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T J English 155 cards

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Cards in this deck (155)

  1. 1Scales of measurementsNominal, Ordinal, Interval, RatioScales of measurements
  2. 2Nominalno #/quantitative, they are categories/groups. Ex: eye color, gender, college majo
  3. 3Ordinalminimal quantitative, know order but not strength. Rank order the variable levels. Ex: lowest-highest, importance of education, health, crime
  4. 4Intervalquantitative, intervals between levels are equal in size (1-2, 2-3), 5 or more levels. Ex: rating scales, very negative/very positive, no absolute zero
  5. 5Ratiohas equal intervals & absolute zero point that indicates absence of variable being measured. Uses data that can be summarized as a mean or math average. Ex: Time, weight, length.
  6. 6IntervalQuantitative
  7. 7NominalCategories or groups
  8. 8Ordinalranks without strengths
  9. 9Ratioabsolute zero, equal parts
  10. 10Scales of measurement stepsCreate operational definition of variable and have 2+levels of variable. Levels are described by using scales. Scale used determines types of stats appropriate for results collected
  11. 11Levels are described by usingscales
  12. 12how many ways are there to describe results3
  13. 13what are the three ways of describing resultscompare groups in %. Correlating individual scores. Compare group means.
  14. 14compare groups usingpercentages
  15. 15Correlating individual scoresNo separate groups of subjects Individuals are measured on 2 variables Each variable has range of numerical values
  16. 16Group Meanscompare the means of the control to the manipulated variable
  17. 17Frequency distributionsAnalyzing & Describing Results: 1st step is to understand data so you can describe it How many people received each possible “score” Percentage of students who received a given score on exam Number of people who received each score on an exam
  18. 18how to graph frequency distributionsPie Charts, Bar Graphs, frequency polygons, histograms
  19. 19Pie Charts# of scores is turned into %, nominal scale info, depicts 1 variable
  20. 20Bar Graphsuse separate bar for each score, able to compare more variables
  21. 21Frequency Polygonsuses lines to depict scores.
  22. 22Histogramsuses bars, continuous values, are connected
  23. 23Pearson CorrelationR
  24. 24Pearson R Correlationstrength of linear association between 2 variables
  25. 25Variabilityrange of scores
  26. 26Variability is composed ofStandard Deviation, Variance, Range
  27. 27Standard deviationaverage deviation of scores from mean, square root of variance.
  28. 28RangeDifference between highest and lowest score
  29. 29Variancedegree to which scores vary about the group mean
  30. 30how many ways are there to describe descriptive statistics2
  31. 31what are the 2 ways of describing descriptive statisticsCentral tendency (overall score), Variability (range of scores)
  32. 32Central tendencyoverall score
  33. 33variabilityrange of scores
  34. 34what are the 3 measures of central tendencymean, median, mode
  35. 35meanarithmetic average dividing the sum by the number of scores, interval or ratio (values of #’s)
  36. 36medianthe middle score in a distribution, divides group in half, very useful if scores are skewed in one direction, ordinal scale (rank order)
  37. 37modesimplest indicator, the most frequent score, nominal scale (category)
  38. 38values of #smean
  39. 39Rank ordermedian
  40. 40categorycamode
  41. 41Internal Validitycertain that results are attributed to the IV, most important in Lab experiments
  42. 42External Validityextent to which findings may be generalized
  43. 43participantscollege students are the most participants in studies(70%), intro to psych, diverse group
  44. 44Meta-analysisexamining results of multiple previous studies to determine reliability of findings
  45. 45Inferential Statisticsgeneralize about population, accuracy is necessary
  46. 46accuracy is necessary becausethe results of a given study are based on data obtained from a single sample of researcher participants and Data are not based on an entire population of scores
  47. 47Inferential statisticsbegins with standard deviation and is a way to describe results
  48. 48Inferential StatisticsAllow researchers to make inferences (predictions) about the true differences in populations of scores based on a sample of data from that population Allows that the difference between sample means reflects random error rather than a real difference
  49. 49Null HypothesisH0: Population Means are Equal = there is NO difference Population means are in fact equal Any mean difference observed in the samples reflects the random error. IV had no effect
  50. 50Research HypothesisH1: Population Means are Not Equal = there is a difference Population means are not equal The mean difference observed is real. IV had effect
  51. 51Research HypothesisIV had effect
  52. 52Null HypothesisIV had no effect
  53. 53How do we determine significant resultsAlpha Level
  54. 54Alpha Levelprobability required for significance. Most common is .05 (5%) or less (5 out of 100 chances that results were due to random error or CHANCE).
  55. 55As the sample size increases(less sampling error), we can be more confident that your outcome is actually different than the null hypothesis
  56. 56The larger the F ratiothe more likely it is that results are significant.
