mb0050-531010671

SMU MBAHCS ASSIGNMENTSEMESTER III

MB0050

RESEARCH METHODOLOGYASSIGNMENT SET: I

SUBMITTED BY:

J.JERALD JEYAPRAKASHMBAHCS

ROLL NO :- 531010671

SMU- MBA Semester III

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Research Methodology-MB0050

INDEX

Q.No Q.1

QUESTION WHY SHOULD A MANGER KNOW ABOUT RESEARCH WHEN THE JOB ENTAILS MANAGING PEOPLE, PRODUCTS, EVENTS, ENVIRONMENTS, AND THE LIKE? HOW DO YOU EVOLVE RESEARCH DESIGN FOR EXPLORATORY RESEARCH? BRIEFLY ANALYZE. BRIEFLY EXPLAIN INDEPENDENT DEPENDENT AND EXTRANEOUS VARIABLES IN A RESEARCH DESIGN A. DIFFERENTIATE BETWEEN CENSUS SURVEY AND SAMPLE SURVEY. ANALYZE MULTI-STAGE AND SEQUENTIAL SAMPLING. LIST DOWN VARIOUS MEASURES OF CENTRAL TENDENCY AND EXPLAIN THE DIFFERENCE BETWEEN THEM? SELECT ANY TOPIC FOR RESEARCH AND EXPLAIN HOW YOU WILL USE BOTH SECONDARY AND PRIMARY SOURCES TO GATHER THE REQUIRED INFORMATION. EXPLAIN THE ROLE OF GRAPHS AND DIAGRAMS? WHAT ARE THE TYPES AND GENERAL RULES FOR GRAPHICAL REPRESENTATION OF DATA?

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Q.2 A. Q.2 B. Q.3 A. Q.3 B. Q.4 Q.5

Q.6 A. Q.6 B.

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Q1. WHY SHOULD A MANAGER KNOW ABOUT RESEARCH WHEN THE JOB ENTAILS MANAGING PEOPLE,PRODUCTS,EVENT,ENVIRONMENTS, AND THE LIKE ? Answer

The manager, while managing people, products, events, and environments will invariably face problems, big and small, and will have to seek ways to find long lasting effective solutions. This can be achieved only through knowledge of research even if consultants are engaged to solve problems. The primary purpose for applied research (as opposed to basic research) is discovering, interpreting, and the development of methods and systems for the advancement of human knowledge on a wide variety of scientific matters of our world and the universe. Research can use the scientific method, but need not do so. The goal of the research process is to produce new knowledge, which takes three main forms: Exploratory Research, which structures and identifies new problems Constructive Research, which develops solutions to a problem Empirical Research, which tests the feasibility of a solution using empirical evidence. The research room at the New York Public Library, an example of secondary research in progress. Research can also fall into two distinct types: 1) Primary Research 2) Secondary Research


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In social sciences and later in other disciplines, the following two research methods can be applied, depending on the properties of the subject matter and on the objective of the research: Qualitative research Quantitative research Research is often conducted using the hourglass model Structure of Research. The hourglass model starts with a broad spectrum for research, focusing in on the required information through the methodology of the project (like the neck of the hourglass), then expands the research in the form of discussion and results. Research and development is nowadays of great importance in business as the level of competition, production processes and methods are rapidly increasing. It is of special importance in the field of marketing where companies keep an eagle eye on competitors and customers in order to keep pace with modern trends and analyze the needs, demands and desires of their customers. Unfortunately, research and development are very difficult to manage, since the defining feature of research is that the researchers do not know in advance exactly how to accomplish the desired result. As a result, higher R&D spending does not guarantee "more creativity, higher profit or a greater market share.


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Q2. A) . HOW DO YOU EVOLVE RESEARCH DESIGN FOR EXPLORATORY RESEARCH? BRIEF ANALYZE. Answer The central purpose is to formulate hypotheses regarding potential problems and opportunities present in the decision situation. The hypotheses can be tested at a later phase with a conclusive research design ( Leichardt and Leichardt, 1980). Exploratory research design applies when the research objectives include the following: a. Identifying problems (threats or opportunities) b. Developing a more precise formulation of a vaguely identified problem(threat or opportunity) c. Gaining perspective regarding the breath of variables operating in a situation d. Establishing priorities regarding the potential significance of various problems (threats or opportunities) e. Gaining management and researcher perspective concerning the character of the problem situation f. Identifying and formulating alternative courses of action; and g. Gathering information on the problems associated with doing conclusive research. h. Identification of problems (threats or opportunities) can be assisted through the following:


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i) Searching secondary sources ii) Interviewing knowledgeable persons iii) Compiling case histories.

