Uma Sekaran (1)



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BUSINESS RESEARCH METHODS OUTLINE DEFINITION OF RESEARCH WHY RESEARCH? TYPES OF RESEARCH HOW MANAGER FACILITATES RESEARCH SELECTION OF A RESEARCHER INTERNAL VERSUS EXTERNAL CONSULTANT-RESEARCHER 1 RESEARCH DEFINITIONS THE PROCESS OF FINDING SOLUTIONS TO PROBLEMS AFTER STUDYING AND ANALYSIS OF THE SITUATIONAL FACTORS THE PROCESS OF REFINING HUMAN EXPERIENCE FOR ADDING INTO THE STOCK OF KNOWLEDGE ANY ORGANIZED INQUIRY CARRIED OUT TO PROVIDE INFORMATION FOR SOLVING PROBLEMS 2 BUSINESS RESEARCH DEFINED SYSTEMATIC INQUIRY THAT PROVIDES INFORMATION TO GUIDE BUSINESS DECISIONS BY REPORTING,DESCRIBING,EXPLAINING AND PREDICTING ORGANIZED,SYSTEMATIC,DATABASED, CRITICAL,OBJECTIVE,SCIENTIFIC INQUIRY INTO A SPECIFIC PROBLEM TO FIND SOLUTIONS 3 WHY RESEARCH? NEED FOR INFORMATION FOR INFORMED –RATIONAL DECISION MAKING DUE TO : IMPROVED INFO AVAILABILITY TO COMPETITORS BETTER DATA COLLECTION AND ANALYTICAL TOOLS FOR OPTIMAL DECISIONMAKING PUBLIC MANDATE FOR BETTER QUALITY AT AFFORDABLE PRICES THE BASIS FOR RESEARCH IS THE CURIOSITY-THE EXCITEMENT TO KNOW THE UNKNOWN 4 AREAS OF BUSINESS RESEARCH ACCOUNTS;BUDGETS,COSTS PRICES FINANCE,OPERATIONS,MERGERS, INFO SYSTEMS,STOCK EXCHANGES ATTITUDES,HRM,STRATEGIES MARKETING,PRODUCT IMAGE,CONSUMER PREFERECES,PROMOTION,NEW PRODUCT DEVELOPMENT ETC 5 THE TYPES OF RESEARCH APPLIED RESEARCH PRACTICAL PROBLEM SOLVING OF CURRENT NATURERELATE TO POLICY,PERFORFANCE AND ACTIONS BASIC RESEARCH PROBLEMS OF THEORETICAL NATURE-GENERAL PROBLEMS NO IMPACT ON ACTIONS,POLICY,PERFORMANCEADDS TO BODY OF HUMAN KNOWLEDGE 6 WHY MANAGER SHOULD BE FAMILIAR WITH RESEARCH TOOLS IDENTIFY –SOLVE PROBLEMS DIFFERENTIATE GOOD AND BAD RESEARCH FACTORS INFLUENCING RESEARCH PROBLEM SITUATION TAKE CALCULATED RISK BY DECISIONS PREVENT POSSIBLE VESTED INTEREST IN A SITUATION COMBINE EXPERIENCE WITH SCIENTIFIC APPROACH IN DECISION MAKING 7 ISSUES IN ENGAGING RESEARCHERS PROBLEM SELECTION LOCATION ,SELECTION ,COMPARE CREDENTIALS UNDERSTANDING WITH CONSULTANT RELEVANCE OF INFORMATION,VARIABLES, METHODOLOGY,CONSULTANT REQUIREMENTS EXPLICT ROLES AND EXPECTATIONS OF CONSULTANT-RESEARCHER ORGANIZATIONAL VALUES 8 CARIFICATION INTERNAL CONSULTANT ADVANTAGES ACCEPTANCE BY EMPLOYEES LESS TIME NEEDED-KNOW THE ORGANIZATION AVAILABLE FOR IMPLEMENTATION LESS EXPENSIVE DISADVANTAGES LESS INNOVATIVE-STEREOTYPE VESTED INTERESTS EXPERTISE NOT VALUED 9 EXTERNAL CONSULTANT ADVANTAGES DIVERSE EXPERIENCE CREATIVE PROBLEM SOLVING SUITABLE FOR COMPLEX PROBLEM OR IF VESTED INTERESTS DISADVANTAGES EXPENSIVE NEED MORE TIME DIFFICULTY IN GETTING EMPLOYEES COOPERATION 10 RESEARCH KNOWLEDGE ENHANCES MANAGERIAL EFFECTIVENESS FACILITATE DECISION MAKING BY MANAGER BETTER UNDERSTANDING OF MODEL SUGGESTED BY CONSULTANT FACILITATE IMPLEMENTATION OPENS PROMOTION AVENUES BY BETTER DECISION MAKING UNDERSTANDS NEED ,COST AND BENEFIT OF RESEARCH 11 ETHICS IN RESEARCH STANDARDS OF BEHOVIOUR IN RESEARCH SAFE GUARDS INTERESTS OF MANAGERS,RESEARCHERS,ANALYSTS, DATA PROVIDERS ETC NEED FOR ETHICAL BEHAVIOUR AT ALL STAGES OF RESEARCH PROCEESS-DATA COLLECTION,ANALYSIS,PRESENTATION OF RESULTS 12 WHAT DOES RESEARCH DO? VERIFICATION OF SOLUTIONS,QUESTIONS,ANSWERS TESTS LOGICAL VALIDITY OF HUNCHES EXAMINES EMPIRICAL SUPPORT OF DEFINITIONS,ACCEPTED BELIEFS IDENTIFIES SOURCES –CAUSES OF TENDENCIES FINDS INTERRELATIONSHIPS BY EXAMINING HYPOTHESIS 13 SCIENTIFIC THINKING –OUTLINE THE NATURE OF SCIENCE THE STYLES OF THINKING THE HALLMARKS OF SCIENTIFIC INVESTIGATION THE HYPOTHETICO DEDUCTIVE METHOD 14 THE NATURE OF SCIENCE CRITICAL ACCOUNT OF LOGICAL JUSTIFICATION BEST CONCEIVED TRUTH IN EACH PERIOD TESTED KNOWIEDGE-FINDINGS NO UNIVERSALLY ACCEPTED AND STABLE AUTHORITY OF ASCERTAINING TRUTHS-LIKE WITCHCRAFT,MYSTIC POWERS,PARAPSYCHOLOGY,INHERITED TRAITS ETC 15 SCIENCE CONTIUED PHYSICAL SCIENCES BETTER DEVELOPED AND FUNDED,MORE OBJECTIVE,TESTABLE AND GENERALIZABLE THAN SOCIAL SCIENCES THE HUMAN BEHAVIOUR CHANGES NO FIELD OF SCIENCE IS FREE FROM GLARING IGNORANCE AND CONTRADICTIONS 16 STYLES OF THINKING IDEALISM-INTERPRET IDEAS -UNTESTED OPINION--LITERARY INFORMAL-EXISTENTIALISM EMPIRICAL-DATA BASED -SCIENTIFIC METHOD RATIONALISM-REASON BASED -SELFEVIDENT TRUTH-DEATH,RDRIVE 17 CONTINUED… -PERSONS OF AUTHORITY BY STATUS,RATHER THAN EXPERTISE,INTEGRITY,QUALITY -POSTULATIONAL –REDUCE PROBLEMS TO MATH TERMS AND DEDUCE FROM RELATIONSHIP OF VARIABLESEGSIMULATION OF PRICES,OUTPUTS TO OPTOMIZE PROFITS 18 THINKING CONTD… DEDUCTION-REASONED CONCLUSION BY GENERALIZING A KNOWN FACTMUST HAVE A VALID PREMISE AND TRUE IN REAL WORLD INDUCTION-CONCLUSION FROM OBSERVED EVIDENCE NOT STRONGLY RELATEDINFERENTIAL JUMP BEYOND THE EVIDENCE PRESENTED COMBINE INDUCTION AND DEDUCTION HALLMARKS OF SCINTIFIC INVESTIGATION PURPOSIVENESS RIGOR TESTABILITY REPLICABILITY PRECISION AND CONFIDENCE OBJECTIVITY GENERALIZABILITY PARSIMONY HALLMARKS CONTD… PURPOSIVENESS -AIM AND OBJECTIVE OF RESEARCH PROJECT RIGOR -EXACT METHOD OF DATA COLLECTION,ANALYSIS,CONCLUS