SOURCES OF DATA

SOURCES OF DATA

BY,

DIVYA K NAIR

CONTENTSINTRODUCTIONPURPOSE OF DATA COLLECTIONSOURCES OF DATATYPES OF DATA03-10-20152

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3RESEARCHRe + Search = ResearchThe systematic investigation into and study of materials, sources, etc., in order to establish facts and reach new conclusions. Research Methodology - Theprocessused to collectinformation anddatafor the purpose ofmakingbusinessdecisions. Themethodologymay includepublicationresearch,interviews,surveysand other researchtechniques, and could include both present and historical information.

INTRODUCTION TO SOURCE OF DATAData are the basic inputs to any decision making process.Data collection is a term used to describe a process of preparing and collecting data.Systematic gathering of data for a particular purpose from various sources, that has been systematically observed, recorded, organized is referred as data collection.03-10-20154

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PURPOSE OF DATA COLLECTIONThe purpose of data collection areto obtain information to keep on record to make decisions about important issuesto pass information on to others03-10-20155

SOURCES OF DATA

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PRIMARY SOURCESData which are collected from the field under the control and supervision of an investigator.Primary data means original data that has been collected specially for the purpose in mind.This type of data are generally a fresh and collected for the first time.It is useful for current studies as well as for future studies.03-10-20157

SECONDARY SOURCESData gathered and recorded by someone else prior to and for a purpose other than the current project. It involves less cost, time and effort.Secondary data is data that is being reused. Usually in a different context. 03-10-20158

EXAMPLES OF PRIMARY AND SECONDARY SOURCESPRIMARY SOURCESSECONDARY SOURCESData and Original ResearchNewslettersDiaries and Journals Chronologies Speeches and InterviewsMonographs (a specialized book or article) Letters and MemosMost journal articles (unless written at the time of the event Autobiographies and Memoirs Abstracts of articlesGovernment DocumentsBiographies

03-10-20159TABLE 1 Examples of primary and secondary sources

COMPARISON OF PRIMARY AND SECONDARY SOURCESPRIMARY SOURCESSECONDARY SOURCESReal time dataPast dataSure about sources of dataNot sure about sources of dataHelp to give results/findingRefining the problemCostly and Time consuming process.Cheap and No time consuming processAvoid biasness of response dataCan not know if data biasness or notMore flexibleLess Flexible

03-10-201510TABLE 2 Comparison of primary and secondary sources

TERITARY SOURCESA teritary source presents summaries or condensed versions of materials, usually with references back to the primary and/or secondary sources.They can be a good place to look up acts or get a general overview of a subject, but they rarely contain original material.03-10-201511

EXAMPLES OF TERITARYSOURCESDictionariesEncyclopaediasHandbooks03-10-201512

TYPES OF DATA

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CATEGORICAL DATAA set of data is said to be categorical if the values or observations belonging to it can be stored according to category. 03-10-201514

NOMINAL DATAA set of data is said to be nominal if the values or observations belonging to it can be a code in the form of a number where the numbers are simply labels. It is possible to count but not order or measure nominal data.03-10-201515

ORDINAL DATAA set of data is said to be ordinal if the values or observations belonging to it can be ranked or have a rating scale attached. Ordinal scales (data) ranks objects from one largest to smallest or first to last and so on.It is possible to count and order but not measure ordinal data.03-10-201516

METHODS OF COLLECTING DATA

INTRODUCTIONOBSERVATION METHODTYPES OF OBSERVATIONOBSERVATIONSFIELD INVESTIGATION METHOD SURVEYCASE STUDY METHODINTERVIEWSCONTENTS03-10-201518

Data are the raw numbers or facts which must be processed to give useful information.Data collection is expensive, so it is sensible to decide what the data will be used for before they are collected. In principle, there is an optimal amount of data which should be collected. These data should be as accurate as possible. INTRODUCTION03-10-201519

Observation method is a technique in which the behavior of research subjects is watched and recorded without any direct contact.OBSERVATION METHOD

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It is the main method of Psychology and serves as the basis of any scientific enquiry. Primary material of any study can be collected by this method. Observational method of research concerns the planned watching, recording and analysis of observed method. This method requires careful preparation and proper training for the observer.CHARACTERISTICS

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Structured ObservationUnstructured ObservationParticipant ObservationNon - Participant ObservationControlled ObservationUncontrolled Observation

TYPES OF OBSERVATION

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STRUCTURED vs UNSTRUCTURED OBSERVATION

STRUCTURED OBSERVATION UNSTRUCTURED OBSERVATIONInstructuredobservation, the researcher specifies in detail what is to be observed and how the measurements are to be recorded.It is appropriate when the problem is clearly defined and the information needed is specified.Inunstructuredobservation, the researcher monitors all aspects of the phenomenon that seem relevant. It is appropriate when the problem has yet to be formulated precisely and flexibility is needed in observation to identify key components of the problem and to develop hypotheses.03-10-201523