  57. 57the larger the sample size,the larger the significant results, which provides better estimates of true population values
  58. 58larger effect size more likely to obtainsignificant results
  59. 59goal is to determine if results are reliable(to be confident as a result of the sample size)
  60. 60alpha level you chooseindicates how confident you wish to be (common level = .05 significance level says you are 95% sure, 5% unsure)
  61. 61Statistical Significancegoal is to determine if results are reliable . alpha level you choose indicates how confident you wish to be . the larger the sample size. larger effect size more likely to obtain significant results.
  62. 62Effect sizestrength of relationship between variables
  63. 63Effect Size providesscale of values, Generally: Small-.15 (.10-.20) Medium-.30 Large-.40 Ex: Pearson r correlation-strength of linear association between 2 variables
  64. 64Milgram's obedience experimentstudy of obedience to authority figure
  65. 65Belmont ReportEthical Principles and Guidelines for the Protection of Human Subjects of Research
  66. 663 Basic principlesBeneficence, Autonomy, Justice
  67. 67Beneficencehigh benefit/low risk ratio, not ok to use people unless there is some benefit
  68. 68Autonomyrespect for persons, able to make their own decision whether to participate or not
  69. 69Justicefairness, do not take from participants unless you give back
  70. 70what are the 3 basic principles outlined in the Belmont ReportBeneficence, Autonomy, Justice
  71. 71Risks in Psychological researchloss of confidentiality
  72. 72Deceptionexperimenter disguises true purpose of experiment
  73. 73Informed consentinformation given to participant before experiment to determine their voluntariness
  74. 74Debriefingproviding information about purpose of research after the experiment
  75. 75IRBInstitutional Review Board reviews research, composed of at least 5 individuals
  76. 76IACUCInstitutional Animal Care Use Committee
  77. 77Exempt researchno risk, archival, anonymous surveys, questionnaires, educational tests
  78. 78APA Ethics CodeAmerican Psychological Association
  79. 79Ethical principlesguidelines to protect humans as participants in research; guidelines to protect animals in research
  80. 80Fraudfabricating data, making it up
  81. 81Plagiarismcopying someone else’s comments as your own, not citing
  82. 82Single case experimental designsMeasured from baseline period (no treatment) to treatment periods to compare changes
  83. 83to control for alternative explanation in single case experimental designsReversal or withdrawal design Called an ABA design Baseline (A) ? Treatment (B) ? Baseline (A)
  84. 84Single case experimental designs is also calledsingle-subject designs
  85. 85Reversal or withdrawal design is called anABA design
  86. 86An ABA design isBaseline (A), Treatment (B), Baseline (A)
  87. 87ABA can be tested how many timesseveral
  88. 88If ethical implications are at risk then end withB (treatment), not applicable to behaviors that shouldn't or cant be reversed such as reading or drug use.
  89. 89Multiple Baseline DesignsAcross subjects, across behaviors, across settings, changes observed under multiple circumstances, determines that the manipulation caused change, rules out other events, shows that at the point treatment was introduced behavior changed.
  90. 90Across subjectsSmoking reduction. Change in behavior in each subject at different times rules out other explanations. Reinforces that IV was responsible for improvement.
  91. 91Across BehaviorsReward system applied to different behaviors in same subject. Behaviors improved shows effectiveness of IV.
  92. 92Across Settingssame behavior measured in different settings (home, work, school). IV introduced at different times in each setting
  93. 93Multiple baseline design is useful forUseful for studying the effects of a teaching practice in which two or more behaviors, people, or settings can be tracked on a single experiment. Useful for teaching skills.
  94. 94Multiple Baseline Design as a toolIn the case of academic skills this offers the teacher an important tool as it is often the case that once the skill have been learned then a return to baseline will not produce a change in performance.
  95. 95Multiple Baseline Design, what is not necessaryNot necessary to return a participant to baseline condition. Can demonstrate causal relation without having to terminate intervention.
  96. 96Multiple Baseline Design an educationUseful for teaching skills. What if a teacher wants to know the impact of fluency training for 3 students in the classroom? DV- Increased reading skills IV- Fluency training program
  97. 97True Experimental designBasic Experiments, Posttest-Only Design, Pretest-Posttest Design, Independent Groups Design, Repeated Measures Design.
  98. 98Basic Experiments2 IV’s each with at least 2 levels, Provide highest degree of internal validity
  99. 99Posttest-Only Design2 equal groups (randomly assigned), measure effect of IV on DV
  100. 100Pretest-Posttest Designtest participants before IV is introduced (to assure the 2 groups are equal, not needed if random assignment was used) and test again after manipulation
  101. 101Independent Group DesignDesign- 2 equal groups (randomly assigned), each group is given different IV’s
  102. 102Repeated Measures Design1 group, all IV’s are given to same group
  103. 103Quasi-Experimental DesignsUsed when control features of experimental designs cannot be achieved and when a true experiment is not possible. More difficult to determine cause due to lack of random assignment.
  104. 104Reasons for using a Quasi-Experimental DesignsFor example, the independent variable cannot be manipulated. Internal validity may be affected. Timing is late. Budget constraints.