Q2.B). BRIEF EXPLAIN INDEPENDENT, DEPENDENT AND EXTRANEOUS VARIABLES IN A RESEARCH DESIGN. Answer Independent Variable: A variable that you believe might influence your outcome measure. This might be a variable that you control, like a treatment, or a variable not under your control, like an exposure. It also might represent a demographic factor like age or gender. Contrast this with the definition of the dependent variable. An independent variable is a hypothesized cause or influence on a dependent variable. One way to distinguish these variables is to ask yourself what you are want to learn from this research. The dependent variable is a variable you are trying to predict. Any variable that you are using to make those predictions is an independent variable. A recently published research study examined the relationship of dietary fat consumption and the development of ischemic stroke in a cohort of 832 men who were free of cardiovascular disease at baseline (1966-1969) and who were followed for a twenty year period. In this study, the independent variables were: percentage of total fat in the diet, percentage of saturated fat, and the percentage of monounsaturated fat. Dependent Variable: In a research study, the variable that you believe might be influenced or modified by some treatment or exposure. It may also represent the variable you are trying to predict. Contrast this with the definition of an independent variable. Sometimes the dependent variable is


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called the outcome variable. This definition depends on the context of the study. In a study of prenatal care, the birth weight is an outcome or dependent variable, but in neonatology, it is more likely to be an independent variable. A recently published research study examined the relationship of dietary fat consumption and the development of ischemic stroke in a cohort of 832 men who were free of cardiovascular disease at baseline (19661969) and who were followed for a twenty year period. In this study, the dependent variable was: incidence of ischemic stroke. Extraneous variable: The independent variables which are not directly related to the purpose of the study but affect the dependent variable are known as extraneous variables. For e.g,. if a researcher wants to test the hypothesis that there is relationship between childrens school performance and their self-concepts, in which case the latter is an independent variable and the former is the dependent variable. In this context, intelligence may also influence the school performance. However, since it is not directly related to the purpose of the study undertaken by the researcher, it would be known as extraneous variable. The influence caused by the extraneous variable on the dependent variable is technically called as an experimental error. Therefore, a research study should always be framed in such a manner that the dependent variable completely influences the change in the independent variable and any other extraneous variable or variables.


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Q 3. A. DIFFERENTIATE BETWEEN CENSUS SERVEY AND SAMPLE SURVEY. Answer Difference between Census and Sampling Practically every country in the world conducts censuses and sampling surveys on a regular basis in order to get valuable data from and about their populations. This data is used by the federal and state governments in making numerous decisions with regard to various health care, housing, and educational issues, among others. While both these two data-gathering methods essentially serve the same purpose, they have a number of differences with regard to approach and methodology, as well as scope. These two methods may also differ in terms of the variance in the data gathered, as you will see later.

Scope A census involves the gathering of information from every person in a certain group. This may include information on age, sex and language among others. A sample survey on the other hand commonly involves gathering data from only a certain section of a particular group. Sampling Variance The main advantage of a census is a virtually zero sampling variance, mainly because the data used is drawn from the whole population. In addition, more precise detail can generally be gathered about smaller groups of the population. As for sampling, there is a possibility of sampling variance, since the data used is drawn from only a small section of the population. This makes sampling a much less accurate form of data collection than a census. In addition, the sample may be too small to provide an accurate picture of the population.


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Cost And Timetable A census can be quite expensive to conduct, particularly for large populations. In most cases, they are also a lot more time-consuming than sample surveys. Adding considerably to the timetable is the necessity of gathering data from every single member of the population. The huge scope of a census also makes it harder to maintain control of the quality of the data. For instance, anyone who does not complete a census form will be visited by a government representative whos only job to is to gather census data. A sample survey for its part costs quite a bit less than a census, since data is gathered from a much smaller group of people. In addition, sample surveys generally take a much shorter time to conduct, again given the smaller scope. This also means reduced requirem

SummaryCensus

Gathers information from every individual in a certain group Since data from the entire population is used, there is no sampling variance Provides detailed information about smaller groups Can be quite costly, particularly for large populations, due to census tally workers as well as hiring temporary census home visitors Includes an uncomfortable visit from a government worker if the census is not filled outon timeSampling

Gathers information from only a section of the population May have a significant degree of sample variance, since the data is derived from only a small section of a population May not provide enough information about smaller groups or smaller geographical sections of a place Costs much less than a census, since data is gathered from only a small section of a group