TESTABILITY -STATISTICAL TEST OF CONCLUSION CONTINUED… REPLICABILITY -REPEATED UNDER SIMILAR CNDITIONS BY OTHERS PRECISION -CONFIDENCE INTERVAL,LIMITSOF ACCURACY CONFIDENCE -LEVEL,PROBABILITY OF RESULT WITHIN INTERVAL HALLMARKS CONT… OBJECTIVE -BASED ON REASONING EMPIRICAL DATA,NOT SUBJECTIVE GENERALIZABILITY -RESULTS OR CONCLUSIONS CAN BE GENERALIZED FOR USE BY OTHERS PARSIMONEY -SIMPLE TO HANDLE VARIABLES,ANALYSIS AND INTERPRET HYPOTHETICO DEDUCTIVE METHOD STEPS OBSERVATION PRELINFO GATHERING-PROBLEM IDENTIFICATION THEORY FORMULATION HYPOTHESIZING FURTHER DATA COLLECTION DATA ANALYSIS DEDUCTION-CONCLUSION STEPS CONT… OBSERVATION -SENSE CHANGES IN THE ENVIRONMENT WHICH ARE UNSATISFACTORYEGMIS NOT USED WELL BY MANAGERS PRELINFORMATION GATHERING -PROBLEM AREA IDENTIFICATION -INTERVIEW AND LITERATURE SURVEY THEORY FORMULATION -IDENTIFY VARIABLES AND THEIR RELATIOSHIP TO THE PROBLEM STEPS CONT… HYPOTHESIZING -FROM THEORETICAL RELATIONSHIP OF VARIABLES CERTAIN TESTABLE HYPOTHESIS CAN BE GENERATED FURTHER DATA COLLECTION -DATA NEEDED TO TEST THE HYPOTHESIS CONTINUED… DATA ANALYSIS -STATISTICAL ANALYSIS OF DATA TO SEE IF IT SUPPORTS THE HYPOTHESIS DEDUCTION -BY INTERPRETATION OF ANALYSIS OF RESULTS RESEARCH PROCESS OUTLINE OBSERVE BROAD PROBLEM AREA PRELLIMDATA COLLECTION PROBLEM IDENTIFICATION THEORETICAL FRAMEWORK HYPOTHESIS GENERATION RESEARCH DESIGN DATA COLLECT,ANALYSE ,INTERPRET HYPOTHESIS CONCLUSION PRESENTATION OF RESULTS MANAGERIAL DECISION MAKING 28 BROAD PROBLEM AREA CURRENT PROBLEMS ,COMPLAINTS,CONCEPTUAL ISSUES,POLICIES NEEDING IMPROVEMENT /EMPIRICAL ANSWERSEG SALES NOT PICKING UP FLEXI TIME PROBLEMS TRAINING PROGEFFECTIVENESS NEW INFORMATION SYSTEM NOT UTILISED PRELIMINARY DATA COLLECTION PRIMARY,SECONDARY DATA SOURCES UNSTRUCTURED INTERVIEW BACKGROUND DATA CONCEPTUAL FACTORS STRUCTURAL FACTORS ,MANAGEMENT PHILOSOPHY WORK ATTITUDES AND ENVIRONMENT LITERATURE SURVEY BACKGROUND DATA ORIGIN,HISTOY,OWNERSHIP CHARTER,PURPOSE LOCATION,DEVELOPMENT HUMAN,FINANCIAL AND OTHER RESOURCES FINANCIAL POSITION 5-10 YEARS STRUCTURAL FACTORS MANAGEMENT PHILOS ROLES,POSITIONS,WORK FLOW SPECIALISATION COMMUNICATION CHANNELS CNTROL SYSTEMS AND SPAN WORK ATTITUDES ENVIRONMENT BELIEFS IN JOB WORK INTERRELATIONSHIPS SUPERVISORY STYLE PARTICIPATION PROMOTION,DEVELOPMENT ,REWARD SYSTEM SOCIAL ORIENTATION OF FIRM UNDERSTANDING ISSUES RATHER THAN THE SYMPTOMS WHY LITERATURE SURVEY? REVIEW PUBLISHED AND UNPUBLISHED SOURCES NO REINVENTING THE WHEEL REVIEW ALL ASPECTS OF PROBLEM HELPS DEVELOP THEORETICAL FRAMEWORK FOR HYPOTHESIS TEST IMPROVES TESTABILITY/REPLICABILITY CLEAR AND CONCISE PROBLEM STATEMENT PERCEIVED TO BE SCIENTIFIC AND SIGNIFICANT CONDUCT LIT SURVEY BASED ON ISSUES AND INTERVIEW SURVEY RELEVANT VARIABLES BIBLIOGRAHICAL CITATION DATA BASES[DB] ABSTRACT DB-CITATIONS AND SUMMARIES FULLTEXT DB;GLOBAL NATIONAL SUBJECT AUTHOR TOPIC TEXT EXTRACT RELEVANT INFO ON LINE LIT REVIEW WRITING TO INCLSUBJECT INTRODUCTION,RESEARCH QUESTION AND TO BUILD ON PREVRESEARCH PROBLEM DEFINITION A WELL DEFINED STATEMENT GAP BETWEEN ACTUAL AND DESIRED STATE-PROBLEM SYMPYOMS NOT TO BE DEFINED AS PROBLEMS CLEAR CONCISE ISSUE STATEMENT TO BE INVESTIGATED FOR SOLUTIONEG HOW DOES NEW PACKAGING AFFECT PRODUCT SALES? WHAT ARE THE COMPNENTS OF GUALITY OF LIFE? IMPORTANT ISSUES MANAGERS TREAT SYMPTOMS AS PROBLEMS ANTECEDENTS-PROBLEMS-CONSEQUENCES INFORM WORKERS HOW RESAERCH FACILITATE THEIR WORK CONFIDENTIALITY OF RESEARCH PURPOSE? WHY THEORETICAL FRAMEWORK? CONCEPTUAL MODEL THAT DISCUSSES RELATIONSHIPS OF VARIABLES IMPORTANT TO INVESTIGATION FROM IT TESTABLE HYPOTHESIS FOR EXAMINING DEVELOPED IT IS CENTRAL TO PROBLEM INVESTIGATION OUTLINE:THEORY AND HYPOTHESIS VARIABLES DEPENEDENT,INDEPENDENT,MODERATING,INTERVENING THEORETICAL FRAMEWORK HYPOTHESIS DEVELOPMENT 39 VARIABLE DEFINED ANYTHING THAT CAN TAKE DIFFERENT VALUES AT VARIOUS TIMES FOR THE SAME PERSON/OBJECT OR SAME TIME FOR DIFFERENT PERSONS/OBJECTS EG EXAM SCORES,ABSENTEEISM, MOTIVATION DEPENDENT VARIALE? OF PRIMARY INTEREST TO RESEARCHER FOR ANALYSIS TO FIND OUT WHAT FACTORS INFLUENCE THE DV EXAMPLES: -WHY SALES ARE NOT UPTO THE MARK?DV-SALES -ANALYSIS OF DEBT EQUITY RATIO OF PRODUCTION FIRMS IN KARACHI DV-DEBT EQUITY RATIO INDEPENDENT VARIABLE? [IV] INFLUENCES THE DEPENDENT VARIABLE IN +/- WAY TO ESTABLISH CAUSAL RELATIONSHIP THE IV IS MANIPULATED EXAMPLES: -NEW PRODUCT SUCCESS>HIGHER FIRM STOCK PRICE[DV] -SUPERVISOR TRAINING>HIGHER PRODUCTION LEVEL[DV] MODERATING VARIABLE STRONG EFFECT ON IV-DV RELATIONSHIP AND MODIFIES IT >>NOOF BOOKS AT HOME>READING ABILITY –PARENT LITERACY{MV} >>WORKFORCE DIVERSITY>ORGANEFFECTIVENESS –MANAGEMENT EXPERTISE{MV} DISTINCTION IV-MV EXAMPLES TRG PROGRAM>WILLINGNESS TO LEARN –MV GROWTH NEEDS FORMAL TRG>EMPLOYEE PRODUCTIVITY-MV EMPLOYEE AGE WORKER INTERACTION>JOB WELL DONE- MV STAY TIME AFTER WORK INTERVENING VARIABLES SURFACES BETWEEN THE TIME IV OPERATES TO INFLUENCE DV UNTIL THEIR IMPACT ON DV WORK FORCE DIV>MANGMT EFFECT{MV}-CREATES SYNERGY[INT V]>ORG EFFECTIVENESS