23Unit 5: Collecting data

PARTICIPANT OBSERVATIONIf the observer observes by making himself, more or less, a member of the group he is observing so that he can experience what the members of the group experience, then the observation is called participant observation. NON PARTICIPANT OBSERVATIONWhen the observer observes as a detached emissary without any attempt on his part to experience through participation what others feel, the observation of this type is known as non-participant observation.PARTICIPANT vs NON PARTICIPANT OBSERVATION03-10-201524

CONTROLLED OBSERVATIONIf the observation takes place according to definite pre-arranged plans, involving experimental procedure, the same is termed as controlled observation. UNCONTROLLED OBSERVATIONIf the observation takes place in the natural setting, it may be termed as uncontrolled observation..CONTROLLED vs UNCONTROLLED OBSERVATION03-10-201525

OBSERVATIONSADVANTAGESMost direct measure of behaviorProvides direct informationEasy to complete, saves timeCan be used in natural or experimental settings

DISADVANTAGESMay require trainingObservers presence may create artificial situationPotential to overlook meaningful aspects Potential for misinterpretationDifficult to analyze

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26Unit 5: Collecting data

Anyactivityaimed at collectingprimary(originalor otherwise unavailable)data,usingmethodssuch as face-to-face interviewing, surveysand case study method is termed as field investigation.

FIELD INVESTIGATION

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The survey is a non-experimental, descriptive research method. Surveys can be useful when a researcher wants to collect data on phenomena that cannot be directly observed (such as opinions on library services). In a survey, researchers sample a population.SURVEY03-10-201528

The Survey method is the technique of gathering data by asking questions to people who are thought to have desired information. A formal list of questionnaire is prepared. Generally a non disguised approach is used. The respondents are asked questions on their demographic interest opinion.

METHOD OF SURVEY

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Case study method is a common technique used in research to test theoretical propositions or questions in relation to qualitative inquiry. The strength of the case study approach is that it facilitates simultaneous analysis and comparison of individual cases for the purpose of identifying particular phenomena among those cases, and for the purpose of more general theory testing, development or construction.CASE STUDY METHOD

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A case study is a form of research defined by an interest in individual cases. It is not a methodology per se, but rather a useful technique or strategy for conducting qualitative research. The more the object of study is a specific, unique, bounded system, the more likely that it can be characterized as a case study. Once the case is chosen, it can be investigated by whatever method is deemed appropriate to the aims of the study.

WHAT IS IT?

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CAN BE USED TO TEST THEORIESCase studies are particularly useful for examining a phenomena in context. The case study methodology is designed to study a phenomenon or set of interacting phenomena in context when the boundaries between phenomenon and context are not clearly evident.The lack of distinction between phenomenon and context make case studies ideal for conducting exploratory research designed to stand alone or to guide the formulation of further quantitative research.

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32Eg the phenomena might be a widespread change in employment systems which has occurred at the same time as changes in labour laws. A case study might help you to understand the affect of the law in the context of a change in employment systems.

LENGTH OF TIMESome case studies may be a snap shot analysis of a particular event or occurrence. Other case studies may involve consideration of a sequence of events, often over an extended period of time, in order to better determine the causes of particular phenomena. 03-10-201533

33Both types have their own advantages and disadvantages, and which you decide on using will depend on what you are testing. The problem with a study which extends over a period of time can be getting access to the data or people to interview.

Interview is the verbal conversation between two people with the objective of collecting relevant information for the purpose of research.It is possible to use the interview technique as one of the data collection methods for the research.It makes the researcher to feel that the data what he collected is true and honest and original by nature because of the face to face interaction.

INTERVIEWS

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SAMPLING

CONTENTSSAMPLESAMPLING DESIGN PROCESSSAMPLING TECHNIQUESDATA PROCESSING AND ANALYSIS STRATEGIESGRAPHICAL REPRESENTATIONLEAST SQUARE METHOD

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SAMPLE

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THE SAMPLING DESIGN PROCESS

Define the Population

Determine the Sampling Frame

Select Sampling Technique(s)

Determine the Sample Size

Execute the Sampling Process

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SAMPLING TECHNIQUESSampling techniques are the processes by which the subset of the population from which you will collect data are chosen.