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Q 3. B. ANALYZE MULTI-STAGE AND SEQUENTIAL SAMPLING. Answer Multistage sampling Multistage sampling is a complex form of cluster sampling. Using all the sample elements in all the selected clusters may be prohibitively expensive or not necessary. Under these ircumstances, multistage cluster sampling becomes useful. Instead of using all the elements contained in the selected clusters, the researcher randomly selects elements from each cluster. Constructing the clusters is the first stage. Deciding what elements within the cluster to use is the second stage. The technique is used frequently when a complete list of all members of the population does not exist and is inappropriate. In some cases, several levels of cluster selection may be applied before the final sample elements are reached. For example, household surveys conducted by the Australian Bureau of Statistics begin by dividing metropolitan regions into 'collection districts', and selecting some of these collection districts (first stage). The selected collection districts are then divided into blocks, and blocks are chosen from within each selected collection district (second stage). Next, dwellings are listed within each selected block, and some of these dwellings are selected (third stage). This method means that it is not necessary to create a list of every dwelling in the region, only for selected blocks. In remote areas, an additional stage of clustering is used, in order to reduce travel requirements. Although cluster sampling and stratified sampling bear some superficial similarities, they are substantially different. In stratified sampling, a random sample is drawn from all the strata, where in cluster sampling only the selected clusters are studied, either in single stage or multi stage. Sequential Sampling Sequential sampling is a non-probability sampling technique wherein the researcher picks a single or a group of subjects in a given time interval, conducts his study, analyzes the results then picks another group of subjects if needed and so on. This sampling technique gives the researcher limitless chances of fine tuning his research methods and gaining a vital insight into the study that he is currently pursuing.


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Q 4. LIST DOWN VARIOUS MEASURES OF CENTRAL TENDENCY AND EXPLAIN THE DIFFERENCE BETWEEN THEM. Answer Arithmetic Mean The arithmetic mean is the most common measure of central tendency. It simply the sum of the numbers divided by the number of numbers. The symbol m is used for the mean of a population. The symbol M is used for the mean of a sample. The formula for m is shown below:

where is the sum of all the numbers in the numbers in the sample and N is the number of numbers in the sample. As an example, the mean of the numbers 5+6+4+8+1+12 = =6

regardless of whether the numbers constitute the entire population or just a sample from the population. The table, Number of touchdown passes, shows the number of touchdown (TD) passes thrown by each of the 31 teams in the National Football League in the 2000 season. The mean number of touchdown passes thrown is 20.4516 as shown below.

37 22 19 14

33 22 19 14

33 22 18 14

32 21 18 12

29 21 18 12

28 21 18 9

28 20 16 6

23 20 15

Table : Number of touchdown passes.


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Although the arithmetic mean is not the only "mean" (there is also a geometric mean), it is by far the most commonly used. Therefore, if the term "mean" is used without specifying whether it is the arithmetic mean, the geometric mean, or some other mean, it is assumed to refer to the arithmetic mean. MEDIAN The median is also a frequently used measure of central tendency. The median is the midpoint of a distribution: the same numbers of scores are above the median as below it. For the data in the table, Number of touchdown passes, there are 31 scores. The 16th highest score (which equals 20) is the median because there are 15 scores below the 16th score and 15 scores above the 16th score. The median can also be thought of as the 50th percentile. Let's return to the made up example of the quiz on which you made a three discussed previously in the module Introduction to Central Tendency and shown in Table 2.

For Dataset 1, the median is three, the same as your score. For Dataset 2, the median is 4. Therefore, your score is below the median. This means you are in the lower half of the class.Finally for Dataset 3, the median is 2. For this dataset, your score is above the median and therefore in the upper half of the distribution. Computation of the Median: When there is an odd number of numbers, the median is simply the middle number. For example, the median of 2, 4, and 7 is 4. When there is an even number of numbers, the median is the mean of the two middle numbers. Thus, the median of the numbers.


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MODEThe mode is the most frequently occurring value. For the data in the table, Number of touchdown passes, the mode is 18 since more teams (4) had 18 touchdown passes than any other number of touchdown passes. With continuous data such as response time measured to many decimals, the frequency of each value is one since no two scores will be exactly the same. Therefore the mode of continuous data is normally computed from a grouped frequency distribution. The Grouped frequency distribution table shows a grouped frequency distribution for the target response time data. Since the interval with the highest frequency is 600700, the mode is the middle of that interval (650).


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Q.5. SELECT ANY TOPIC FOR RESEARCH AND EXPLAIN HOW YOU WILL USE BOTH SECONDARY AND PRIMARY SOURCES TO GATHER THE REQUIRED INFORMATION. Primary Sources of Data Primary sources are original sources from which the researcher directly collects data that has not been previously collected, e.g., collection of data directly by the researcher on brand awareness, brand preference, and brand loyalty and other aspects of consumer behavior, from a sample of consumers by interviewing them. Primary data is first hand information collected through various methods such as surveys, experiments and observation, for the purposes of the project immediately at hand. The advantages of primary data are It is unique to a particular research study It is recent information, unlike published information that is already available The disadvantages are It is expensive to collect, compared to gathering information from available Sources Data collection is a time consuming process It requires trained interviewers and investigators 2 Secondary Sources of Data These are sources containing data, which has been collected and compiled for another purpose. Secondary sources may be internal sources, such as annual reports, financial statements, sales reports, inventory records, minutes of meetings and other information that is available within the firm, in the form of a marketing information system. They may also be external sources, such as government agencies (e.g. census reports, reports of government departments), published sources (annual reports of currency and finance published by the Reserve Bank of India, publications of international organizations such as the UN, World Bank and International Monetary Fund, trade and financial journals, etc.), trade associations (e.g. Chambers of Commerce) and commercial services (outside suppliers of information).


