Inquiry and Methodology in Development
Inquiry and Methodology in Development CAS 301
Cal State Fullerton
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Sharon Seidman PhD CAS 301 Developmental Inquiry 85 Methodology Research Basics What are the pieces and how do they fit together Em Vygoteky Co nitive Develo merit 2 Sources of Knowledge 3 Bottom up figured out 38 T op down taught Bottom Up Induction 38 Based on 88 Salient experience 38 Anecdotea 38 Subject to 38 Human error 88 Illusory correlations Sharon Seidman PhD CAS 301 Developmental Inquiry 86 Methodology Top Down Authority 3 Accepted if 3 Believable source 3 Relevant information 3 Fits with experience 3 No evidence Empirical Research 3 Knowledge based an observation 3 Requires information that is 3 Accurate 3 Diverse 3 Confirmed by 3 Multiple assessmentsinvestigations 3 Evaluation of alternatives 3 Peer review Goals of Research 8 Description 8 Prediction 8 Causation Sharon Seidman PhD CAS 301 Developmental Inquiry 86 Methodology Goals of Research 3 Description what ghee cIHs moiemth look Ike Prediction when WI cit7d wak Cau5ati0n how can we W ZJVG 4 h wakhg 3 3 Reeearch Proceee 3 Develop hypotheeie or question 3 8 State apeci c testable prediction 3 Collect data Variablee 3 Baeie for reeearch 3 8 Individual elemente of hypothesespredictione 3 Muet vary A Varawe Hae Eye9 3 8 15 a category 3 8 15 a member of a category 3 8 Can change 3 8 Cannot change Sharon Seidman PhD CAS 301 Developmental Inquiry 86 Methodology Variables vs Levels 3 Test scores 3 52 inches 3 Grade of A 3 Charlie Brown 3 Beverages 3 Pants size 3 8 Popcorn 3 8 Vanilla 3 Blue 3 Authors 3 Hair color 3 Cartoon characters 3 Ice cream flavor 3 12 units Types of Variables 3 Situation Variables 3 PlaceSetting 3 May be pre existing or created 3 ParticipantSubject Variables 3 Person 3 Preexisting 3 Response Variables 3 Participants reaction to situation 3 BehaviorsOutcomes Sarne characteristic may be a different type of variable depending on question hypothesis Sharon Seidman PhD CAS 301 Developmental Inquiry 86 Methodology Types of Variables Subject Situation Response 38 Cold vs warm rooms 38 Timeofday 38 Tall vs short people 38 Ethnicity 38 Happiness 38 of letters read 38 Children vs adults 38 Enthusiasm 38 GPA 38 Test scores 38 Instructions 38 Selfesteem 38 Age 38 Gender 38 Hair color 38 Language Defining Variables 38 Conceptual Definitions Idea you are trym to test 38 Operational Definition 777m you are actually measurhg Defining Variables 38 Social skills 38 Communication skills 38 Thematic curriculum Sharon Seidman PhD CAS 301 Developmental Inquiry 86 Methodology Operational Quality Validity 3 Construct validity 3t Measure assess concept 3t Measure doesn39t assess anything else 3 lntemal validity 3 Study measures cause 3 8 No other explanation is suggested 3 8 External validity 3 Study applies to real world 3 Results apply to population of interest Exercise Identifying and Defining Variables Expectations 3t Hypotheses Stamth ofpossibe Martiansrip between conceptual varables 3 Prediction 5mm ofemxtedreatimship kenem operatima Varables Sharon Seidman PhD CAS 301 Developmental Inquiry 86 Methodology Expectations 3 Two kinds of hypotheses 3 Group differences 3 Relationships 3 Must specify nature of expectation Relations Among Variables 3 Linear relations between 2 variables 3 Measured by correlation coefficient 3 Include 3 8 Predictor variables 3 Criterion variables Correlations Positive Negative Sharon Seidman PhD CAS 301 Developmental Inquiry 86 Methodology Correlations Weight Candy Intake Exercise Relations Among Variables 3 Linear relations between 2 variables 3 Comparisons between 2 groups 3g Input 3 Experiments Independent variables created situation 3 Quasi experiment Existing variables preexisting subject variables 3 Outcome variables dependent variables criterion variables Between Group Comparisons Sharon Seidman PhD CAS 301 GROUP Commmsows Sharon Seidman PhD CA5 301 Week 7 TODAY39S AGENDAS Review exam 1 5 Collect article 1 workshee rs 3 Learn more abou r group comparisons BUT FIRST THINKING ABOUT EXAM 1 Week 7 1 Sharon Seidman PhD CAS 301 RESEARCH PROCESS i Develop hypothesis or question E State specific testable prediction Collect data VARIABLES E Basis for research 3 Individual elements of hypothesespredictions Ii Must vary A variable Has level i Is a category Li Is a member of category Can change Cannot change DIFFERENT