we accept the null hypothesis which is false.

This could be stated below:. Suppose we set a null hypothesis that rainfall does not affect food production. From experience and research findings in the past it is well known that rain fall certainly affect food production. Hence the null hypothesis should be rejected, but instead, if we accept it we commit type II error. He has to calculate the probability that sample result could diver age as widely as it has from expectation Ho wee true. Making a formal statement: It consists of making a formal statement of the null hypothesis Ho and also of the alternative hypothesis Ha Selecting a significance level: Generally the hypothesis is tested on a pre-determined level of significance and as such the same should be specified.

Deciding the distribution to use: After deciding the level of significance the researcher has to determine the appropriate sampling distribution. Selecting a random sample and computing an appropriate value: The researcher has to select a random sample s and compute an appropriate value from the sample data.

Calculation of the probability The researcher has to calculate the probability that the sample result would diverge as widely as it has from expectations. Comparing the probability Afterwards, the researcher has to compare the probability thus calculated with ithe specified value for significance level.

First it summarizes large mass of data into understandable and meaningful form. The reduction of data facilitates further analysis.

Second, statistics makes exact descriptions possible. For example when we say that the educational level of people in X district is very high. The description is not specific; but when statistical measures like the percentages of literate among males and females. The percentage of degree holders among males and females and the like are available the description becomes exact.

Third, statistical analysis facilitates identification of the casual factors underlying the complex phenomena. What are the factors which determine a variable like labour productivity of academic performance of students? What are the relative contributions of the causative factors? Answers to such questions can be obtained from statistical multivariate analysis Fourth statistical analysis aids the drawing of reliable inferences from observational data.

Last, statistical analysis is useful for assessing the significance of specific sample results under assumed population conditions.

This is type of analysis is called hypothesis testing. Parametric Tests: The tests of significance used for hypothesis testing are of two types; the parametric and non-parametric tests. The parametric tests are more powerful but they depend on the parameters or characteristics of the population.. They are based on the following assumptions; The observations or values must be independent The samples are drawn on a random basis.

The populations should have equal variances The data should be at least at interval level so that arithmetic operations can be used. The important parametric tests are ; The z-test, the t-test, and the F-test. They are explained below:. The Z-test: It is based on the normal distribution; it is widely used for testing the significance of several statistics such at mean, median, mode, coefficient of correlation and others.

The relevant test statistic, z is calculated and compared with its probable value to be reads from the normal distribution table at a specified level of significance for judging the significance of the measured concerned. The t-test: It is suitable for testing the significance of a sample mean or for judging the significance of difference between the means of two samples.

The t-test can also be used for testing the significance of the co-efficient of simple and partial correlations. The relevant test statistic, t, is calculated from the sample data, it is compared with its corresponding critical value in the t-distribution table for rejecting or accepting null hypothesis. The F-test: The F test is used to compare the variances of two independent samples. It is also used in analysis of variance ANOVA for testing the significance of more than two sample means at a time.

It is also used for judging the significance of multiple correlation coefficients. This assumption is that population of data from which a samples are drawn is normally distributed. But there are some situations when the researcher cannot or does not want to make such assumption. In such situations we use statistical methods for testing hypothesis, which are called non-parametric tests because such tests do not depended on any assumption about the parameters of the parent population.

Most non-parametric tests do not require lengthy computations. It is less time-consuming Non-parametric tests are applicable for all types of data It makes possible to work with very small samples. The important nonparametric tests are the chi-square test the median test the Mann-whitney U test the sign test, the Wilcoxin matched-pairs test and Kolmogorow Smirnov test.

For detatiled explanation refer Statistical methods by S. C Guptha. A scale ha a wide range of application is social science research. Scaling provides the procedures if assigning numbers to various degrees of opinion, attitude and other concepts. Normally this takes place in two ways: Making judgment about some characteristics of an individual are then directly placing him on a scale.

Constructing a questionnaire in such a way that the score of individual responses assign him a place on a scale. In rating scale, the rater makes a judgment about some characteristics of a subject and places him directly on some point on the scale. These scales can be either discrete or continuous. In these scales two or more categories are provided representing discrete amount of some characteristics. The rater can tick the category which he feels best describes the person of object being rated.

Thus for examples, the characteristics job knowledge may be divided into five categories on a discrete scale thus Exceptionally good Above average Average Below average Poor.