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Methods of Data Collection: The researcher directly collects primary data from its original sources. In this case, the researcher can collect the required data precisely according to his research needs and he can collect them when he wants and in the form that he needs it. But the collection of primary data is costly and time consuming. Yet, for several types of social science research, required data is not available from secondary sources and it has to be directly gathered from the primary sources. Primary data has to be gathered in cases where the available data is inappropriate, inadequate or obsolete. It includes: socio economic surveys, social anthropological studies of rural communities and tribal communities, sociological studies of social problems and social institutions, marketing research, leadership studies, opinion polls, attitudinal surveys, radio listening and T.V. viewing surveys, knowledge-awareness practice (KAP) studies, farm management studies, business management studies etc. There are various methods of primary data collection, including surveys, audits and panels, observation and experiments. 1. Survey Research A survey is a fact-finding study. It is a method of research involving collection of data directly from a population or a sample at a particular time. A survey has certain characteristics: It is always conducted in a natural setting. It is a field study. It seeks responses directly from the respondents. It can cover a very large population. It may include an extensive study or an intensive study

A survey involves the following steps Selection of a problem and its formulation Preparation of the research design Operation concepts and construction of measuring indexes and scales Sampling Construction of tools for data collection Field work and collection of data


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Processing of data and tabulation o Analysis of data o Reporting

There are four basic survey methods, which include: Personal interview Telephone interview Mail survey and Fax survey Personal Interview Personal interviewing is one of the prominent methods of data collection. It may be defined as a two-way systematic conversation between an investigator and an informant, initiated for obtaining information relevant to a specific study. It involves not only conversation, but also learning from the respondents gestures, facial expressions and pauses, and his environment. Interviewing may be used either as a main method or as a supplementary one in studies of persons. Interviewing is the only suitable method for gathering information from illiterate or less educated respondents. It is useful for collecting a wide range of data, from factual demographic data to highly personal and intimate information relating to a persons opinions, attitudes, values, beliefs, experiences and future intentions. Interviewing is appropriate when qualitative information is required or probing is necessary to draw out the respondent fully. Where the area covered for the survey is compact, or when a sufficient number of qualified interviewers are available, personal interview is feasible. Interview is often superior to other data-gathering methods. People are usually more willing to talk than to write. Once rapport is established, even confidential information may be obtained. It permits probing into the context and reasons for answers to questions. Interview can add flesh to statistical information. It enables the investigator to grasp the behavioral context of the data furnished by the respondents. It permits the investigator to seek clarifications and brings to the forefront those questions, which for some reason or the other the respondents do not want to answer. Interviewing as a method of data collection has certain characteristics.


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They are: 1. The participants the interviewer and the respondent are strangers; hence, the investigator has to get himself/herself introduced to the respondent in an appropriate manner. 2. The relationship between the participants is a transitory one. It has a fixed beginning and termination points. The interview proper is a fleeting, momentary experience for them. 3. The interview is not a mere casual conversational exchange, but a conversation with a specific purpose, viz., obtaining information relevant to a study. 4. The interview is a mode of obtaining verbal answers to questions put verbally. 5. The interaction between the interviewer and the respondent need not necessarily be on a face-to-face basis, because the interview can also be conducted over the telephone. 6. Although the interview is usually a conversation between two persons, it need not be limited to a single respondent. It can also be conducted with a group of persons, such as family members, or a group of children, or a group of customers, depending on the requirements of the study. 7. The interview is an interactive process. The interaction between the interviewer and the respondent depends upon how they perceive each other. 8. The respondent reacts to the interviewers appearance, behavior, gestures, facial expression and intonation, his perception of the thrust of the questions and his own personal needs. As far as possible, the interviewer should try to be closer to the social-economic level of the respondents. 9. The investigator records information furnished by the respondent in the interview. This poses a problem of seeing that recording does not interfere with the tempo of conversation. 10. Interviewing is not a standardized process like that of a chemical technician; it is rather a flexible, psychological process. 3 Telephone Interviewing Telephone interviewing is a non-personal method of data collection. It may be used as a major method or as a supplementary method. It will be useful in the following situations:


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1. When the universe is composed of those persons whose names are listed in telephone directories, e.g. business houses, business executives, doctors and other professionals. 2. When the study requires responses to five or six simple questions, e.g. a radio or television program survey. 3. When the survey must be conducted in a very short period of time,provided the units of study are listed in the telephone directory. 4. When the subject is interesting or important to respondents, e.g. a survey relating to trade conducted by a trade association or a chamber of commerce, a survey relating to a profession conducted by the concerned professional association. 5. When the respondents are widely scattered and when there are many call backs to make. 4. Group Interviews A group interview may be defined as a method of collecting primary data in which a number of individuals with a common interest interact with each other. In a personal interview, the flow of information is multi dimensional. The group may consist of about six to eight individuals with a common interest. The interviewer acts as the discussion leader. Free discussion is encouraged on some aspect of the subject under study. The discussion leader stimulates the group members to interact with each other. The desired information may be obtained through selfadministered questionnaire or interview, with the discussion serving as a guide to ensure consideration of the areas of concern. In particular, the interviewers look for evidence of common elements of attitudes, beliefs, intentions and opinions among individuals in the group. At the same time, he must be aware that a single comment by a member can provide important insight. Samples for group interviews can be obtained through schools, clubs and other organized groups. 5. Mail Survey The mail survey is another method of collecting primary data. This method involves sending questionnaires to the respondents with a request to complete them and return them by post. This can be used in the case of educated respondents only. The mail questionnaires should be simple so that the respondents can easily understand the questions and answer them. It should preferably contain mostly closedended and multiple choice questions, so that it could be completed within a few minutes. The distinctive feature of the mail survey is that the questionnaire is selfadministered by the respondents themselves and the responses are recorded by them and not by the investigator, as in the case of personal interview method. It does not involve face-to-face conversation between the investigator and the respondent.


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Communication is carried out only in writing and this requires more cooperation from the respondents than verbal communication. The researcher should prepare a mailing list of the selected respondents, by collecting the addresses from the telephone directory of the association or organization to which they belong. The following procedures should be followed a covering letter should accompany a copy of the questionnaire. It must explain to the respondent the purpose of the study and the importance of his cooperation to the success of the project. Anonymity must be assured. result, it is not desirable to reveal it. In this case, a disguised organization name may be used. A self-addressed stamped envelope should be enclosed in the covering letter. After a few days from the date of mailing the questionnaires to the respondents, the researcher can expect the return of completed ones from them. The progress in return may be watched and at the appropriate stage, follow-up efforts can be made. The response rate in mail surveys is generally very low in developing countries like India. Certain techniques have to be adopted to increase the response rate. They are: 1. Quality printing: The questionnaire may be neatly printed on quality light colored paper, so as to attract the attention of the respondent. 2. Covering letter: The covering letter should be couched in a pleasant style, so as to attract and hold the interest of the respondent. It must anticipate objections and answer them briefly. It is desirable to address the respondent by name. 3. Advance information: Advance information can be provided to potential respondents by a telephone call, or advance notice in the newsletter of the concerned organization, or by a letter. Such preliminary contact with potential respondents is more successful than follow-up efforts. 4. Incentives: Money, stamps for collection and other incentives are also used to induce respondents to complete and return the mail questionnaire. 5. Follow-up-contacts: In the case of respondents belonging to an organization, they may be approached through someone in that organization known as the researcher. 6. Larger sample size: A larger sample may be drawn than the estimated sample size. For example, if the required sample size is 1000, a sample of 1500 may be drawn. This may help the researcher to secure an effective sample size closer to the required size.


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Q 6. A. EXPLAIN THE ROLE OF GRAPHS AND DIAGRAMS? Answer Roles of Graphs Graph is a diagram, as a curve, broken line, or series of bars, representing various kinds of quantitative information and relationships, such as the successive changes in a variable quantity or quantities. The graphs which are most commonly used in visual aids are Bar graphs, Pie Charts, Line graphs and Scatter diagrams. Graphs play a very important role during presentations because they make the data easier to understand and interpretations and comparisons can be made quickly. They are useful in presentations also because they can summarize large amounts of data and can convey the basic idea of the research. Graphs really help the audience in absorbing the data as they are simple to interpret and are appealing. By using graphs, variations and trends in data can be showed clearly and they show how the values of particular variables change over time. Graphs also help in determining the relationship between variables. A graph is an abstract data structure that is meant to implement the graph and hyper graph concepts from mathematics. A graph data structure consists of a finite (and possibly mutable) set of ordered pairs, called edges or arcs, of certain entities called nodes or vertices. As in mathematics, an edge(x,y) is said to point or go from x to y. The nodes may be part of the graph structure, or may be external entities represented by integer indices or references. A graph data structure may also associate to each edge some edge value, such as a symbolic label or a numeric attribute (cost, capacity, length, etc.). Roles of Diagrams Diagram is a graphic representation of an algebraic or geometric relationship. Role Activity Diagrams (RADs) are a useful way of describing processes. They are valuable in documenting processes as they are now, and as they might be in the future. The main part of the SPRINT BPR Methodology describes the ways in which Role Activity Diagrams can be used within a broader change project. This guide tells you how to draw Role Activity Diagrams.