TYPES OF VARIABLES Week 7 2 Sharon Seidman PhD CAS 301 VARIABLE DEFINITIONS gt Malid Internal Pred391ct391ve Test retest Concurrent Inter rater Convergent Nominal Discr391m391nant LIKERT SCALES E Special type of ordinal scale 3 Ordered rating categories i Example 1 2 5 Not at all A Lot DESCRIBING A GROUP Norms Central Tendencies EMean HMedian EMode E Individual Differences Variability Range Standard Deviation Week 7 3 Sharon Seidman PhD CAS 301 SCENARIO 1 Questions 3 Variable identification EXAxis IIY xis E Type of graph i Causality VARIABLE5 S CAU5ALITY ii Types of variables Su 39 E Created vs preexisting variables ESubject always preexisting Situation a response maybe 0 Preexisting 0 Created SCENARIO 2 The Administration for Children and Families decided to use the Peabodi Picture Vocabulary Test 3rd Edition PPVTI I to assess children39s receptive English vocabulary ey liste t e following data a out the test as the reason for olce39 The correlation between Head Start children39s PP TIII score and their kindergarten knowledge tes s Week 7 4 Sharon Seidman PhD CAS 301 CONSTRUCT VALIDITY it Face validity subjective i Criterion validity objective IPredictive in future HConcurrent between groups Convergent between measures EDiscriminantdivergent between measures CONSTRUCT RELIABILITY E Interitem internal consistency Splithalf IE Cronbach39s alpha on Testretest Interrater Alternate forms SCENARIO 5 The US Department of Health and Human Services conducted a study of Head Start39s impact on children39s development in 2004 2005 The compared the cognitive and academic sgills n of c ildren who did a did not enroll in Hea Start programs and used multiple re ression to determine how muc Head Start par icipation was associated with improved child outcomes I 3 Your 4 ur ammo Mtasur Olds c 15 Peabody Picture Vocabulary Test III 12 3 IWoodcockJohnson III LetterWord Ident 24 2 Letter Numinchsk 49 4 Color Naming Task 1o Week 7 5 Sharon Seidman PhD CAS 301 SCENARIO 4 change in Desired Real 1 Fania 5an Dasmd Result 1 m Fan CORRELATION STRENGTH DIRECTION 10 to 70 Strong Negative 69 to 30 Moderate Negative 29 to 00 Weak Negative 00 to 29 Weak Positive 30 to 69 Moderate Positive 70 to 10 Strong Positive Naf re same as percentage 5CALE5 OF MEASUREMENT RatioInterval Mean Median Mode Ordinal Median Mode E Nominal E Mode Appy 7 0 quantitative measures Week 7 Sharon Seidman PhD CAS 301 Some MORE REVIEW GOALS OF RESEARCH Descri tive EDescrlphon gt Stutisfics El Prediction Inferentiul Statistics monusution Normc skewed Week 7 7 Sharon Seidman PhD DIFFERENCES IN RANGE A A DIFFERENCES IN STANDARD DEVIATION A A KINDS OF PREDICTIONS 3 Linear Relations 3 Correlations 3 Group Comparisons 3 Experiments Week 7 CAS 301 Sharon Seidman PhD LINEAR RELATION CLASS SIZE FIGHTS CORRELATIONS LINEAR RELATION Fights Per Day Class Size Week 7 CAS 301 Sharon Seidman PhD CAS 301 SOMETHmG NEW 1 i i GROUP g COMPARiSONS CLASS SIZE FIGHTS 35 10 3O 9 2 8 15 6 BETWEEN GROUP COMPARISON E Group 1 Classes with 20 Kids i Group 2 Classes with 10 Kids Question Is the amount of fighting significantly different Week 7 Sharon Seidman PhD CAS 301 DESCRIBING GROUPS 3 Review IiNorms mean median mode UVariability range standard deviation New question how similar are two groups How many group members are similar How much do two graphs overlap lIs difference between groups bigger than chance FREQUENCY OF FIGHTING IN 20 STUDENT CLASSES Number of Classes Number of Fights FREQUENCY OF FIGHTING IN 10 STUDENT CLASSES Number of Classes Number of Fights Week 7 1 1 Sharon Seidman PhD PROPERTIES OF A NORMAL DISTRIBUTION Deviation Area 22 136 341 341 136 2 2 erar dard 3s 2s 15 Mean 15 25 3s TANDARD ASSUMPTIONS IN GROUP COMPARISONS E Normative vs Atypical Group Members l Middle 95 normal Extreme 5 atypical l 0 Very high scores 25 I 0 Very low scores 25 El Group Comparison Process HCompare normative group members lMeans SI middle 95 FREQUENCY OF FIGHTING IN 20 STUDENT CLASSES Number of Classes 5 01 6 7 8 Number of Fights Week 7 CAS 301 Sharon Seidman PhD CAS 301 COMPARING GROUPS 95 01 H o m T smnsnc E Numerical representation of difference between groups E Difference between groups a iV a ea by variability within the groups Mean1 Meanz SD GROUP COMPARISONSI 2 POSSIBILITIES E Groups are different Research Hypothesis Groups are the same Null Hypothesis Week 7 13 Sharon Seidman PhD CAS 301 FREQUENCY OF FIGHTING IN 20 STUDENT CLASSES Number of