In these scales just above the category notation, an uninterrupted line is provided. The rate can tick anywhere along its length as shown below. The individuals responses to the various scales may be aggregated or summed to provide a single attitude for the individual the following are the four types of Attitude scales. The respondent will tick his opinion, either favorable or unfavorable the each statement in the instrument.

The responses will give a numerical score indicating its favourableness or unfavourableness and he scores are totaled to measure the respondents attitude. In other words the overall score represents the respondents positions. In a Likert scale, normally a respondent will be asked to respond to each of the statements in terms of several degrees. Usually five degrees but at time 3 to 7 may also be used of agreement or disagreement.

Suppose a researchers wants to examine whether one considers his job quite pleasant, the respondent may respond in any of the following ways: strongly agree agree undecided disagree strongly disagree.

In the above scale, each points carries score, the response will be given weight or scores. The least score will be given to the least favorable degree of job satisfaction and the most favorable is given to the highest score. Advantage: The Likert Type scale is easy to develop in comparison to thurstone type scale it can be performed without a panel judges.

It is more reliable because under it. Respondents can answer each statements included in the instrument The likert type scale permits the use of statements that are not manifestly related to the attitude being studied. It can be used in a respondent-centered and stimulus centered studies I. It requires less time to construct, it is frequently used by the students of opinion research. Limitations: These scales will indicate whether respondents are more or less favourable to a topic and they can not tell how much more or less they are.

The interval between strongly agree and agree may not be equal to the interval between agree and undecided. Thurstone Type Scale differential scales Here, the selection of items is made by a panel of judges who evaluate the items in terms of whether they are relevant to the topic area and unambiguous in application.

Here, the researcher adopts the following procedures: The researcher collects more differential statements, usually 20 or more, that express various points of view toward a group institution idea or practice. A panel of judges, will arrange them in 11 groups or piles ranging from one extreme to another in position. The judges will be asked to arrange generally in the first pile of the statements which he thinks are most unfavourable to the issue, in the second pile to place those statements which he thinks are next most unfavorable and he goes on doing so in this manner till in the eleventh pile he puts the statements which he considers to be the most favourable.

The judges will sort out the items and when there is disagreement between the judges in assigning a position to an item that item will be left out. The panel will establish the median scale value between one and eleven. Then, the researcher makes a final selection of statements, a sample of statements whose median scores are spread evenly from one extreme to other is taken. The statements so selected constitute the final scale to be administered to respondents.

The respondents will be asked to check the statements with which they agree.. The median value is worked out and this establishes their score or quantifies their opinion. It may be noted that is the actual instrument the statements are arranged in random order of scale value. It is an attempt to measure the psychological meaning of an object to an individual. It consists of a set of bipolar rating scales, usually 7 points by which one or more respondents rate one or more concept on each scale item.

Once the data collection is complete, it is examined carefully to eliminate any errors or mistakes. For that purpose of editing of data becomes mandatory. Editing means to rectify or to set to order or to correct or to establish sequence. Persons with editing responsibility should be trained and experienced in this job. Editing is performed at two stages and depending on that it could be two types.

Field editing and centralized editing. Field Editing: Field editing refers to the performance of the editing immediately in the field where data is collected. For example if the data is collected through questionnaire or schedule, then whether all the questions are answered or not whether writing is legible or not etc should be checked out after the collecting the questionnaire from the respondent in the field itself. Centralized Editing: In this type of editing, editing is done by a person or a team after all the recorded questionnaires schedules are collected.

So clearly it is not carried out on the field itself or immediately after the data are collected. In such editing normally the instructions regarding editing are printed and circulated to the person or the team doing the editing. This is only to ensure that there is uniformity in editing. Coding is a practice which simplifies recording of answers. When standard answers for a question could be indicated, each answer is assigned a code. So instead of writing the answers in full, the investigator simply writes the code.

This is not only saves times but also avoid confusing answers. Classification of data means grouping the data on the basis of some common characteristics. Classified data can be used for specified purposes with ease. Further classification adds to clarity and helps to maintain consistency. Classification can be made on the basis of a common characteristics like sex, literacy, colour, height, and weight etc.

Which are called cells. Tabulation has several rules and the most important ones are listed below: Every table should be numbered numbering could be in alphabet.

Crores, tones etc Each column should be titled. Each row must be titled Rows and columns are to be numbered Footnotes of the table should indicate the explanatory notes on the data in the table and the footnotes must be positioned below the table Data to be compared must be placed in adjacent columns.