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The guide will show you that Role Activity Diagrams are a reasonably simple diagramming technique. It is not difficult to learn how to draw them and it is not difficult for most people to interpret them. The guide progresses by introducing each of the main constructs of the Role Activity Diagram. It describes these in turn, giving advice about the drawing conventions. This is syntactic guidance. In addition to these syntactic skills, the creation of Role Activity Diagrams relies upon an ability to scope a study, to decide on the level of interest and to determine the boundaries of each role in a diagram. This is where the real skill of using Role Activity Diagrams comes in but such issues are addressed only partially in this report. In reality the reader will rely upon experience gained through using Role Activity Diagrams in projects. This experience will teach how Role Activity Diagrams can best be used, and what they are most useful for. Q.6.B. WHAT ARE THE TYPES AND GENERAL RULES FOR GRAPHICAL REPRESENTATION OF DATA? Answer REPRESENTATION OF DATA Besides the tabular form, the data may also be presented in some graphic or diagrammatic form. The transformation of data through visual methods like graphs, diagrams, maps and charts is called representation of data.

The need of representing data graphically:Graphics, such as maps, graphs and diagrams, are used to represent large volume of data. They are necessary: If the information is presented in tabular form or in a descriptive record, it becomes difficult to draw results. Graphical form makes it possible to easily draw visual impressions of data. The graphic method of the representation of data enhances our understanding. It makes the comparisons easy. Besides, such methods create an imprint on mind for a longer time.


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It is a time consuming task to draw inferences about whatever is being presented in nongraphical form. It presents characteristics in a simplified way. These makes it easy to understand the patterns of population growth, distribution and the density, sex ratio, agesex composition, occupational structure, etc. General Rules for Drawing Graphs, Diagrams and Maps 1. Selection of a Suitable Graphical Method Each characteristic of the data can only be suitably represented by an appropriate graphical method. For example, To show the data related to the temperature or growth of population between different periods in time line graph are used. Similarly, bar diagrams are used for showing rainfall or the production of commodities. The population distribution, both human and livestock, or the distribution of the crop producing areas are shown by dot maps. The population density can be shown by choropleth maps. Thus, it is necessary and important to select suitable graphical method to represent data. 2. Selection of Suitable Scale Each diagram or map is drawn to a scale which is used to measure the data. The scale must cover the entire data that is to be represented. The scale should neither be too large nor too small. 3. Design The diagram or map should have following design: Title: The title of the diagram/map must be clear and include The name of the area, Reference year of the data used and The caption of the diagram. These are written with different font sizes and thickness. The title, subtitle and the corresponding year is shown in the centre at the top of the map/diagram.


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Legend or Index: The index must clearly explain the colours, shades, symbols and signs used in the map and diagram. A legend is shown either at the lower left or lower right side of the map sheet. Direction the maps should show the direction North and properly placed on the top. Types of Diagrams The diagrams and the maps is of following types: (i) One-dimensional diagrams such as line graph, poly graph, bar diagram, histogram, age, sex,pyramid, etc.; (ii) Two-dimensional diagram such as pie diagram and rectangular diagram; (iii) Three-dimensional diagrams such as cube and spherical diagrams. The most commonly drawn diagrams and maps are: Line graphs Bar diagrams Pie diagram Wind rose and star diagram Flow Charts 1. Line Graph The line graphs are usually drawn to represent the time series data related to the temperature, rainfall, population growth, birth rates and the death rates. Construction of a Line Graph 1 st step: Round the data to be shown up to the 1 digit of even numbers. 2nd step: Draw X and Y-axis. Mark the time series variables (years/months) on the X axis andthe data quantity/value to be plotted on Y axis. 3rd step: Choose an appropriate scale to show data and label it on Y-axis. If the data involves anegative figure then the selected scale should also show it. 4th step: Plot the data to depict year/month-wise values according to the selected scale on Yaxis,mark the location of the plotted values by a dot and join these dots by a free hand drawn line.


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A line graph to represent the data


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2. Polygraph Polygraph is a line graph in which two or more than two variables are shown on a same diagram by different lines. It helps in comparing the data. Examples which can be shown as polygraph are: The growth rate of different crops like rice, wheat, pulses in one diagram. The birth rates, death rates and life expectancy in one diagram. Sex ratio in different states or countries in one diagram. Construction of a Polygraph. All steps of construction of polygraph are similar to that of line graph. But different lines are drawn to indicate different variables. A polygraph to compare the variables.

3. Bar Diagram It is also called a columnar diagram. The bar diagrams are drawn through columns of equal width. Following rules were observed while constructing a bar diagram: (a) The width of all the bars or columns is similar. (b) All the bars should are placed on equal intervals/distance. (c) Bars are shaded with colours or patterns to make them distinct and attractive.


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Three types of bar diagrams are used to represent different data sets: The simple bar diagram Compound bar diagram Polybar diagram. Simple Bar Diagram

A simple bar diagram is constructed for an immediate comparison. It is advisable to arrange the given data set in an ascending or descending order and plot the data variables Accordingly. However, time series data are represented according to the sequencing of the time period. A simple bar diagram.

Construction Steps: Draw X and Y-axes on a graph paper. Take an interval and mark it on Y-axis to plot data. Divide X-axis into equal parts to draw bars. The actual values will be plotted according to the selected scale.