Classes 5 01 6 7 8 Number of Fights REALITY vs CONCLUSION Inferential statistics determination about probability of observed difference between groups Small probability accept research hypothesis Large probability accept null hypothesis Week 7 14 Sharon Seidman PhD CAS 301 Reality Our Null is Null is Conclusion True False Accept Null Reject Null Reality Our Null is Null is Conclusion True False Accept Null Type II T Error Reject Null Type Error PROBABILITY E Criterion 05 5 i Probability of Type 1 Error DAccepting research hypothesis when null is true Week 7 15 Sharon Seidman PhD I I l 95 zs l s n l 99 33 I I I CAS 301 KEYS TO COMPARISON E Norms M i Variability Standard deviation SD i Sample size Degrees of freedom DEGREES OF FREEDOM H Related to sample size i Possible variability in sample How much freedom is there to get a different score Week 7 S haro r1 Seidman PhD CAS 301 WRITING RESULTS i Need all the information EDegrees of Freedom lfstatistic EProbability criterion alpha E fdf plt 05 ii f18 375alt 05 EFFECT SIZE E Similar to variance in correlations 3 Measures power of fanalysis Week 7 Sharon Seidman PhD CAS 301 Inquiry 86 Methodology More on Data Collection 8 Group Comparison Sharon Seidman I llD m 31 Today s Agenda a Review in Exercise on t tests it Find Article 2 a New information a More on group comparisons a More on data collection a Analyze Article 2 Schedule Reminder jVo cass qe weefor I l SprQq Bred mi Sharon Seidman PhD CAS 301 Inquiry 86 Methodology Research Process a Examine association between 2 variables 4 Develop hypothesis or question a State specific testable prediction in Collect data Variables a Basis for research a Individual elements of hypothesespredictions a Mu st vary A variable Has levels a Is a category a Is a member of category in Can change a Cannot change Variable Definitions gt Valid Reliable Scale OFace olnternal 0Ratio 0 Predictive 0Test retest Olnterval 0Concurrent Olnter rater Ordinal 0Convergent 0 Nominal Discriminant Sharon Seidman PhD Variables 8 Causality a Types of variables a Subject 4 Situation a Response in Created vs pre eXisting variables a Subject always pre eXisting a Situation 85 response may be a Pre eXisting a Created CAS 301 Inquiry 86 Methodology Goals of Research a Description Descriptive Statistics in Prediction lnferential I Statistics in Cau sation Describing a Group a Norms Central Tendencies a Mean 4 Median 4 Mode in Individual Differences Variability a Range 4 Standard Deviation Sharon Seidman PhD CAS 301 Inquiry 86 Methodology Kinds of Inferences 4 Linear Relations 3 Correlations a Group Comparisons i Experiments Comparison Between 2 Groups it Based on a Difference between group norms means 4 Differences Within groups standard deviation 4 Odds that sample represents population degrees of freedom in Produces probability of Type 1 Error Example a Is the number of fights in classrooms With 20 children significantly greater than the number of fights in classrooms With 10 children a Steps a Sample classrooms in each group 4 Count the fights in each room 4 Compare groups to see if norm for 20 children classes is typical of 10 children classes Sharon Se idman PhD Number of Classes Frequency of Fighting in 20 Student Classes I 6 7 8 Number of Fighfs 910 CAS 301 Inquiry 86 Methodology Number of Classes Frequency of Fighting in 10 Student Classes 4 6 Number of Fighfs Area Properties of a Normal Distribution 22 136 341 341 136 22 5 Standard 35 25 Deviation 15 Mean 15 25 Sharon Seidman PhD CAS 301 Inquiry 86 Methodology Comparingi 95 Groups I 4 5 6 7 8 b I 10 Children 20 Children T statistic a Numerical representation of difference between groups a t 18 375p lt 05 Degrees of Probability of Type 1 Error Difference between means divided by standard deviation 139 L Reality Decision Null is Hypothesis True is True Accept Null Type H Error Accept Type I Hypothesis Error Sharon Seidman PhD CAS 301 Inquiry 86 Methodology Degrees of freedom a Related to sample size a Possible variability in sample a HOW much freedom is there to get a different score Exercise Moving on to Article 2 Sharon Seidman PhD CAS 301 Inquiry 86 Methodology Research Project Context 4 Article Review 1 4 Article Review 2 a Selfiselected article a Sarne theme as article 1 a Individual or 1 partner a Develop presentation due 4 5 4 Article Review 3 a 2 4 additional articles a Individual or group up to 4 a Workday 4 12 a Due 4 l9 Article Review 2 