OCCURRENCE OF EACH VARIABLE DEPENDS ON GIVEN SITUATION FOR WHICH THEORETICAL FRAMEWORK ADVANCED VARIABLES SUMMARIZED IV CAUSES INT V MV EXPLAINS DEPENDENT EFFECT BETWEEN IV AND INT V INT V IS FUNCTION OF IV AND SURFACES BETWEEN TIMES IV AND ITS IMPACT ON DV-TIME DIMENSION DV VARIANCE EFFECT CAUSED BY IV –CONCERNS THE ANALYST TO FIND OUT WHAT INFLUENCES THE VARIABLE THEORETICAL FRAMEWORK FEATURES IDENTIFY AND LABEL RELEVANT VARIABLE S DISCUSS RELATIONSHIP OF VARIABLES TO EACHOTHER INDICATE DIRECTION OF RELATIONSHIP + OR -- REASONS FOR RELATIONSHIP LITERATURE SURVEY SCHEMATIC DIAGRAM THEORET FRAMEW EXAMPLE COMMUNICATION COCKPIT CREW COMMUNICATIN GROUND STAFF DECENTRALIZATION –INDEPENDENT VARIABLES TRAINING- MODERATING VARIABLE AIR SAFETY CONTROL VIOLATIONS-DEPENDENT VARIABLE HYPOTHESIS DEFINED A FORMAL TESTABLE STATEMENT LOGICALLY ASSUMED RELATIONSHIP BETWEEN VARIABLES AS A TESTABLE STATEMENT THEORIZED RELATIONSHIP OF VARIABLES THAT CAN BE SCIENTIFICALLY TESTED BY ANALYSIS FOR CLUES TO PROBLEM SOLUTION HYPOTHESIS EXAMPLES IF THEN STATEMENT-IF EMPLOYEES ARE HEALTHY THEY WILL TAKE LEAVE LESS FREQUENTLY DIRECTIONAL-MORE OR LESS THAN –THE GREATER THE STRESS IN THE JOB THE LOWER THE JOB SATISFATION NON DIRECTIONAL-THERE IS A RELATIONSHIP BETWEEN AGE AND JOB SATISFATION NULL HYPOTHESIS STATES NO SIGNIFICANT RELATIONSHIP BETWEEN VARIABLES OR NO SIGNIFICANT DIFFERENCE BETWEEN MEANS OF TWO GROUPS Ho:Um=Uw MOTIVATION LEVEL OF MEN AND WOMEN Ho:p=o ALTERNATE HYPOTHESIS STAEMENT EXPRESSING RELATIONSHIP BETWEEN VARIABLES-DIFFBETWEEN GROUPS Ha:Um< Uw Ha:po RESEARCH DESIGN OUTLINE PURPOSE OF STUDY TYPE OF INVESTIGATION RESEARCHER INTERFERENCE STUDY SETTING UNITS OF ANALYSIS TIME HORIZON 53 PURPOSE OF STUDY EXPLORATION:SITUATION UNKNOWN,PRELIMINFO FOR COMPREHENSIVE STUDY LATEREGETHICAL VALUES OF DIFFCULTURES DESCRIPTION:TO ASCERTAIN/DESCRIBE FEATURES OF A VARIABLE EGEMPLOYEES CHARACTERISTICS Continued… TESTING HYPOTHESIS:EXPLAIN NATURE OF RELATIONSHIPS-DIFFERENCES-INTERDEPENDECES EGSALES VOLUME –PROMOTION EFFORTS CASE STUDY:CONCEPTUAL ANALYSIS OF SIMILAR SITUATIONS FOR GENERALIZATION TYPE OF INVESTIGATION CAUSAL RELATIONSHIP:ESTABLISH DEFINITE CAUSE OF A PROBLEM EGDOES SMOKING CAUSES CANCER? CORELATION:IDENTIFY IMPORTANT FACTORS ASSOCIATED WITH PROBLEM EGARE SMOKING AND CANCER RELATED? GROUP INFERENCES:RANKS-SMALLER-GREATER EGARE WOMEN MORE MOTIVATED THAN MEN AT WORK? RESEARCHER INTERFERENCE MINIMAL IF STUDY IN NATURAL SETTING EGTRAINING EFFECTIVENESS BASED ON DATA MANIPULATION,CONTROL OR SIMULATION:ANALYST CONTROLS VARIABLES EGEFFECT OF LIGHT ON WORKER OUTPUT STUDY SETTING NON CONTRIVED:NATURAL SETTING-FIELD EXPERIMENT EG ARE THE RATES OF INTEREST RELATED TO EXTENT OF DEPOSITS? CONTRIVED:INDEPENDENT VARIABLE CHANGED TO SEE EFFECT ON DP –LAB EXPERIMENT EGTO STUDY RELOF RATE OF INTEREST ON INCLINATION TO SAVE THE RATES OF INTEREST IN VARIOUS BRANCHES ARE CHANGED UNITS OF ANALYSIS INDIVIDUALS:EGSTUDY MOTIVATION OF EMPLOYEES DYADS:INTERACTION OF SUPERVISOR SUBORDINATE PAIR GROUP:EGPATTERN OF MISUSE BY VARIOUS DEPARTMENTS ORGANIZATIONS:EMOLUMENTS OF EMPLOYEES IN VARIOUS UTILITIES CULTURES:EGPROFITS MADE BY SUBSIDIARIES OF A CORPORATION IN VARIOUS COUNTRIES TIME HORIZON CROSS SECTIONAL:ONE SHOT STUDY-ONE TIME OR PERIOD EG DATA STUDY OF STOCK MARKET APRIL-JUNE LONGITUDINAL:STUDY OF INFORMATION AT MORE THAN ONE PERIOD OF TIME EGCHANGE IN BEHAVIOUR OF EMPLOYEES BEFORE AND AFTER MANAGEMENT CHANGE EXPERIMENTAL DESIGN OUTLINE LAB EXPERIMENT INTERNAL VALIDITY EXTERNAL VALIDITY WHAT AFFECTS INTERNAL VALIDITY ? THREATS TO INTERNAL VALIDITY EXPERIMENTAL DESIGNS AND INTERNAL VALIDITY 61 LAB EXPERIMENT CAUSAL STUDY OF IV-DV AND COTROL OR ISOLATE CONTAMINATING VARIABLES MANIPULATE-TREAT IV TO SEE EFFECT ON DV EGEFFECT OF LIGHT ON WORKER OUTPUT CONTROL CONTAMINATING VARIABLE BY MATCHING EGSPREADING SUBJECTS EQUALLY ACROSS CONTRL-EXPGROUPS RANDOMIZATION:RANDOM SELECTION OF SUBJECTS OF GROUPS ALSO CONTROLS CONTAMINATING VARIABLES INT AND EXT VALIDITY INTVALIDITY IS THE CONFIDENCE IN CAUSAL RELATIONSHIP IV-DV –IT IS HIGH IN LAB EXPERIMENT EXTVALIDITY IS THE EXTENT THE RESULTS FOUND IN LAB EXP ARE GENERALIZABLE FIELD EXP BEING IN NATURAL SETTING HAS MORE EXT VALIDITY THE HIGHER THE EXTERNAL VALIDITY THE LOWER THE INTERNAL VALIDITY AND VICE VERSA TO ENSURE BOTH FIRST LAB EXP THEN FIELD EXP FACTORS AFFECTING INT VALIDITY HISTORY:DURING LAB EXP OTHER FACTORS EFFECT DV EG PROMOTION BY FIRM AND ASSOCIATION MATURATION:EFFECT OVER TIME EG OLDER,TIRED,HUNGER,EXPERI TESTING:SUBJECT TREATMENT EFFECTS POST TEST BY SENSITIZING INSTRUMENTATION:CHANGE IN FRAME OF MEASUREMENT PRE AND POST TEST EGMEASURE DIFFERENT OUT PUTS FACTORS CONT… SELECTION BIAS:IN SELECTION OF MEMBERS OF EXP-CONTROL GROUPS STATISTICAL REGRESSION:SELECTION OF EXTREME SCORE SUBJECTS EGHIGHLY OR LOW MOTIVATED WORKERS MORTALITY:ATTRITION OF GROUP MEMBERS THE ABOVE EFFECTS CAN BE REDUCED BY SOPHISTICATED RESEARCH DESIGN EXAMPLE DEMOCRATIC STYLE BEST TO RAISE EMPLOYEE MORALE? 