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4. Line and Bar Graph The line and bar graphs as drawn separately may also be combined to depict the data related to some of the closely associated characteristics such as the climatic data of mean monthly temperatures and rainfall. A Line and bar Graph.


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5. Multiple Bar Diagram Multiple bar diagrams are constructed to represent two or more than two variables for the purpose of comparison. For example, a multiple bar diagram may be constructed to show proportion of males and females in the total, rural and urban population or the share of canal,tube well and well irrigation in the total irrigated area in different states.

(a) Mark time series data on X-axis and variable data on Y-axis as per the selected scale. (b) Plot the data in closed columns. 6. Compound Bar Diagram When different components are grouped in one set of variable or different variables of one component are put together, their representation is made by a compound bar diagram. In this method, different variables are shown in a single bar with different rectangles.


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Construction (a) Arrange the data in ascending or descending order. (b) A single bar will depict the set of variables by dividing the total length of the bar as per percentage. 7. Pie Diagram Pie diagram is another graphical method of the representation of data. It is drawn to depict the total value of the given attribute using a circle. Dividing the circle into corresponding degrees of angle then represent the sub sets of the data. Hence, it is also called as Divided Circle Diagram.


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The angle of each variable is calculated using the following formulae.

If data is given in percentage form, the angles are calculated using the given formulae.

Calculation of Angles (a) Arrange the data on percentages in an ascending order. (b) Calculate the degrees of angles for showing the given values (c) It could be done by multiplying percentage with a constant of 3.6 as derived by dividing the total number of degrees in a circle by 100, i. e. 360/100. (d) Plot the data by dividing the circle into the required number of divisions to show the share different regions/countries Construction (a) Select a suitable radius for the circle to be drawn. A radius of 3, 4 or 5 cm may be chosen for the given data set. (b) Draw a line from the centre of the circle to the arc as a radius.


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(c) Measure the angles from the arc of the circle for each category of vehicles in an ascending order clock-wise, starting with smaller angle. (d) Complete the diagram by adding the title, sub title, and the legend. The legend mark be chosen for each variable/category and highlighted by distinct shades/colours.

Precautions(a) The circle should neither be too big to fit in the space nor too small to be illegible. (b) Starting with bigger angle will lead to accumulation of error leading to the plot of the smaller angle difficult. 8. Flow Maps/Chart Flow chart is a combination of graph and map. It is drawn to show the flow of commodities or people between the places of origin and destination. It is also called as Dynamic Map. Transport map, which shows number of passengers, vehicles, etc., is the best example of a flow chart. These charts are drawn using lines of proportional width. Many government agencies prepare flow maps to show density of the means of transportation on different routes. The flow maps/ charts are generally drawn to represent two the types of data as given below: 1. The number and frequency of the vehicles as per the direction of their movement 2. The number of the passengers and/or the quantity of goods transported. Requirements for the Preparation of a Flow Map: (a) A route map depicting the desired transport routes along with the connecting stations. (b) The data pertaining No. of trains of selected routes of to the flow of goods, Delhi and Adjoining areas services, number of vehicles, etc., along with the point of origin and destination of the movements. (c) The selection of a scale through which the data related to the quantity of passengers and goods or the number of vehicles is to be represented.


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Construction (a) Take an outline map of Delhi and adjoining areas in which railway line and the nodal stations are depicted. (b) Select a scale to represent the number of trains. Here, the maximum number is 50 and the minimum is 6. If we select a scale of 1cm = 50 trains, the maximum and minimum numbers will be represented by a strip of 10 mm and 1.2 mm thick lines respectively on the map. (c) Plot the thickness of each strip of route between the given rail route. (d) Draw a terraced scale as legend and choose distinct sign or symbol to show the nodal points (stations) within the strip. Thematic Maps Varieties of maps are drawn to understand the patterns of the regional distributions or the characteristics of variations over space these maps are known as the distribution maps or thematic maps. Requirements for Making a Thematic Map (a) State/District level data about the selected theme. (b) Outline map of the study area along with administrative boundaries.


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(c) Physical map of the region. For example, physiographic map for population distribution and relief and drainage map for constructing transportation map. Rules for Making Thematic Maps (i) The drawing of the thematic maps must be carefully planned. The final map should properly reflect the following components: a. Name of the area b. Title of the subject-matter c. Source of the data and year d. Indication of symbols, signs, colours, shades, etc. e. Scale (ii) The selection of a suitable method to be used for thematic mapping. Classification of Thematic Maps based on Method of Construction The thematic maps are generally, classified into quantitative and non-quantitative maps. The quantitative maps are drawn to show the variations within the data. For example, maps depicting areas receiving more than 200 cm, 100 to 200 cm, 50 to 100 cm and less than 50 cm of rainfall are referred as quantitative maps. These maps are also called as statistical maps. The non-quantitative maps, on the other hand, depict the nonmeasurable characteristics in the distribution of given information such as a map showing high and low rainfall-receiving areas. These maps are also called as qualitative maps. The construction of quantitative maps: There are three types of quantitative maps (a) Dot maps (b) Choropleth maps (c) Isopleths maps


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9. Dot Maps The dot maps are drawn to show the distribution of phenomena such as population, cattle, types of crops, etc. The dots of same size as per the chosen scale are marked over the given administrative units to highlight the patterns of distributions. Requirement (a) An administrative map of the given area showing state/district/block boundaries. (b) Statistical data on selected theme for the chosen administrative units, i.e., total population, cattle etc. (c) Selection of a scale to determine the value of a dot. (d) Physiographic map of the region especially relief and drainage maps. Precaution (a) The lines demarcating the boundaries of various administrative units should not be very thick and bold. (b) All dots should be of same size.