Activities it Now a Later 4 Identify partner a Review article if desired use worksheet a Select article 4 Identify key points a Print article 4 Develop presentation More on Group Comparisons Sharon Seidman PhD CAS 301 Inquiry 86 Methodology Scales of Measurement a RatioInterval gt Mean Median Mode in Ordinal gt Median Mode in Nominal gt Mode Scales of Measurement in Between Group Comparisons a Grouping Variable a Called independent or predictor a Used as nominal measure a Outcome Variable a Called dependent or criterion 4 Must it Be intervalratio or Likert a Accommodate math Defining Groups 4 Created grou s a Independent variables a De ned by experimenter a Create experimental design a Group creation strategies a Random assignment a Matched pairs 4 Existing groups a Predictor variables a De ned b a Subject variables a Preeexisting situation variables a Create quasiexperimental design Sharon Seidman PhD and experience a 3 different designs a Cross sectional 4 Longitudinal a Sequential a Qu asi eXperimental Developmental Designs 4 Examine change associated With age a Attempt to differentiate development CAS 301 Inquiry 86 Methodology CrossSectional Cohort E ects Longitudinal CrossSectional 1 i Sharon Seidman PhD Longitudinal Sequential Cross Sectional CAS 301 Inquiry 86 Methodology Types of Comparisons a Two different groups of people a Scores are independent of each other a One measurement does not in uence the other a Independent group design a One group of people before and after pretest vs postetest a Scores are related to each other a One measurement does influence the next a Repeated measures design Relations among Design Elements in Existing vs created grouping variables a Predictor vs independent variables a Independent groups created by a Random assignment a Matched pairs a Quasi experimental vs experimental in Independent vs Repeated measures a 2 different groups vs one group measured 2 times 4 Longitudinal design repeated Sharon Seidman PhD CAS 301 Review for Exam 1 ee Sharon Seidmon CAS 301 mnan me 3 mm w a pm ng 1m Mmunvwebng mssm iudmlsmm dbrabmade 1 ummm mun n1 wmmm sausages eg PsycFmSTand Enema CAS 301 Learning Objectives w mnwm mate aquot o J Lmieagnenrium nth CSUFLmiFnhen mecaunmerandcmecmn mkm iw I me my nr om nemevovmls Undzrslan 69 9quotng r 1mm mm on E i is owed u m a m mummumm and mu mumm mam snemsy omvzlms mo or o a nun unveiled amunmew en resume CSUF and u wanna m mm mm on n woe imwmmm niemelveseaxh mm mm H mm mm gntnmbrmaunn may ow n Mesa seams rm APA 5M5 uwmmn Amm n vmhan mm Pompom ow Mam Popular Writing Scholarly Writing Audience Everyone Modem Professional Associations amp Access Everywhere Universities o For accoracys ReView For interest innovation Personal Text citations EVldence sources Emoiricai data Pars721779 7110 75 vampnon 1 Examples People Vazng 071 jars7 Review for Exam 1 Sharon Seidman PhD CAS 301 APA Style Papers Research Report Literature Review Title Page 39Title Page r Abstract r Abstract Introduction Introduction 39 Method Evidence 39 Results JLiterature 39 Discussion JExperience 39 References References 39GraphsaFigures GraphsaFigures 39 Appendices 39 Appendices Abstract Summary Of entire paper quot Included in library thGbGSGS Introduction 39Topic Information JWhat paper is about Why we should care Background Information Past research Prior Knowledge HypothesesExpectations Review for Exam 1 2 Sharon Seidman PhD CAS 301 Method MUN05 0075 to collect information quot Design ParticipantsSample 39 Materials Procedure Results MUN05 ear780 39 Description quot Statistical analysis quot No interpretation of data Discussion Warm resu t5 meg7 Comparison to expectations 39 Comparison to past research I Limitations Interpretation Review for Exam 1 3 Sharon Seidman PhD LEDGE CONSR CT t i L CAS 301 a a g iieri research tugs Mar money1Q Ari Begins with hypothesis general concept or question Create specific testable prediction 1 Prediction can specify reiotioo or group differences lolJDr riigxriis 3 i L liaD ialDi t predictiurrs based on it testrelesl re iamlity interrater re ia oility i J Classfya research approach as expenmenzal Sampling and Assignment alional J Distngiiislianiongsamplingiechniques J Identity different strategies for collecth data random haphalard quota stattied ranch ea 3 Inmaliu I obsehatori case study armiial research range in a wirelaiional study disadvantagesafeach riiithin iV N39FHl 39 39 I 3 I i i t II