There are TWO general types of sampling techniques:1) PROBABILITY SAMPLING2) NON-PROBABILITY SAMPLING03-10-201539

CLASSIFICATION OF SAMPLING TECHNIQUES

Sampling Techniques

NonprobabilitySampling Techniques

ProbabilitySampling Techniques

JudgmentalSampling

Quota Sampling

SequentialSampling

SystematicSamplingStratifiedSamplingClusterSampling Simple RandomSampling

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PROBABILITY SAMPLINGA sample will be representative of the population from which it is selected if each member of the population has an equal chance (probability) of being selected.Probability samples are more accurate than non-probability samples They allow us to estimate the accuracy of the sample.It permit the estimation of population parameters.03-10-201541

TYPES OF PROBABILITY SAMPLINGSimple Random SamplingStratified Random SamplingSystematic SamplingCluster Sampling03-10-201542

SIMPLE RANDOM SAMPLINGSelected by using chance or random numbersEach individual subject (human or otherwise) has an equal chance of being selectedExamples: Drawing names from a hatRandom Numbers

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SYSTEMATIC SAMPLINGSelect a random starting point and then select every kth subject in the populationSimple to use so it is used often

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STRATIFIED SAMPLINGDivide the population into at least two different groups with common characteristic(s), then draw SOME subjects from each group (group is called strata or stratum)Results in a more representative sample

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CLUSTER SAMPLINGDivide the population into groups (called clusters), randomly select some of the groups, and then collect data from ALL members of the selected groupsUsed extensively by government and private research organizations Examples:Exit Polls

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NON-PROBABILITY SAMPLINGDEFINITIONThe process of selecting a sample from a population without using (statistical) probability theory.

NOTE THAT IN NON-PROBABILITY SAMPLINGeach element/member of the population DOES NOT have an equal chance of being included in the sample, andthe researcher CANNOT estimate the error caused by not collecting data from all elements/members of the population.03-10-201547

TYPES OF NON-PROBABILITY SAMPLINGQuota SamplingJudgemental SamplingSequential Sampling03-10-201548

QUOTA SAMPLINGDEFINITION Selecting participant in numbers proportionate to their numbers in the larger population, no randomization.

For example you include exactly 50 males and 50 females in a sample of 100.03-10-201549

JUDGMENTAL SAMPLINGDEFINITIONIt is a form of sampling in which population elements are selected based on the judgment of the researcher.

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SEQUENTIAL SAMPLINGSequential 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.

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DATA PROCESSING AND ANALYSIS STRATEGIESOverview of the stages of Data Analysis

Raw DataEditingCodingData FileAnalysis Inferential analysis Descriptive analysis 03-10-201552

EDITINGThe process of checking and adjusting responses in the completed questionnaires for omissions, legibility, and consistency and readying them for coding and storage.

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TYPES OF EDITING1. Field Editing Preliminary editing by a field supervisor on the same day as the interview to catch technical omissions, check legibility of handwriting, and clarify responses that are logically or conceptually inconsistent.2. In-house EditingEditing performed by a central office staff; often dome more rigorously than field editing03-10-201554

DATA CODING

A systematic way in which to condense extensive data sets into smaller analyzable units through the creation of categories and concepts derived from the data.

The process by which verbal data are converted into variables and categories of variables using numbers, so that the data can be entered into computers for analysis.

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CLASSIFICATIONMost research studies result in a large volume of raw data which must be reduced into homogeneous groups if we are to get meaningful relationships.Classification can be one of the following two types, according to the nature of the phenomenon involved. Classification according to attributes : Data are classified on the basis of common characteristics which can be either descriptive or numerical.Classification according to class interval : Data are classified on the basis of statistics of variables.

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TABULATIONWhen a mass of data has been assembled, it becomes necessary for the researcher to arrange the same in some kind of concise and logical order. This procedure is referred to as tabulation.Tabulation is an orderly arrangement of data in rows and columns.Tabulation is essential because :It conserves space and reduces explanatory and descriptive statement to a minimum.It facilitates the process of comparison.It provides a basis for various statistical computation.It facilitates the summation of items and detection of errors and omissions.03-10-201557

GRAPHICAL REPRESENTATIONAfter collecting data, the first task for a researcher is to organize and simplify the data so that it is possible to get a general overview of the results. One method for simplifying and organizing data is to construct a graphical representation.

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DISTRIBUTION GRAPHSIn a distribution graph, the score categories (X values) are listed on the X axis and the frequencies are listed on the Y axis. When the score categories consist of numerical scores from an interval or ratio scale, the graph should be either a histogram or a polygon. 03-10-201559

HISTOGRAMSIn a histogram, a bar is centered above each score (or class interval) so that the height of the bar corresponds to the frequency and the width extends to the real limits, so that adjacent bars touch.

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POLYGONSIn a polygon, a dot is centered above each score so that the height of the dot corresponds to the frequency. The dots are then connected by straight lines. An additional line is drawn at each end to bring the graph back to a zero frequency.

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BAR GRAPHSWhen the score categories (X values) are measurements from a nominal or an ordinal scale, the graph should be a bar graph. A bar graph is just like a histogram except that gaps or spaces are left between adjacent bars.