3EXP GRPS FOR PRE TEST AUTOCRATIC,DEMOCRATIC,PARTICIPATIVE AND CONTROL GRP NO TEST TWO MEMBERS MOVE TONOTHER GROUP-HISTORY EFFECT TWO MEMBERS FROM AUTO G LEFT-MORTALITY EFFECT A POST TEST WAS GIVEN TO ALL-TEST EFFECT INT VALIDITY AND EXP DESIGNS SHORTER TIME SPAN REDUCES HISTORY,MATURATION,MORTALITY EFFECTS QUASI EXP DESIGNS: 1 EXP G-PRE AND POST T>TEST EFFECT --E=02-01 NO CONTROL G 1EXP G-POST T AND 1 CONTROLGE=02-01 >MATURATION EFFECT CONT… TRUE EXP DESIGNS: 1EXP,1CONTROL GPREAND POST TEST ,CONTROL GNO TREATMENT E=[02-01]-[04-03] >MORTALITY EFFECT SOLOMON 4 GROUP DESIGN: 1 EXP ,1CONTROE GAS ABOVE 1 EXP G 1CONTROL GPOST TEST,CONTROL GNO TREATMENT >MORTALITY EFFECT SIMULATION ALTERNATIVE TO LAB/FIELD EXP COMPUTER BASED MODEL BUILDING TECHNIQUE CREATES SETTING RESEMBLING NATURAL ONE PARTIPANTS RANDOMELY EXPOSED TO REAL WORLD EXPERIENCE IN SIMULATED ENV MANIPULATION AND CONTROL BY RESEARCHER DATA COLLECTION BY OBSERVTAPING,INTERVIEW EXPENSIVE, MORTALITY EFFECT IT IS UNETHICAL TO TO FORCE SUBJECTS TO PARTICIPATE IN EXP GIVE MENIAL WORK DISALLOW WITHDRAWAL USE RESULTS AGAINST EXPOSE TO HAZARD NOT PRESERVE SECRECY NO DEBRIEFING AFTER EXP WITH HOLD BENEFITS MANAGERIAL CONSIDERATIONS IS EXPERIMENT DESIGN REQUIRED? NEED FOR CAUSAL RELATIONSHIP OR CORRELATION ? IS HIGH VALIDITY NEEDED? HOW IMPORTANT IS COST? SCALES OUTLINE OPERATIONAL DEFINITION NOMINAL SCALE ORDINAL SCALE INTERVAL SCALE RATIO SCALE 72 OPERATIONAL DEFINITION VARIABLES HAVE TO BE MEASURED IN THEORETICAL FRAMEW TO TEST HYPOTHESIS PHYSICAL MEASURES EASY-TEMPERATURE,LENGTH SUBJECTIVE FEELINGS,ATTITUDES,PERCEPTIONS DIFFICULT TO MEASURE AND ARE ABSTRACT CONCEPTS-LIKING,HAPPINESS OPERATONALLY DEFINING A CONCEPT IS TO RENDER IT MEASUREABLE ACHIEVEMENT MOTIVAT DIMENSIONS-TYPICAL CHARACTERISTICS: 1DRIVEN BY WORK-CONSTANTLY WORKING,RELUCTANT TO TAKE TIME OFF,EFFORT DESPITE SETBAC 2UNABLE TO RELAX-THINKS OF WORKAT HOME,NO HOBBIES 3IMPATIENT WITH INEFFECT-DISLIKE MISTAKES,DISLIKE WORK WITH SLOW P 4SEEKS MODERCHALLENGE-OPTS FOR CHALLENG ING JOB 5SEEKS FEEDB-ASKS FOR,IMPATIENT FOR FEEDBACK LEARNING EXAMPLE UNDERSTANDING:ANSWER Qs,GIVE EXAMPLE TO EXPLAIN RETENTION:RECALL MATERIAL SAME TIME APPLICATION:SOLVE PROBLEMS APPLYING CONCEPT,INTEGRATE WITH OTHER RELEVANT MATERIAL MOST CONCEPTS HAVE BEEN MEASURED –OPERATIONALLY DEFINED SCALES SCALE:A TOOL /MECHANISM TO DISTINGUISH /MEASURE VARIABLE NOMINAL SCALE:ALLOWS TO ASSIGN SUBJECTS TO MUTUALLY EXCLUSIVE CATEGORIES EGMALE-FEMALE,PAKISTANI-AMERICAN TO DISTINGUISH/DIFFERENTIATE ORDINAL SCALE:DISTINGUISHES AND RANKS VARIABLES EG BEST TO WORST,FIRSTBTO LAST,RANK JOB CHARACTERICS LIKE INTERACTION,SKILL USE,WHOLE TASK,SERVE OTHERS,INDEPENDENT SCALES CONT… INTERVAL SCALE:DIFFERENTIATES,RANKS,DISTANCE BET VARIABLES,GROUPS SUBJECTS IN CATEGORIES EGTHERMOMETER SCALE, PREFERENES ON A 5/7 POINT SCALE STRONGDISAGREE,DISAGREE,NEITHER AGREE NOR DISAGREE ETC RATIO SCALE:DIFFERENCE ,ORDER,DISTANCE AND UNIQUE ORIGIN EG WEIGHING SCALE,USE ARITH OR GEOMETRIC MEAN,STANDARD DEVIATION,VARIANCE,,TESTS OF SIGNIFICANCE T,F SCALES CONT… RATIO SCALES USED WHEN EXACT NUMBERS ARE CALLED FOR EG HOW MANY ORDERS DO YOU OPERATE? INTERVAL SCALE USED FORB RESPOSES TO VARIOUS ITEMS ON 5/7 POINTS USE OF STATS MEASURES AS RATIO SCALE,AMEAN,STANDDEVIATION,VARIANCE,T,F ORDINAL SCALE:FOR PREFERENCE IN USE,STATS MEASURES ARE MEDIAN,RANGE,RANK ORDER CORRELATIONS NOMINAL SCALE:USED FOR PERSONAL DATA,STATS MEASURES,MODE,X2 SCALING OUTLINE SCALING RATING SCALES RANKING SCALES GOODNESS OF MEASURES RELIABILITY VALIDITY 79 SCALING ASSIGN NUMBERS OR SYMBOLS TO ELICIT ATTITUDINAL RESPONSES TOWARDS OBJECTS,EVENTS ,PERSONS ETC NOT TO BE CONFUSED WITH 4 SCALES RATING SCALES:DICHOTOMY,CATEGORY,LICKERT,NUMERICAL,SEMANTIC DIFFERENTIAL, ITEMISED,FIXED CONSTANT SUM,STAPEL,GRAPHICAL RATING RANKING SCALES:PAIRED COMPARISON,FORCED CHOICE RATING SCALES DICHOTOMY S:YES NO RESPONSE TO A QUESTIONEGDO YOU LIKE TO WORK? CATEGORY S:ELICIT ONE RESPONSE FROM SEVERAL EGDO YOU LIVE IN A/B/C/D ? LIKERT S:EG5POINT/STRONGLY AGREE…STRONGLY DISAGREE NUMERICAL S:5 TO 7 POINTS BIPOLAR ADJECTIVE AT EACH ENDEGEXTREMELY PLEASED…EXTREMELY DISPLEASED RATING SCALES CON… SEMANTIC DIFFERENTIAL S:BIPOLAR ATTRIBUTES AT ENDS EGBEAUTIFUL-UGLY ITEMISED RATING S:5 TO 7 POINTS WITH ANCHOR EGVERY UNLIKEY…VERY LIKELY RATING SCALES CONT FIXED CONSTANT SUM S:ASSIGN NUMER TO EACH ITEM FROM POINTS EG COLOUR,SHAPE,SIZE STAPEL S:DIRECTION AND INTENSITY OF ATTITUDE EG –3 TO +3 GRAPHIC RATING S:PLACE MARK ON GRAPHIC SCALE CONSENSUS S:A PANEL OF JUDGES SELECTS ITEM WHICH MEASURES CONCEPT RANKING SCALES CONT PAIRED COMPARISON S:RESPONDENTS TO SELECT TWO OBJECTS AT A TIME”RESPONDENTS FATIGUE IF NUMBER LARGE” FORCED CHOICE S:RANK OBJECTS RELATIVE TO EACH OTHER TO ASSESS ATTITUDES TOWARDS OBJECTS EGFINANCIAL ENVITONMENT MOST USEFUL LEAST USEFUL GOODNESS OF MEASURES VALIDITY: RIGHT MEASURE FOR THE CONCEPT[IN EXP DESIGN EXACT CAUSE EFFECT REL/GENERALIZ] RELIABILITY:ACCURACY TO MEASURE THE CONCEPT TO BE STABLE AND CONSISTANT STABILITY:MEASURES THE CONCEPT EVEN IF CHANGE OCCURS