Expectations Variables CI Discriminate between independent variables predictor variables including the subset called subject variables dependent variables and criterion variables Distinguish between variablesfactors and valueslevels of variables Explain the difference between conceptual and operational definitions and the importance of each Identify the scale of measurement used for iven measures nominal ordinal intervalratio Assess quality of measurement using the general concepts of validity and reliability including criterion validity convergentdivergent validity race validity ElEl El D testretest reliability interrater reliability Review for Exam 1 Sharon Seidman PhD CAS 301 Variables 39 Basis for research Individual elements of hypothesespredictions 39 Must vary A variable Has levels 39 Is a category 39 Is a member of a r Can change category 39 Cannot change Different Types of Variables Variable Definitions gt Operation Reliable Internal Test retest Face Predictive Concurrent Ratio IntervaI Inter rater 0rdinaI Convergent NominaI Discriminant Review for Exam 1 Sharon Seidman PhD CAS 301 Measurement Error quot Goal assess concept 39 Error assess something e1se Source of error Operational definition doesn t match validity Operational definition isn t consistent reliability Operational Quality Validity Construct validity JMeasure assess concept Measure doesn39t assess anything else quot Internal validity sStudy measures cause SNo other explanation is suggested External validity Study applies to real world Results apply to population of interest Construct Validity r Face validity subjective r Criterion validity objective Predictive in future Concurrent between groups Convergent between measures sDiscriminant between measures Review for Exam 1 6 Sharon Seidman Ph D Operational Quality Reliability quotr Test retest Alternate for ms Inter nal consistency 2 Split half J Cronbach s alpha 0 gt Ranges from O to l J 60 is acceptable 4 80 is good Inter rater CAS 3O 1 Ii Distinguish among Sampling and 5am I Research Strategies astlons about l Age 1e 39 erences range in 3 Relative contrib nd 3 e nunure I wit 3 Continuous and discanl a 1 Stability and instability 3 Di 39 rees r I39E 39 Irn terpretatlon of research ou le DI BS about as ss secllonal seq 139 39 Research Ethics CI Understand the importance of evaluating the Identify stress and psychological harm to costbenefit ratio when designing research participants that potentially result from El Demonstrate awareness of the importance of research participation peer review of proposed research El Understand the ethical issues related to methodology prior to data collection conducting research with children and other Cl Identify when deception may be necessary in special populations conducting research and be able to distinguish deception from a lack of informed consent Review for Exam 1 Sharon Seidman PhD in mm wait i m armali grm the resea39 512 cal imd39ngs e g mums and external lnterv39e tigures or takes at summarized 1 such as those that appear w texts rvspaoms o mclEs ru man m sums are Wm eh esgn emphved and ex mn s 1 Understand 3 Exps Expl mem names 3 Recngmze men cause and sheet are being tested a mmwsnmg hermequot tune a a quawmemen Camus at measuring manipulation rm ems m 1299 auvanuges a usmg a mp39ex experimental assign imare than me IS urgimms CAS 301 Descriptive Analyses El Create a frequency polygon or bar graph given a set of data El Compute explain and graphically represent the measures of central tendency that are appropriate for a set of given data CI Distinguish between inferential and descriptive statistics and be able to classify various statistics appropriately Frequency Distributions Three styles Pie graphs 2Bar graphs histograms Line graphs frequency polygons 39 Select based on Type of scale fNLtIleel39 of variables Point to be emphasized Review for Exam 1 Sharon Seidman PhD CAS 301 Receptive Language Girls Boys Receptive Language 7 El Girls I Boys er Yer Emer39g39ng Nmost Fully Receptive Language EIGir39Is Emerging Almosf Fully Review for Exam 1 Sharon Seidman PhD CAS 301 Describing Groups Central Tendencies Mean mathematical average Median middle score Mode most common score Variability Range smallest to largest score Standard Deviation normality of central tendency Normal Skewed 60018 of Research 739 Description gt Descriptive Statistics 9 Prediction lnferential Statistics r Causation Review