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SMOOTH CURVEIf the scores in the population are measured on an interval or ratio scale, it is customary to present the distribution as a smooth curve rather than a jagged histogram or polygon. The smooth curve emphasizes the fact that the distribution is not showing the exact frequency for each category.

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DESCRIPTIVE AND INFERENTIAL DATA ANALYSISDescriptive analysis is the study of distributions of one variable (described as unidimensional analysis) or two variables (described as bivariate analysis) or more than two variables (described as multivariate analysis).Is devoted to summarization and description of data. Inferential analysis is mainly on the basis of various test of significance for testing hypothesis inorder to determine with what validity data can be said to indicate some conclusions.Uses sample data to make inferences about a population03-10-201564

CORRELATION ANALYSISCorrelation a LINEAR association between two random variables.Correlation analysis show us how to determine both the nature and strength of relationship between two variables.When variables are dependent on time correlation is applied.Correlation lies between +1 to -1.A zero correlation indicates that there is no relationship between the variables.A correlation of 1 indicates a perfect negative correlation.A correlation of +1 indicates a perfect positive correlation.03-10-201565

SPEARMANS RANK COEFFICIENTA method to determine correlation when the data is not available in numerical form and as an alternative method, the method of rank correlation is used. Thus when the values of the two variables are converted to their ranks, and there from the correlation is obtained, the correlations known as rank correlation.

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COMPUTATION OF RANK CORRELATIONSpearmans rank correlation coefficient can be calculated when: Actual ranks givenRanks are not given but grades are given but not repeatedRanks are not given and grades are given and repeated

= 1 -Sdi2i=1i=n

n3 - n603-10-201567di = difference between ranks of ith pair of two variablesn = no. of pairs of observations

KARL PEARSONS COEFFICIENT OF CORRELATION03-10-201568

LEAST SQUARE METHODThe method of least squares is a standard approach to the approximate solution of over determined systems, i.e., sets of equations in which there are more equations than unknowns."Least squares" means that the overall solution minimizes the sum of the squares of the errors made in the results of every single equation.The goal is to find the parameter values for the model which best fits the data.03-10-201569

PROBLEM STATEMENT03-10-201570

Contd.03-10-201571

DATA ANALYSIS USING STATISTICAL PACKAGES

CONTENTSCHI SQUARE TESTANOVA TEST03-10-201573

CHI-SQUARE TESTThe chi-square test is an important test amongst the several tests of significance developed by statisticians.It was developed by Karl Pearson in1900.CHI SQUARE TEST is a non parametric test not based on any assumption or distribution of any variable.This statistical test follows a specific distribution known as chi square distribution.In general, the test we use to measure the differences between what is observed and what is expected according to an assumed hypothesis is called the chi-square test.03-10-201574

CONDUCTING CHI-SQUARE ANALYSIS03-10-201575

EXAMPLE 1: TESTING FOR PROPORTIONSLeaf Cutter AntsCarpenter AntsBlack AntsTotalObserved25181760Expected20202060O-E5-2-30(O-E)2E1.250.20.452 = 1.90

HO: Horned lizards eat equal amounts of leaf cutter, carpenter and black ants.HA: Horned lizards eat more amounts of one species of ants than the others.03-10-201576

EXAMPLE 1: TESTING FOR PROPORTIONS

2=0.05 = 5.99103-10-201577

EXAMPLE 1: TESTING FOR PROPORTIONSChi-square statistic: 2 = 5.991 Our calculated value: 2 = 1.90*If chi-square statistic > your calculated value, conclude that there is goodness of fit.5.991 > 1.90 we accept the hypothesis that there is goodness of fit between observed and expected values.. Leaf Cutter AntsCarpenter AntsBlack AntsTotalObserved25181760Expected20202060O-E5-2-30(O-E)2E1.250.20.452 = 1.90

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ANALYSIS OF VARIANCE (ANOVA)ANalysis Of VAriance (ANOVA) is the technique used to determine whether more than two population means are equal. Types of ANOVAOne way ANOVATwo way ANOVA03-10-201579

ONE WAY ANOVA03-10-201580The ANOVA used for the studying the differences among the influence of various categories of independent variables on a dependent variable is called one way ANOVA.Below are given the yield (in kg per acre for 5 trial plots of 4 varieties of treatment

Carry out an analysis of variance and state your conclusions.PLOT NO.TREATMENT1234142486880250665294362687678434786482552707066

EXAMPLE03-10-201581I (x1)II (x2)III (x3)IV (x4)4248688050665294626876783478648252707066240330330400

CONTD03-10-201582MSC = SSC/(k-1) = 2580/3 = 860MSE = SSE/(N-k) = 1656/(20-4) =103.5The degree of freedom = (k-1,N-k) = (3,16)k: no. of columns; N : total no. of observationsANOVA TABLE

F = 860/103.5 = 8.3NOTE: If MSC>MSE, F = MSC/MSE; If MSC