CONSISTANCY:ITEMS IN THE INSTRUMENT SOLICT SIMILAR IMPACT ON RESPONDENTS ITEMS ANALYSIS TO SEE IF ITEMS BELONG IN THE INSTRUMENT THE MEANS BETWEEN HIGH SCORE S AND LOW SCORES ITEMS GROUP ARE TESTED BY t VALUES TO FIND HIHLY DISCRIMINATING ITEMS TO BE INCLUDED IN THE INSTRUMENT THE VALIDITY OF MEASURES IS ESTIMATED RELIABILITY/STABILITY TEST RETEST RELIABILITY:REPEAT INSTRUMENT WITH SAME GROUP AND ANOTHER TIMECORRELATION PARALLEL FORM RELIABILITY:RESPONSES OF TWO COMPARABLE SETS OF MEASURES FOR SAME CONCEPTHIGHLY CORRELATED RELIABILITY/CONSISTAN INTERNAL CONSISTANCY:ITEMS AS A SET MEASURE THE SAME CONSTRUCT RELIABLY CONSISTANCY TEST:RESPONDENTS ANSWERS TO ALL ITEMS ARE CORRELATED CRONBACH A COEFF SPLIT HALF RELIABILITY:CORRELATION OF ITEMS OF BOTH HALVES OF INSTRUMENT AFTER SPLIT VALIDITY INSTRUMENT MEASURES THE INTENDED CONCEPT CONTENT V:ENSURES THAT MEASURES INCLUDE REPRESENTATIVE,ADEQUATE SET OF ITEMSFOR CONCEPT APPROVED BY PANEL OF JUDGES FACE VALIDITY:DO THE ITEMS MEASURE THE CONCEPT ON THE FACE OF IT[LOOK LIKE] VALIDITY CON… CRITERION V:THE MEASURE DIFFERENTIATES INDIVIDUALS ON A CRITERIONCORRELATION PREDICTIVE V:DIFFERENTIATES A FUTURE RELATED CRITERIONEGAPTITUDE TEST FOR JOB/SUBJECT CONCURRENT V:DISCRIMINATES INDIVIDUALS KNOWN TO BE DIFFERENTEGSCORE FOR WORK ETHICS FOR A HARD WORKER VALIDITY CONT CONSTRUCT V:DOES THE MEASURE FIT THE CONCEPT AS THEORIZED BY FACTOR ANALYSIS? CONVERGENT V:DO 2 INSTRUMENTS MEASURING THE CONCEPT CORRELATE HIGHLY? DISCRIMINATING V:DOES THE MEASURE HAVE A LOW CORRELATION WITH THE VARIABLE THAT IS SUPPOSED TO BE UNRELATED TO THE VARIABLE? EXAMPLES TESTED INSTRUMENTS JOB ENRICHMENT,PARTICIPATIVE MANAGEMENT,ROLE CONFLICT,CAREER SALIEN,LEAST PREFFERED COWORKER,PRODUCTIVITY AUDIT,ADS,SELLING,MARKETING AND QUALITY SERVICE RESPONSES,RELIABILITY RESPOSIVENESS,TANGIBLE PERSONAL ATTITUDES ETC DATA COLLECTMETHODS OUTLINE INTERVIEW METHODS QUESTIONNAIRE METHODS OBSERVATION SURVEYS SETTING SOURCES 93 INTERVIEW METHODS UNSTRUCTURED:PRELIMINARY,TO IDENTIFY CRITICAL FACTORS SEQUENCE OF Qs NOT PLANNED FROM BROAD TO SPECIFIC Qs STRUCTURED:TO ELICIT INDEPTH,DIRECT INFORMATION TYPE OF INFO NEEDED IS KNOWN PREDTERMINED Qs LISTED /POSED VISUAL AIDS USED BIAS FREE INTERVIEW INTERVIEWER RAPPORT WITH RESPONDENT NOT TO INFLUENCE RESP BY BODY LANGUAGE RECORD RESPONSES ACCURATELY CORRECT ANALYSIS,INTERPRET TACTFUL QUESTIONING REPEAT AND CLARIFY Qs CONFIDENCE BY CREDIBILITY/ABILITY ALLEY FEARS AND SUSPICION BIAS FREE CONT INTERVIEWEE TO UNDERSTAND Qs EXPRESSES TRUE OPINION AVOIDS PERSONAL LIKING/DISLIK AVOID PRESENCE OF NON PARTICIPANTS WHO RESTRICT RAPPORT FOR OPENNESS ENSURE AVAILABILITY FLEXIBILITY BY APPOINTMENT QUESTIONING TECHNIQUE FUNNELING:START WITH OPEN ENDED Qs,FROM BROAD TO SPECIFQs TO IDENTIFY KEY ISSUES UNBIASED:ASK Qs IN A WAY OF LEAST BIAS IN RESPONSE CLARIFY ISSUES:REPHRASE IMPORTANT INFO OF RESPONDENT HELP RESPUNDERSISSUES:Qs IN A SIMPLE WAY TAKE NOTES DIRECTLY /THEREAFTER INTERVMETHODS +/- FACE TO FACE:ADAPT THE Qs,CLARIFY DOUBTS,OBSERVE NON VERBAL CUES,MAY BE EXPENSIVE,NEED TRAINED STAFF TELEPHONIC:REACH RESPONDENT FAST,DISCOMFORT OF FACING AVOIDED,ABRUPT TERMINATION COMPUTER ASSISTED:INDEXES RESPONSES,FILTERS OUT OF RANGE RESPOSES TO ENHANCE ACCURACY,SELECTS RESPONDENTS AND CALLS FROM FILES,RECORDS RESPONSES QUESTIONNAIRE DESIGN SET OF Qs FOR RESPONSE PERSONALLYADMINISTERED: QUICK,LESS COST LOCALLY,DOUBTS CLARIFIED,NEED LESS TRAINED STAFF, MAIL QUESTIONNAIR:FOR WIDE AREA COVERAGE,LOW RESPONSE[30 %] , PROVIDE MONETARY AND OTHER INCENTIVES TO RESPOND,FACILITATE BY ENCLOSING SELF ADDRESSED STAMPED ENVELOPE ,KEEP Qs SIMPLE TO ANSWER QDESIGN WORDING CONTENT/PURPOSE:TAP DIMENSIONS AND ELEMENTS OF CONCEPT BY BEHAVIOURAL Qs LANGUAGE/WORDING:ACCORDING TO THE LEVEL OF UNDERSTANDING OF RESPONDENTS OPEN ENDEDQs:RESPCHOOSES WAY TO DECIDE CLOSED Qs:CHOICE FROM GIVEN ALTERNATIVES POSITIVAND NEGATIVWORDED Qs:NOT TO BE USED FOR SAME CONCEPT TOGATHER,USE TO AVOID MECHANRESP BIAS IN Qs DOUBLE BARRELED:WHERE TWO PARTS LEND TO DIFFERENT ANSWERSEGGOOD MARKET SELLS WELL AMBIGUOUS:RESPONDEND MAY NOT BE SURE OF MEANING RECALL:RECALL PAST EVENT HAZY LEADING:TO PHRASE A QTO ELICIT RESPONSE OF RESEARCHER LIKING EGEMPLOYEE TO GET RAISE IN INFLTIONARY SITUATION BIAS IN Qs CONT LOADED:MAY SOLICIT EMOTIONALLY CHARGED RESPONSE EGWILL IT BE VINDICTIVE IF UNION DECIDES TO STRIKE SOCIALLY UNDESIRABLE:EGDO YOU THINK OLDER PEOPLE BE LAID OFF? LENGHTY:NOT OVER 2O WORDS SEQUENCE:FROM GENERAL TO SPECIFIC CROSS CULTURAL RESEARCH CORRECT ASSESSMENT OF ATTITUDES BY MULTINATIONALS TRANSLATION OF INSTRUMENT ITEMS:BACK TRANSLATION TO ESTABLISH IDIOMATIC EQUIVALENCES PROCEDURES:UNIFORM PROCEDURE OF DATA COLLATION ALSO WITHIN A TIME FRAME PRINCIPLES OF MEASUREMENT WORDING TO MINIMISE BIAS MEASURES TO BE RELIABLE AND VALID SCALES AND SCALING APPROPRIATE ESTABLISH GOODNESS OF DATA EASY CODING AND CATEGORIZATION OF DATA QUESTIONNAIRE GETUP LOGICALLY ORGANIZED SECTIONS NEATLY PLACED INSTRUCTIONS FOR RESPONDENTS MINIMUM AMOUNT OF EFFORT BY RESPONDENT PRE