for Exam 1 10 Sharon Seidman PhD CAS 301 Correlational Studies El Create a scatterplot and recognize the type of relationship represented positive negative curvilinear no relation CI Estimate the sign and magnitude within 3 for linear relationships between two variables El Interpret the correlation coefficient 139 including direction and strength of relation Cl Discuss factors influencing statistical significance of the correlation coefficient r El Explain the limitations eg regarding cause effect interpretations type of data needed and utility of the correlational approach Two Variable Graph Mean Score for Group Members h Aw Wm Two Variable Graph Individual Score for Each Person 106 104 102 100 PPVTR a Review for Exam 1 Sharon Seidman PhD CAS 301 mm Em 0 Linear Relation Nature of Linear Relation Review for Exam 1 12 Sharon Seidman PhD Curvilinear Relation CAS 301 Correlation Coefficient l 00 to 70 Strong Negative 69 to 30 Moderate Negative 29 to 00 Weak Negative 00 to 29 Weak Positive 30 to 69 Moderate Psitive 70 to 100 Strong Positive Factors Influenc1ng Correlat10n r Restriction of range r Multiple correlations 39 Partial correlations Review for Exam 1 ShwenSeannHLD CASBOI Limitations amp Requirements 39Limitations gLinearreiationoniy inssociation isn t cause Sampieintiuencesstrengtn Reauirements JMathematicaidata Ratio interval Likert Adeauatesampiesize Utility iDescription Prediction Structuraimodeiing given a desc means Review for Exam 1 14 Sharon Seidman PhD Review for Exam 1 CAS 301 Sharon Seidman PhD CAS 301 Inquiry 86 Methodology ngaroq Seidrqaq Cf S 307 jWore 0 aa Pdecho lt52 Group C onzparSoq Par 2 Review Reward Process Examine association between variables Develop hypothesis or question State specific testable prediction Collect data Sharon Seidman PhD CAS 301 Inquiry 86 Methodology Varawe Basis for re search Individual elements of hypotheses prediction s Must vary A variable Has levels Is a category Is a member of category Can change Cannot change Varable CDefIp39fbs l Varawe Q Gamafly Types of variables Subject Situation Response Created vs pre eXisting variables Subject always pre eXisting Situation 85 response may be Pre eXisting Created Sharon Seidman PhD CAS 301 Inquiry 86 Methodology Goa5 g Researcz Description SDtCSt ritptiVe a 1s 1cs Prediction lnferential I Statistics Causat1on CDescrbklg a Group orms Central Tendencies Mean Median Mode Individual Differences Variability Range Standard Deviation fzcs OfJy erezces Linear Relations ECorrelations Group Comparisons LiEXperirnents Sharon Seidman PhD Conyaan39squeweeq 2 Groups Based on Difference between group norms means Differences Within groups standard deviation Odds that sample represents population degrees of freedom Produces probability of Type 1 Error CAS 301 Inquiry 86 Methodology gxanzpe Is the number of fights in classrooms With 20 children significantly greater than the number of fights in classrooms With 10 children Steps Sample classrooms in each group Count the fights in each room Compare groups to see if norm for 20 children classes is typical of 10 children classes Frequency g 39g yQO Sfua ef Classes Number of Classes T I 5678910 Number of Fighfs Sharon Seidman PhD CAS 301 Inquiry 86 Methodology Frequency g 39gg yJ 0 Sfua ef Classes Number of Classes I 3 4 5 6 8 Number of Fighfs Droperfes g a ornza CDSfrbufbq Area 22 136 341 341 136 22 erar dard 3s 25 15 Mean 15 25 35 Deviation 95 Gonzparkzg Groups X I I I on I 4 5 6 7 I 10 Children 20 Children m Sharon Seidman PhD CAS 301 Inquiry 86 Methodology fesfafSft Numerical representation of difference between groups tl8 375p lt 05 Degrees of Probability of Freedom T e 1 Error Difference deviation Eeyrees offreeconz Related to sample size Possible variability in sample How much freedom is there to get a different score Drobab y Errors r L Reality Decision Null is Hypothesis True is True Acce t Null Type H P Error Accept Type I Hypothesis Error Sharon Seidman PhD CAS 301 Inquiry 86 Methodology Varables fr Belaveer Group Conyaan soqs Grouping Variable Called independent or predictor Used as nominal measure Outcome Variable Called dependent or criterion Must Be interval ratio or Likert Accommodate math weopnyeqfa Desqu Longitudinal 01 59 Sequential Sectional 1 O 2 I 2 Sharon Seidman PhD CAS 301 Inquiry 86 Methodology jqferveqfbq Desqu 7rqCpe oqufeMfbq Sfua fes a I g I l 5 l I g I 8quot I L Before 39 After BaseIne qaySS OJ 6 ch 5 5 2 E I