They provide data systematically in columns and rows. It presents a very clear idea of what the table presents. Table provides a considerable saving in time taken in understandings what is represented by the data and hence all confusion is avoided. It facilitates comparison: Tables provide comparison. Generally table is divided into various parts and for each part there are totals and subtotals, the relationship between different parts of data can be studied much more easily with the help of a table than without it.

It gives identity to the data: When the data are arranged in a table with a title and number they can be distinctly identified and can be used as a source reference in the interpretation of a problem. It provides patterns: Tabulation reveals patterns with the figures which can not be seen in the narrative form. It also facilitates the summation of the figures if the reader desires to check the totals.

Part of a table 1. Table number 2. Title of the table 3. Caption Heading 4. Head note and 6. Foot note. Tables can be broadly classified to two categories: 1. Simple and complex frequency tables 2. General purpose and special purpose frequency tables.

The following is the illustration of such a table. The following example illustrates the nature of such a table. They provide information for general use or reference. They usually contain detailed information and are not constructed for specific discussion. It was time consuming. Establishing multiple correlations hips was complex. Accuracies were not guaranteed. However, now the personal computers have emerged as one of the most effective tools in the use of market research.

Discussed below are some of the areas where personal computers can find applications. Word Processing: The market survey findings are to be in variably presented in the form of a report. Through work processing draft report and final reports can be easily prepared by avoiding repetitive typing.

Data Processing: Simple software are now available for the processing of data. The work is done in a short time with compact outputs. They can be self explanatory or easier to draw conclusions. Data Base Management System: Availability of different types of databases at reasonable cost would save considerable time of the executives and will help them in decision making. Graphics: Earlier this data had to be manually presented in the form of a graph, chart or histogram.

Now with the help of Pcs after feeding the data and with the help of simple software this data will appear in different graphical forms. The storing facility of the computers will help the researcher immensely for using the data whenever he requires. Results of computer analysis lead to more accuracy. Errors in the machinery can occur but due to increased efficiency in error-detecting techniques, these seldom lead to false results.

Diligence: Being a machine a computer does not suffer from the human traits of tiredness and lack of concentrations. If two million calculations have to be performed it will perform the two millionths with exactly the same accuracy and speed as the first.

Automation: Once a program is in the computers memory, all which is needed is the individual instructions to it, which are, transferred one after the other, to the control unit for execution. The CPU follows these instructions until it meets a last instruction which says stop program execution. Generally, the statistical results are presented through diagrams and graphs, We can see them in newspapers, magazines, journals, advertisements, etc.

They provide birds eye view of the entire data 2. They are attractive 3. They provide memorizing effect 4. They facilitate comparison of data. They are 1. Nature of data 2. The target audience for whom the diagram is drawn 3. The The facilities available to draw the diagram 5.

Purpose of the representation 6. The size of the paper or the sanctioned size for the diagram etc. Dates Ocw. No enrollment or registration. Freely browse and use OCW materials at your own pace. There's no signup, and no start or end dates.

Knowledge is your reward. Use OCW to guide your own life-long learning, or to teach others. Dates Studocu. Lecture Cartercenter. It is assumed that this lecture note on research methodology will be given to health science students who have taken basic Epidemiology and Biostatistics courses. Course Nou. Category : It Courses Show more. Notes Lecturenotes. Research Researchgate. Research Unrwa. Students should also consult their own course guidelines on writing research up the results of their research projects.

Training People. Category : Training Courses Show more. Research Geektonight. We provide complete business research methods pdf. Business Research Methods study material includes business research methods notes , book, courses , case study, syllabus, question paper, MCQ, questions and answers and available in business research methods pdf form. Business Research …. EBook Studynama. There are no. Course Assets. All three assignments. Research Ebooks. Category : Free Courses Show more.

Topic Ebookskenya. Research Acpsf. It is the plan, structure and strategy of investigation conceived so as to obtain answers to research questions. To ensure that your methods are firmly linked to your research questions or aims , it is a good idea to draw a diagram which links each research question with the methods you plan to use to answer it. In the diagrams below, the lines without arrows indicate the breakdown of the research aims.

Nursing Web2. Chapter 2 introduces readers to key. Research Slideshare. Kishor K. AdeLecture 1 Research Methodology 2 Contents 1. Meaning of Research 2. Objectives of Research 3. The chart shown in Figure 1represents a research process. But these activities should be following in a strictly prescribed sequence otherwise researcher may face the problem in completion of the research. In the research process, each step is specific and they are separate and distinct from each other.