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Construction a. Select the size and value of a dot. b. Determine the number of dots in each state using the given scale. For example, number of dots in Maharashtra will be 9,67,52,247/100,000 = 967.52. It may be rounded to 968, as the fraction is more than 0.5. c. Place the dots in each state as per the determined number in all states. d. Consult the physiographic/relief map of India to identify mountainous, desert, and/or snow covered areas and mark lesser number of dots in such areas.


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10. Choropleth Map The choropleth maps are also drawn to depict the data characteristics as they are related to the administrative units. These maps are used to represent the density of population, literacy/growth rates, sex-ratio, etc. Requirement for drawing Choropleth Map a. A map of the area depicting different administrative units. b. Appropriate statistical data according to administrative units. Steps to be followed a. Arrange the data in ascending or descending order. b. Group the data into 5 categories to represent very high, high, medium, low and very low concentrations. c. The interval between the categories may be identified on the following formulae i.e. Range/5 and Range = maximum value minimum value. d. Patterns, shades or colour to be used to depict the chosen categories should be marked in an increasing or decreasing order.


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Construction (a) Arrange the data in ascending order as shown above. (b) Identify the range within the data. In the present case, the states recording the lowest and highest literacy rates are Bihar (47%) and the Kerala (90.9%) respectively. Hence, the range would be 91.0 47.0 = 44.0 (c) Divide the range by 5 to get categories from very low to very high. (44.0/ 5 = 8.80). We can convert this value to a round number 9.0. (d) Determine the number of the categories along with range of each category. Add 9.0 to the lowest value of 47.0 as so on. We will finally get following categories: 47 56 Very low (Bihar, Jharkhand, Arunachal Pradesh, Jammu and Kashmir) 56 65 Low (Uttar Pradesh, Rajasthan, Andhra Pradesh, Meghalaya, Orissa, Assam, Madhya Pradesh, Chhattisgarh) 65 74 Medium (Nagaland, Karnataka, Haryana, West Bengal, Sikkim, Gujarat, Punjab, Manipur, Uttaranchal, Tripura, Tamil Nadu) 74 83 High (Himachal Pradesh, Maharashtra, Delhi, Goa) 83 92 Very High (Mizoram, Kerala)


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(e) Assign shades/pattern to each category ranging from lower to higher hues. (f) Prepare the map as shown in Fig. (g) Complete the map with respect to the attributes of map design. 11. Isopleth Map Variations in the degrees of slope, temperature, occurrence of rainfall, may be represented by drawing the lines of equal values on a map. All such maps are termed as Isopleths Map. The word Isopleths is derived from ISO meaning equal and Plath means lines. Thus, an imaginary line, which joins the places of equal values, is referred as Isopleths. The more frequently drawn isopleths include Isotherm (equal temperature), Isobar (equal pressure), Isohyets (equal rainfall), Isonephs (equal cloudiness), Isohels (equal sunshine), contours (equal heights), Isobaths (equal depths), Isohaline (equal salinity), etc. Requirement (a) Base line map depicting point location of different places. (b) Appropriate data of temperature, pressure, rainfall, etc. over a definite period of time. (c) Drawing instrument specially French Curve, etc. Rules to be observed (a) An equal interval of values be selected. (b) Interval of 5, 10, or 20 is supposed to be ideal. (c) The value of Isopleths should be written along the line on either side or in the middle by breaking the line. Interpolation Interpolation is used to find the intermediate values between the observed values of at two stations/locations. Generally, drawing of isopleths joining the places of same value is also termed as interpolation. Method of Interpolation: For interpolation, follow the following steps: (a) Firstly, determine the minimum and maximum values given on the map. (b) Calculate the range of value i.e. Range = maximum value minimum value. (c) Based on range, determine the interval in a whole number like 5, 10, 15, etc. The exact point of drawing an Isopleths is determined by using the following formulae. Point of Isopleth = Interval


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The interval is the difference between the actual value on the map and interpolated value. For example, in an Isotherm map of two places show 28 C and 33 C and you want to draw 30C isotherm, measure the distance between the two points. Suppose the distance is 1cm or 10 mm and the difference between 28 and 33 is 5, thus, exact point of 30 will be plotted 4mm away from 28C or 6mm ahead of 33C.


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