Single Before 39 After Case w Sharon Seidman PhD CAS 301 Inquiry 86 Methodology Prefesf r Pos equayy39s Frequency Score Pos esf vs Coqfro qayys Test Group Control Group Frequency Score Before After Group Averages m 5 amp139ng Mssfgymeq Sharon Seidman PhD CAS 301 Inquiry 86 Methodology SanyyI39Qq Identification of participants Strate gies Random Entirely random Stratified random Clus ter H aphazard my Quota 75594an Creation of experimental groups Must be determined by experimenter Only applies to Independent Variables S trate gie s Random Haphazard jWefyocs offDalia I decho Sharon Seidman PhD CAS 301 Inquiry 86 Methodology CDafa Calledbiz CeCmkues Testing Observation Survey questionnaire Interview Content analysis Pre eXisting source archival data Obsewfbq Sfral ey es Naturalistic vs Systematic Participant vs Concealed Issues Reactivity Reliability coding recording Sampling vs comprehensive Quesfbzzare Jssues Measure ideas rather than behavior Ease data collection Evaluate sample characteristics Distribution Find target population Ensure adequate response rate Format Close vs openiended questions In uence of wording Reactivit Social desirability Order effects Sharon Seidman PhD CAS 301 Inquiry 86 Methodology Coqfequayy39s Analysis of thing rather than person Requires coding counting Jzl eW ws Same risks as Observations Surveys Advantages Detailed qualitative information Clinical interview exibility Facfora Desqu Sharon Seidman PhD CAS 301 Inquiry 86 Methodology Wore Compex Easy15 9 Multiple levels of a variable More than 2 groups 9 Multiple independent variables 2 IVs and a DV Fear l m Dark Light Room Room Fear Wa7l People Monster 5me Stories Stories Jzl eracfbq gjj ecfs Fear Dark Light Room Room Sharon Seidman PhD CAS 301 Inquiry 86 Methodology VumertaMzaQSS A an I 7 Cell Means Show Interaction Effects Dark Light Monster 6 1 People 3 1 Marginal Means Show Main Effects of Single IV SfafSftaMzaQSS for Facforas Analysis of Variance ANOVA Described by of IV Predictors One way TWO way Etc Described by levels of IV Predictors 2 X 2 2 X 3 14 Sharon Seidman PhD CAS 301 Inquiry 86 Methodology 0 IWay39 VOVJV 03 wrong 2 spawn ragga Little Medium Lots Room Lighting Two IWay39 VOW Fear Dark Light Room Room 3 x Z YOW Sharon Seidman PhD CAS 301 Inquiry 86 Methodology SiafSftaMzaQSS Procedure ANOVA Statistic F Differences Between Grou s Differences Within Groups Same procedure but more groups than t test Eeyrees q Freecon 1St Variability from groups Levels of IV 1 2nd Variability from subjects e rror Facfora gxanzpe Effect of Story 85 Light on Fear 3 Comparisons 2 main effects 1 interaction Statistics 3 statistical statements Each analysis uses different means Sharon Seidman PhD CAS 301 Inquiry 86 Methodology gxanzpe Source of Variance df F Type of Story 1 15 Room lighting 1 20 Interaction 1 22 Error 36 Raw7 5 Main effect Marginal Means F statement There was a significant main effect for type of story children were more fearful with monster stories M 35 than people stories M 20 F1 36 15p lt 05 Raw7 5 Interaction effect Cell Means F statement There was a significant interaction between type of story and room lighting In dark rooms children were more fearful with monster stories M 60 than people stories M 30 but in light rooms they were less fearful whether they read monster M 10 or people stories M 10 F1 36 15plt 05 CAS 301 Developmental Inquiry amp Methodology Week 1 Sharon Seidman PhD I 0A8 80 Devec opmentac Inquiry amp Met odoc ogy 84mm Saldman PAD 39 Standards amp Accouula wily W W W W W Learning goals 6r Maj or evrCore classes 0A8 learning Goaes W W W 6r Development erTheory 6r Research 6r Contexts 6r Developmental Inquiry erlnformation Literacy 6r Field Based Practice 6r Professional Growth CAS 301 Developmental Inquiry 86 Methodology Sharon Seidman PhD Week 1 Goaes and 00iectives wmaa aw am em up Learning Objectives for CAS 301 erlnformation Acquisition erKnowledge Construction erEvaluation and Interpretation erCommunication Serves as Study Guide lot Me Finad Standards amp Accountaaieity elm wm sum W erLeaIning goals erTethooks er Core activities er Final exam course Materiaes elm ageW 23pm erMethods in Behavioral Research 8Lh Ed erAPA Publication Manual 5m er Computer supplies er Saving media erEmail address erlnternet access er Printer acce ss CAS 301 Developmental Inquiry 85 Methodolog Week 1 Sharon Seidman PhD course Activities Participation W W W W a Includes a