TESTING OF Qs –NO AMBIGUITY EXAMPLES PERSONAL DATA,INCOME,ENDING ETC ELECTRONIC QDESIGN SURVEY CHECKS LOGICAL/SYMMETRICAL ERROR DATA EDITING PROGRAMMES COMPUTING AND MEASURES MULTIPLE REGRESSION ON LINE QSURVEY,MAIL DATA DISC TO RESPONDENTS OBSERVATION SURVEY OBSERVE BEHAVIOUR,ACTIVITIES,BODY LANGUAGE,PROCESSES,CHILDREN UNSTRUCTURED:NO SPESIFIC IDEA OF ASPECT TO BE STUDIED-NATURAL STRUCTURED:PREDTERMINED EVENTS OBSERVED,RECORDED AS NEEDED LESS RESPBIAS,EASY TO OBSERVE ENVIRONMENT EFFECTS,CHILDREN NEED PRESENCE,SLOW,EXPENSIVE,DOES NOT OBSERVE COGNITIVE EFFECT,NEED TO TRAIN OBSERVERS BEHAVIOURAL OBSERV NON VERBAL:BODY MOVEMENT , GLANCES,FACE EXPRESSION LINGUISTIC:SOUNDS EXTRA LINGUISTIC:VOICE,PITCH;RATE OF SPEAKING SPATIAL :HOW ONE RELATES PHYSICALLY TO OTHERS NON BEHAVIOURAL:RECORD ANALYSIS,PHYSICAL PROCESSES,CONDITIONS BIASES IN OBSERVATION ERRORS IN RECORDING , MEMORY LAPSES,BOREDOM,FATIGUES RESPONDENT REACTIONS LACK OF TRAINING:WHAT TO OBSERVE[EVENT,TARGET],HOW AND WHEN USE OF CAMERAS,RECORDING ETC CONCEALMENT OF OBSERVER ,EQUIPMENT AND PURPOSE UNOBTRUSIVE OBSERVATION,AVOID HALLO EFFECT,OBSERVER DRIFT FURTHER METHODS/SOURCES WORD ASSOCIATION:EGWORK IS – THEMATIC TEST:STORY AROUND A PICTURE INKBLOT TEST:INTERPRETATION MULTI METHODS USE FOCUS GROUP:GROUP DISCUSSION UNDER MODERATOR-RESPONSES PANEL:FOCUS GROUP TO STUDY INTERVENTION EFFECT OVER TIME EG EFFECT OF ADS TRACE MEASURES:EG CANS IN TRASH FOR BRAND USE SAMPLING OUTLINE DEFINITION WHY SAMPLING? NORMAL DISTRIBUTION SAMPLING DESIGN PROBABILITY SAMPLING NON PROBABSAMPLING PRECISION AND CONFIDENCE CALCULTION OF SAMPLE SIZE 111 DEFINITIONS POPULATION:GROUP,EVENTS TO BE INVESTIGATED ELEMENT:A MEMBER OF POPULATION POPULATION FRAME:LIST OF ELEMENTS EGTELDIRECTORY SAMPLE:RESEARCHER DRAWS SUBSETOF POPULATION TO DRAW CONCLUSIONS FROM IT FOR WHOLE POPULATION SUBJECT:AN ELEMENT OF A SAMPLE DEFINITIONS CON… SAMPLING :PROCESS OF DRAWING A SAMPLE FROM A POPULATION TO UNDERSTAND,ANALYSE ITS PROPERTIES TO GENERALIZE FOR THE WHOLE POPULATION SAMPLING R EDUCES EFFORT AND COST IF POPULATION IS LARGE REPRESENTATIVE S:IN A REPRESENTATIVE SAMPLE ITS CHARACTERISTICS ARE THE SAME AS THOSE OF THE POPULATION SAMPLING DESIGN EXPLORATORY DESIGN: REPRESENTATIVE SAMPLE IS NOT NEEDED-RESULTS NOT GENERALIZED, FOR CLUES TO ISSUES FOR DESIGN OF SAMPLE ONE NEEDS TARGET POPULATION,PARAMETER TO STUDY,SAMPLING FRAME,SAMPLE SIZE,TIME AND RESOURCES REQUIRED PROBABILITY SAMPLING ELEMENTS HAVE SAME CHANCE OF BEING SELECTED,USED WHEN REPRESENTATIVE SAMPLE IS IMPORTANT UNRESTRICTED RANDOM SAMPL:EACH ELEMENT HAS KNOWN AND EQUAL CHANCE OF BEING SELECTED LEAST BIAS AND MOST GENERALIZABLE EXPENSIVE AND CUMBERSOME RESTRICTED PROBABS SYSTEMATIC:DRAW Nth ITEM RANDOMLY ,EFFICIENT AND USED FOR ATTITUDE SURVEYS ETC STRATIFIED RANDOM:HOMOGENITY WITHIN GROUP,HETROGENITY AMONG GROUPS,SELECT SUBJECTS AT RANDOM EACH SUBGROUP IF SUBGROUPS WITHIN POPULATION HAVE DIFFERENT PARAMETERS PROBABILITY S CONT… PROPRTIONATE STRATIFIED RANDOM:PROPSELECTION FROM EACH GROUP EG JOB LEVELS DISPROPORTIONATE STRATRANDOM:IF STRATA TOO SMALL OR TOO LARGE AND MORE PROBSUSPECTED WITHIN SUB GROUPS CLUSTER:GROUPS HETROGENOUS WITHIN AND HOMOGENOUS AMONG THEM ,LESS EFFICIENT MULTISTAGE CLUSTER:CLUSTER IN EACH AREA AND SUB CLUSTERS AND RANDOM SELECTION PROBASAMPLING CON AREA SAMPLING:POPULATION WITH IN EACH GEOGRAPHICAL CLUSTER,LESS COSTLY DOUBLE SAMPLING:1st SAMPLE FOR PRELEMINARY INFORMATION OF INTEREST,2nd TIME PREVIOUS SAMPLE USED FOR FURTHER DETAIL NON PROBAB SAMPLING ELEMETS PROBABILITY OF SELECTION NOT KNOWN,FOR QUICK PRELFINDINGS CONVENIENCE :EASILY AVAILABLE SAMPLE ELEMENTS TAKEN PURPOSIVE:CONFINED TO SPECIFIC GROUP WHO CAN PROVIDE DESIRED INFORMATION JUDGEMENT:BEST PEOPLE TO PROVIDE INFO QUOTA:ENSURE CERTAIN PEOPLE ARE REPRESENTED IN A STUDY BY QUOTA PRECIS AND CONFIDENCE PRECISION:HOW CLOSE ESTIMATE IS TO TRUE POPULATION STATS STANDARD SAMPLING ERROROF MEANS=Sx=S/SQUARE ROOT[n-1] CONFIDENCE:LEVEL OF CERTAINTY TO HAVE THAT PRECISION EG 95% FOR k=196 Sx=10/(49^1/2)=143 U=X+kSx=105+-196*143=1o5+-235 BY LAERGER n MULTIPLY BY [N-n]/N-1 LARGER THE SAMPLE SIZE HIGHER THE PRECISION OR SMALLER THE SAMPLING ERRORTHE NARROWER PRECISION RANGE THE LOWER THE CONFIDENCE LEVEL PRECISION AND CONFID… NO SAMPLE HAS EXACTLY SAME CHARACTERISTICS AS POPULATION PROBABILITY SAMPLING COMES CLOSER TO POPULATION STATISTICS X,S,S^2 MEAN,STANDARD DEV, VARIANCE OF SAMPLE U,SIGMA,SIGMA^2 OF POPULATION n SAMPLE SIZE,N POPULATION SAMPLE SIZE EFFECTED BY VARIABILITY OF POPULATION PRECISION/ACCURACY NEEDED COST /BENEFIT OF INVESTIGATION MOST RESEARCH SAMPLES SIZE>30AND OUTLINE D ATA ANALYSIS/INTERPRET DATA READY FOR ANALYSIS: EDIT,CODING,CATEGORIZATION,DATA ENTRY DATA ANALYSIS: OBJECTIVES OF DATA ANALYSIS:TEST GOODNESS,HYPOTHESIS TEST, ANALYSIS AND INTERPRETATION:DESCRIPTIVE STATISTICS,INFERENTIAL STATISTICS 123 DATA READY… EDIT:CHECK INCOMPLETENESS AND INCONSISTANCY,LOGICALLY RECTIFY DATA BLANK RESPONSES:LACK OF UNDERSTANDING,UNWILLINGNESS TO ANSWER,INDIFFERENCE TAKE MID