However, the following order relating to various steps provides a useful procedural instruction regarding the research process: 1 Identification of research problem 2 Broad literature survey 3 Hypothesis formulation 4 Preparation of research design 5 Determining sample design 6 Data collection 7 Analysis of data 8 Hypothesis testing 9 Generalizations and interpretation 10 Preparation of the report or presentation of the results, 5 Sample Copy.

Identification of research problem: There are two types of research problems like, those which relate to states of nature means that denote the hypothetical conditions of what the lives of people might have been like before societies came into existence and those which relate to relationships between different variables. Initially the researcher must recognize the problem he wants to study, i.

At the onset the problem may be discussed in a broad way and then the doubts, if any, relating to the problem may be resolved. Then, the probability of a particular clarification has to be considered before working on formulation of the problem.

Basically two steps are involved in formulating the research problem, viz. The most excellent way of understanding the problem is to discuss it with contemporaries or with those having some knowledge in the related matter. In an academic institution the researcher can take the assistance from a guide who is usually an experienced man and has several research problems in his mind.

In private business units or in governmental organizations, the problem is usually allocate by the administrative agencies with whom the researcher can discuss the problem originally that how it is came about and what reflections are involved in its possible clarification.

Broad literature survey: After the identification of research problem, the researcher must at study all available literature to get himself familiar with the selected problem.

He may review two types of literature first is the conceptual literature which is related to the concepts and theories, and second is the empirical literature which consisting of previous studies similar to the proposed research problem. The researcher should undertake vast literature survey concerned with the problem.

For this purpose, the abstracting and indexing journals and published or unpublished bibliographies are the first place where researcher can get the 6 Sample Copy. Handbook of Research Methodology information or knowledge. Academic journals, conference proceedings, government reports, books etc.

After this the researcher revise the problem into analytical or operational terms i. This assignment of formulating, or defining, a research problem is a important step in the entire research process.

Once the problem is formulated, a synopsis of it should be written down. Hypotheses formulation: After the literature survey, researcher should make a hypothesis or working hypothesis. Working hypothesis is a guess made to test the logical or empirical outcome of a research. A hypothesis assists to explain the research problem and objective into a comprehensive explanation or prediction of the expected results of the study.

Hypothesis is derived from the research problem, literature review and conceptual framework. Since Hypothesis is to be tested therefore it should be very specific and limited to the piece of research.

Hypothesis formulation could be done by using the following approaches: a Discussions with colleagues and experts about the research problem, its source, cause and the objectives in search of a solution; b Assessment of data and records, c Evaluation of similar previous studies in the area similar problems; and d Personal investigation which involves original field survey Thus, any hypotheses take place as a result of a-prior thinking about the subject, assessment of the available data and material including related previous studies.

Formulation of working hypotheses is a basic step of any research process. Preparation of research design: A good research design will be prepared if a research problem should be stated clearly. In other words, the purpose of research design is refers as general procedure that you choose to combine the various components of 7 Sample Copy.

Shanti Bhushan Mishra, Shashi Alok the study in a consistent and logical way. It comprises the outline for the collection, measurement, and analysis of data.

A flexible research design which offers the opportunity for allowing the different aspects of a problem is considered suitable if the purpose of the research study is to be clear. There are several research designs, such as, Descriptive e. It can be supposed that in such type of inquiry all the items are covered and not a single element is left and highest accuracy is obtained. But in practical way this may not be true because a single element of bias in such inquiry will get larger the number of observations increases.

Moreover, there is no way of scrutiny the element of bias or its level except through a resurvey or use of sample checks.

Besides, such type of inquiry comprises a lot of time, money and energy. Apart from this, census inquiry is not possible practically under many conditions. For example, blood sugar testing is done only on sample basis. Hence, quite often we select only a few items from the population for our study purposes. The selection of items in such type of manner is technically called a sample. The researcher must decide the way of selecting a sample or choose a sample design for his study.

In other words, a sample design is a exact sketch determined prior to any type of data collection for obtaining a sample from a given universe. There are two types of sampling: non-probability and probability sampling. Non-probability sampling uses a subjective method of selecting units from a universe, and is generally easy, quick, and economical.

Therefore, it is useful to perform preliminary studies, focus groups or follow-up studies. Probability samples are based 8 Sample Copy.