Inecl ass exercises amp Worksheets a Discussion a 10 assignments will be graded wWorth 50 points total course Activities Rasaarc Prefect W W W W a Examine relations among a ECE quality 6ranin characteristics a Child outcomes a Based on key article CAS 301 Developmental Inquiry 86 Methodology Week 1 Sharon Seidman PhD Rasaarcli Project eeamauts m m mm W erArticle Review 1 key article erArticle Review 2 additional article erArticle 2 Presentation erArticle Review 3 2 4 new articles erProject Outline er Paper er Project Pre sentation exams m wm gum W er 2 Midterms er 50 points each er Include a Short answer a Multiple choice a Exercises er Standardized department final er 60 points er Includes a Computer portion a Paper portion Sc adueiug Discussions M ageW gum erlmplications of compressed format erLong long long long class erAllocate whole week for each exam erNeed to plan CAS 394L Practicum er Supervised eldwork erlncludes erEthics erMandatory reporting erReview of DAP CAS 301 Developmental Inquiry 85 Methodolog Week 1 Sharon Seidnian PhD WWWW Mi WWWW Jntroduction to Resume W W W W a Goals a Process a Implications 3 Resume Genes W M For any topic can seek different kinds of informa ion a Description a Causation 6 Prediction CAS 301 Developmental Inquiry 85 Methodology Week 1 Sharon Seiclman PhD We Davaeopmaut OI Wa liiug M a a waking W warm4 Description gum3 we gt W 1M What does locomotion look like at different ages v causation lemma wm ww39i gamed What experiencesin uences the move from one ability to j x w CAS 301 Developmental Inquiry 85 Methodology Week 1 Sharon Seidman PhD Prediction M g W atMa a Given current skills when will a child learn to walk How wide 7 deem to wadli Nature vs Nurture lemma wm leMa a wl w endogenous vs exogenous CAS 301 Developmental Inquiry 85 Methodolog Week 1 Sharon Seidman PhD Mcgraw Twin Study W W W Gunslious WAN aw m39h39me pariods or saquaucas in davaeopmaul WDoas axpan39ama nurtura a ul l osa saquaucas II atlases a There are critical periods a Experience will not in uence developmental milestones McGraw ampJuhnny 1932 Design W W W W a Provide infants with different experiences a EXamine their motor and physical development over time McGraw mimmy 1985 CAS 301 Developmental Inquiry 85 Methodolog Sharon Seidman PhD Participants W W a Controls a Study began when children were two months ol 0 2 twins Jimmy and Johnny 0 56 age matched children a Raised in normal fashion Week 1 Procedure Johnny Jimmy Controls Many Mode rate activities activities activties High Low Mode rate challe nge challenge challenge Little ode ra e stimulation stimulation stimulation Last 1 V2 months together CAS 301 Developmental Inquiry 85 Methodolog Week 1 Sharon Seidman PhD conceusions W W a Your Opinion a Was there evidence for critical periods or normative sequences a Did training affect physical and motor development a McGravxfs Decisions euume Jssuas W W a Stress amp psychological harm a Deception a lnformed consent WWWW LI WWW 9 i 3 33 CAS 301 Developmental Inquiry 86 Methodology Week 1 Sharon Seiclman PhD Popular Scholarly Writing Writing Academic 85 Audience Everyone Professional Associations 85 Access Everywhere Universities Review For interest For accllraCy 86 innovation Personal Text citations Ev1dence sources Empirical data Exam les Parenting Child Develop ment p People Young Children APAStyee Papers Research Report Literature Review erTitle Page erTitle Page erAbstract erAbstract er Introduction er Introduction erMethod erEvidence er Results er Literature er Discussion 6r Experience erReferences erReferences erGraphs amp FigliresefcrraphS amp Figures erAppendices WAPPendiCCS Aastmct wm 1M ratW erSummary of entire paper erlncluded in library databases CAS 301 Developmental Inquiry 86 Methodology Week 1 Sharon Seidman PhD Jutroductiou m m mm W erTopic Information erWhat paper is about erWhy we should care erBackground Information erPast research erPrior knowledge erHypotheses Expectations Mat50d vim wm gum W What was done to collect information erDesign erParticipants Sample or M ate rials erProcedure Rasuets wm ageW 2 W What was learned erDescription erStatistical analysis erNo interpretation of data CAS 301 Developmental Inquiry 85 Methodolog Sharon Seidman PhD Discussion W W What do results mean wComparison to expectations wComparison to past research erLimitations erlnterpretation Week 1
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