POINT OF SCALE IGNORE BLANK RESPONSES ASSIGN MEAN VALUE OF RESPONSES ASSIGN RANDOM NUMBER IN SCALE DATA CONT… CODING:ASSIGN UNIQUE NUMBERTO EACH VARIABLE AND ITEM EG AGE,EDUCATION CHECK 10% FOR ACCURACY CATEGORIZATION:VARIABLES SUCH THAT SEVERAL ITEMS MEASURING SAME CONCEPT ARE GROUPED TOGETGEREG VARIOUS CATEGORIES OF AGE ENTRY:BY SCANNER DIRECTLY OR MANUALLY USING STATS PACKAGE DATA EDITOR DATA ANALYSIS USE STATS PACKAGE SS-9 FOR WINDOWS FOR TESTS,EXCEL FOR DISPLAY RESULTS FEEL FOR DATA:MEASURES OF CENTRAL TENDENCY,DISPERSION,DISTRIBUTION, INTERRELATIONS OF VARIABLES TO DETECT INCORRECTNESS ,BIAS,OUT OF RANGE DATA GOODNESS OF DATA:RELIABILITY ANALYSIS CRONBACH ALPHA COEFF CLOSER TO 1 THE HIGHER INTERNAL CONSISTANCY RELIABILITY OF ITEMS OF MEASURES DATA ANALYSIS CONT… SPLIT HALF RELIABILITY COEFFFOR CORRELATION OF SPLIT ITEMS STABILITY OF MEASURES:PARALLEL FORM RELIABILITY,TEST RETEST RELIABILITY TEST FOR CORRELATION OF MEASURES VALIDITY:FACTORIAL VALIDITY BY MULTIVARIATE TECHNIQUES TO CONFIRM CORRECTNESS OF DIMENSIONS OF CONCEPTS CRITERION VALIDITY:TEST MEASURES TO DIFFERENTIATE INDIVIDUALS KNOWN TO BE DIFFERENT DATA ANALYSIS CONT… CONVERGENT V:TWO SOURCES RESPONDING TO SAME MEASURES HIGHLY CORRELATED DISCRIMINATORY V:TWO DISTINCTLY DIFFERENT CONCEPTS ARE NOT CORRELATED IF VALIDATED MEASURES ARE USED NO NEED FOR VALIDITY TEST ONLY TEST RELIABILITY HOYPOTHESIS TESTING EXAMPLE EXAMINE CRONBACH ALPHA FOR MEASURES FREQUENCY DISTRIBUTION OF THE VARIABLES DESCRIBE MEAN,STANDARD DEVIATION OF MEASURES PEARSON’S CORRELCOEFFICIENT RESULTS OF HYPOTHESES EXAMPLE CONT… RELIABILITY:CRONBACH ALPHA 082, MEASURES INTERNALLY CONSISTANT, CORRELATED FREQUENCY DISTRIBUTION OF PERSONAL DATA EGDEPT WISE % RESPONDENTS DESCRIPTIVE STATS MAX,MIN,MEAN,STD DEV,VARIANCE OF VARIABLES EG JOB SAT AVERAGE,ITL LOW, INFERENTIAL STATS:PEARSON CORRELATION,BELOW 059 MEASURES VALIDITY-IF>0,75 VARIABLES NOT DISTINCT EXAMPLE CONT… EG ITL IS NEGATIVELY CORREL TO JOB SAT,EQUITY,JOB ENRICH HYPOTHESIS TEST 1:NO DIFFERENCE BETMEN AND WOMEN IN PERCEIVED EQUITY Ho:Uw=Um t-Test TCAL=075 EXAMPLE CON… FCAL=3327FCRIT=3 H REJECTED,SIG=004 D=3-1=2,DF=171-12-4=159 HYPOTHESIS 3:NO DIFFERENCE IN ITL OF EMPLOYEES AT 5 JOB LEVELS H0:U1=U2=U3=U4=U5ANOVA TEST- fcal125 EXAMPLE CONT HYPOTHESIS 5:4 VARIABLES DO NOT SIGNIFICANTLY EXPLAIN VARIANCE IN ITL-MULTIPLE CORREL ANALYSIS R CORRELOF VARIABLES 058,R^2=03 VARIANCE SIG001,DF4=5-1,DF156=160-4 F=24 FCAL=167>FCRIT HO REJECTED HELP IN CHOICE OF TEST THE TYPE OF TEST DEPENDS ON HYPOTHESIS,SCALE,COST AND BENEFIT EXPERT SYSTEMS HELP CHOOSE APPROPRIATE PROCEDURE AND TESTS EGSTAT NAVIGATOR, THEY ALSO HELP IN RESEARCH DESIGN RESEARCH PROPOSAL OUTLINE PURPOSE SPONSOR USES RESEARCH BENEFITS TYPES OF PRPOSALS STRUCTURING PROPOSALS PROBLEM STATEMENT RESEARCH OBJECTIVES LITERATURE REVIEW BENEFITS OF STYDY RESEARCH DESIGN D ATA ANALYSIS 135 PROPOSAL OUTLINE NATURE/FORM OF RESULTS QUALIFICATION OF RESEARCHER BUDGET SCHEDULE FACILITIES/SPECIAL RESOURCES PROJECT MANAGEMENT BIBLIOGRAPHY APPENDICES MEASUREMENT INSTRUMENT EVALUATING THE RESEARCH PROPOSAL PURPOSE OF PROPOSAL THE PROPOSAL INDICATES: SIGNIFICANCE OF RESEARCH PROBLEM RELATED RESEARCH OF OTHERS DATA NEEDED,METHODS OF COLLECT,ANALYSIS,INTERPRET PURPOSE,DESIGN AND FITNESS TO RESAERCH BASIS TO EVALUATE RESULTS WORKPLAN ,TIME AND BUDGET ESTIMATES TYPES OF PROPOSALS-COMPLEXITY STUDENT TERM PAPER,THESIS,DOCTORAL THESIS INTERNAL EXPLORATION,SMALL SCALE OR LARGE SCALE STUDY EXTERNAL EXPLORATORY,SMALL TO LARGE SCALE CONTRACT GOVT SPONSORED STUDY NEEDS ALL MODULES DOCTORAL THESIS DOES NOT NEED SUMMARY,RESQUALIFICATIONS, BUDGET,PROJECT MANAGEMENT, STRUCTURE OF PROPOSAL EXECUTIVE SUMMARY:INFO ABSTRACT FOR EXECUTIVE EVALUATION STATING PROBLEM,OBJECTIVES,BENEFITS OF RESAERCH APPROACH PROBLEM STATEMENT:STATE PROBLEM, BACKGROUND,CONSEQUENCES, IMPORTANCE,BENEFITS OF STUDY RESEARCH OBJECTIVES:PURPOSE OF RESAERCH QUESTION/HYPOTHESIS SPONSOR SPECIFIC CONCRETE AND ACHIEVABLE GOALS LISTED IN ORDER OF IMPORTANCE STRUCTURE CON… LITREVIEW:HISTORICALLY SIGNIFICANT,RECENT,RELATED RESEARCH,DATA,REPORTS AS BASIS OF PROPOSED STUDY,DISCUSS IMPORTANCE/BENEFITS OF STUDY:A FEW PARAS HOW STUDY WOULD BENEFIT THE SPONSOR RESEARCH DESIGN:TECHNICAL DETAILS OF PHASES OF THE PROJECT,SAMPLE SELECTION,DATA COLLMETHODS,INSTRUMENTS, ANALYSIS PROCEDURE STRUCTURE CON… DATA ANALYSIS:FOR COMPLEX RESEARCH STUDIES -METHODS/TESTS NATURE/FORM RESULTS:TO SEE IF OBJECTIVE OF STUDY,CONTRACTUAL STATEMENT ACHIEVED, CONCLUSIONS, ACTION PLANS,PLANS,MODELS RESEARCHER QUALIFICATIONS: ACACDEMIC,RELEVANT EXPER ENTIRE RESUME IF SPCIFICALLY ASKED BUDGET:1-2 PAGES SUB HEADINGS NEED SCHEDULE:MAJOR PHASES,DURATION, MILESTONES,COMPLETION-PERT PLAN STRUCTURE CON… PROJECT MANAGEMENT:TEAM ORG RESPONSIBILITIES,CONTROL PROCEDURES,REPORTING ,COMPETENCY BIBLIOGRAPHY:STANDARD FORMAT RESEARCH AND QUOTATIONS APPENDICES:GLOSSARY,SAMPLE OF MEASURING INSTRUMENT EVALUATION:CRITERIA ESTABLISHED BEFORE PROPOSAL RECEIVED,NEATLY PRESENTED,LOGICALLY ORGANIZED,GUIDELINES FOR BUDGET,SCHEDULE,EASILY UNDERSTOOD PROBLEM STATEMENT STATISTICS –OUT LINE DESCRIPTIVE STATS FREQUENCY DISTRIBUTION MEASURES OF CENTRAL TENDENCY MEASURES OF DISPERSION INFERENTIAL STATS CORRELATION ANALYSIS REGRESSION ANALYSIS TESTS OF RELATIONSHIP BETWEEN VARIABLES 143 TEST OF SIGNIFICANT MEAN DIFFERENCES BETWEEN GROUPS DESCRIPTIVE STATS CHARACTERISTICS OF CENTRAL TENDENCY,DISPERSION,SHAPE DESCRIBE DISTRIBUTIONS DISTRIBUTION:THE VALUES ALONGWITH FREQUENCY OF OCCURRENCE STANDARD NORMAL DISTRIBUTION:MOST PHENOMENA TEND TO CLUSTER AROUND MEAN-INVERTED BELL SHAPED CURVE MEAN:ARITHMATIC AVERAGE-FOR INTERVAL AND RATIO DATA MEDIAN:MIDPOINT OF A DISTRIBUTION –ORDINAL DATA DESCRIPTIVE CONT… MODE:MOST FREQUENTLY OCCURRING VALUE-NOMINAL DATA VARIANCE:AVERAGE OF SQUARED DEVIATION SCORES FROM DISTRIBUTION’S MEAN STANDARD DEVIATION:SQUARE ROOT OF VARIANCE RANGE:DIFFERENCE BETLARGEST AND SMALLEST SCORE IN A DISTRIBUTION-ORDINAL DATA INTER QUARTILE RANGE DIFF BETWFIRST AND THIRD QUARTILE OF DITRIBUTION-ORDINAL DATA STATISTICAL TESTS PROCEDURE: STATE NULL HYPOTHESIS CHOOSE THE STATS TEST:DEPENDS ON EFFICIENCY,POPULATION,SAMPLE DRAW,SCALE SELECT LEVEL OF SIGNIFICANCE:0001-01-WITHIN RANGE COMPUTE THE CALCULATED DIFFERENCE VALUE:APPROPRIATE SIGNIFICANCE TEST EG t TEST,CHI SQUARE TEST ETC STATISTICAL CON… OBTAIN THE CRITICAL VALUE FROM TABLES FOR REGION OF REJECTION/ACCEPTANCE OF NULL HYPOTHESIS MAKE THE DECISION:FOR MOST TESTS IF CALCULATED VALUE IS LARGER THAN CRITICAL VALUE WE REJECT NULL HYPOTHESIS STATISTTESTS CONT STATTEST SIGNIFICANCE OF CHANGE/DIFFERENCE IF DIFF DOES NOT REPRESENT SAMPLING FLUCTUATION ONLY NON PARAMETRIC TESTS FOR NOMINAL AND ORDINAL DATA-CHI SQUARE PARAMETRIC TESTS FOR INTERVAL/RATIO SCALES AND RELIABLE ,INDEPENDENT OBSERVATIONS, POPULATION NORMAL DISTRIBUTION, EQUAL VARIANCES OF POPULATION INFERENTIAL STATS TO KNOW FROM ANALYSIS THE RELATIONSHIP BETWVARIABLES, DIFFERENCE AMONG VARIABLES FROM SUBGROUPS,HOW SEVERAL IVs MIGHT EXPLAIN THE VARIANCE IN A DV MEASURING DEGREE OF RELATIOSHIP BETWEEN 2 VARIABLES IS CORRELATION ANALYSIS USING RELATIONSHIP BETWEEN A KNOWN VARIABLE AND AN UNKNOWN VARIABLE TO ESTIMATE THE UNKNOWN IS REGRESSION ANALYSIS PEARSON PRODCORRELATION SHOWS DIRECTION,STRENGHT,SIGNIFICANCE OF REL OF 2 VARIABLES +1 TO –1,SIGNIFICANCE 0001-01 r= SUM [X-x][Y-y]/[N-1]SxSy FOR SMALL SAMPLES SAMPLING ERROR BELOW r=05 T-TEST OF SIGNIFICANCE WHEATHER r IS CHANCE DEVIATION FROM A POPULATION FOR INDEPENDSAMPLE,NORMAL DISTRIBUTION,BIVARIATE Ho:P=0 NO CORRELATION t=r/square root[1-r^2]/n-2=093/1-086/8^1/2=703 CRITICAL VALUE df 2 and p=0005 CALCULATED VALUE>2*CRITVALUE,NULL HYPOTHESIS REJECTED CHI SQUARE TEST USED TO FIND RELATIONSHIP BETWEEN NOMINAL VARIABLES BY SMALL SAMPLE SIZE CHI SQUARE=SUM[O-E]^2/E O=OBSERVED E=ESTIMATED VALUE EG 4 RETIREPLANS [P]INDEPENDENT OF 3CLASSES OF EMPLOYEES df=[4-1][3-1]=6 CALCULATED VALUE2808>CRITICAL VALUE 12593 NULL HYPOTHESIS REJECTED LINEAR REGRESSION PHI T CHI SQUARE BASED BIVARIATE T WHEN OBSERVED VALUES OF X TAKEN TO ESTIMATE CORRESPON Y VALUES IT IS SIMPLE REGRESSION BY MORE THAN ONE VARIABLES IT WOULD BE MULTIPLE REGRESSION EG CORRELATION OF JOB ACCIDENT AND SMOKING PHI=SQUARE ROOT CHI SQUARE/N=SQUARE ROOT 611257/60=0305 MODERATE RELATIONSHIP BETWEEN VARIABLES ANALYSIS OF VARIANCE WHEN 2 OR MORE POPULATION MEANS HYPOTHESIS IS TESTED FOR ANOVA ,WHEATHER TWO DIFFERENT SAMPLE MEANS COME FROM THE SAME POPULATION F DISTRIBUTION VARIES WITH df ACCOUNT FOR ENUMERATOR AND DENOMINATOR EG RECOVERY DAYS NOT INFLUENCED BY 3 TYPES TREATMENTS IN 4 HOSPITALS:COMPVALTREATM O99 MULTIVARIATE ANALYSIS FOR COMPLETE BUSINESS PROBLEMS MULTIPLE IV AND DV EGBUYER PREFERENCES/PRODUCT OPTIONS USE MANOVA,MULTIPLE REGRESSOR DISCRIMINATORY TECHNIQUES FOR INTERDEPENDENT VARIABLES USE :FACTOR ANALYSIS,CLUSTER ANALYSIS,MULTIDIMENSION SCALING FOR METRIC DATA USE SCALES :INTERVAL AND RATIO FOR NONMETRIC DATA USE NOMINAL AND ORDINAL SCALES MULTPLE REGRESSION FOR DESCRIPTION,HYPOTHESIS TEST AND FOR ESTIMATING Y=Bo+B1X1+B2X2+…Bn+Xn WHERE Bs ARE REGRESSION COEFFICIENTS EGHAS ANN FAMILY INCOME X1,FAMILY SIZE X2,FAMILY LOCATION X3INFLUENCE ON ANN FAMILY FOOD SPENDING Y IF B1=06 B2=02 X1 HAS 3TIMES INFLUENCE ON Y THAN X2 DISCRIMANT ANALYSIS FIND PREDICTORS FOR BEST ANALYSIS OF SUBSETS JOINS NOMINAL DV WITH I OR MORE INTERRVAL/RATIO SCALED VARIABLES Di=do+d1x1+d2x2+…dpxp egADMINISTRATOR SUCCESSFUL OR NOT[Di],ability to work with others[x1],motivation for administration[x2],professional skill[x3] Di=o+06 x1+045x2+03x3 x1 is more important than x2,x3 MANOVA USED TO DIFFERENTIATE RELATIONOF 2 OR MORE DV AND FACTORS INTERDEPENDENT TECH FACTOR ANALYSIS:REDUCE MANY FACTORS TO MANAGEABLE WITH OVERLAPPING CHARACTERISTICS REPLACE DEPENDENT RELATIONSHIPS TO MATRIX OF INTERRELATIONSHIPS BY PRINCIPAL COMPONENT ANALYSIS TRANSFORM SET OF VARIABLES TO NEW SET VARIABLES,NOT CORRELATED PRINCIPAL COMPONENT SECOND COMPONENT AND LINEAR COMBINATION TILL 100% VARIANCE IS ACCOUNTED FOR







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