  105. 105How many Quasi-experimental designs types are there6
  106. 1066 types of Quasi-Experimental DesignsOne-Group Posttest-Only , One-Group Pretest-Posttest Design, Nonequivalent Control Group Design, Nonequivalent Control Group Pretest-Posttest Design , Propensity Score Matching of Nonequivalent Treatment & Control Groups Interrupted Time Series design
  107. 107One-Group Posttest-onlyno control group
  108. 108one-group pretest-posttestthreats to internal validy
  109. 109Nonequivalent Control Group2 non equal groups
  110. 110Nonequivalent Control Group Pretest-Posttestmost useful
  111. 111Propensity Score Matching of Nonequivalent Treatment & Control Groupsstatistical calculation to match several participant variables
  112. 112Interrupted Time Series Designmeasures variable over extended period of time
  113. 113Threats to internal ValidityHistory, Maturation, Testing, Instrument decay, Regression toward mean
  114. 114Historyoutside influences (confounding events) interfering between 1st & 2nd measurements, not part of manipulation. Ex: Is change due to manipulation or event (argument) that occurred at same time?
  115. 115Maturationchange within subject during manipulation Ex: Is change due to manipulation or fatigue, hungry, wiser, experience?
  116. 116Testingchange in subjects behavior due to test itself Ex: Is change due to manipulation or has test increased their skills, taking test is too difficult?
  117. 117Instrument decayHuman or equipment fails Ex: Is change due to manipulation or is equipment not working properly, experimenter become tired, decreased attention, forgetting?
  118. 118Regression toward meanthose who measured at extremes (unusually high/low) become closer to average when measured on different days/times. Appears to be due to manipulation although it may be due to measure not being reliable.
  119. 119how many developmental designs are there3
  120. 120developmental designsCross-Sectional Method, Longitudinal Method, Sequential Method
  121. 121Cross-Sectional Methodpeople of different ages are studied and compared
  122. 122Longitudinal Methodsame group is observed over various parts in time in their life.
  123. 123Sequential Methodcombination of Cross-Sectional Method and Longitudinal Method
  124. 124Cross sectional methodsimilar to Independent Groups Design, persons of different ages measured at the same point in time. Cohort-group of people born at same time, exposed to same events, same influences, same demographics.
  125. 125Cohortgroup of people born at same time, exposed to same events, same influences, same demographics. "Cross sectional method"
  126. 126Longitudinal Methodsimilar to Repeated Measures Design, same group is observed over various pts in time in their life. To study pattern on various variables, social/emotional adjustments, personality dimensions, pet interaction
  127. 127Sequential MethodCross-sectional-study groups of certain age and then Longitudinal-study those people for partial time span and tested again, shorter time span than actual longitudinal study. Ex: study in changes in self-esteem at various ages over time
  128. 128according to the belmont report, which principle refers to the need for research to maximize benefits and minimize any possible harmful effects (risks) of participation?Beneficence
  129. 129The real purpose of the Milgram study was to studyobedience to authroity
  130. 130APA Ethics Code was developed by theAmerican Psychological Association
  131. 131The fabrication (making it up) of data is know asFraud
  132. 132Before conducting the experiment, Tony explains to the participants the purpose of the study and tells them that participation is voluntary; they can withdraw if they want and are asked to sign a paper. this process is known asInformed Consent
  133. 133which of the following is a potential risk that a participant may be concerned about during a research experimentLoss of Confidentiality
  134. 134The Committee to review animal research is theIACUC
  135. 135Autonomy refers toIndividuals are able to make a decision whether to participate or not
  136. 136Anonymous questionnaires, surveys and educational tests are all considered ____ researchexempt
  137. 137correlation coefficientit is a statistic that describes how strongly variables are related to one another.
  138. 138A correlation of 0.00 indicates thatthere is no relationship between variables
  139. 139What happens when a correlation is nearer to 1.00(plus or minus)the relationship between the variables becomes stronger
  140. 140which of the following is a measure of central tendencyMedian
  141. 141which of the following is one of the three basic ways of describing results of research investigationsComparing group percentages
  142. 142Effect size is thestrength of the relationship between variables
  143. 143which of the following is not one of the three basic ways of describing research result?regressing scores to the average
  144. 144A ____ of exam scores reveals how many students received a given score on the examfrequency distribution
  145. 145A Pearson r correlation coefficient describes the (____) and the (____) of a linear relationship between two interval scale or ratio scale variables.direction; strength
  146. 146The levels of nominal scale variables are simplydifferent categories or groups
  147. 147which of the following designs use a reversal of a manipulationABA design
  148. 148In which type of multiple-baseline design are several different behaviors of a single subject measured over timeacross behaviors
  149. 149In a single-case experimental design, the observation of a participants behavior before the manipulated treatment is referred to as abaseline period
  150. 150Which of the following methods involves studying persons of different ages at only one point in timeCross-sectional
  151. 151A developmental researcher is interested in how self-esteem develops across the lifespan. He identifes 20 children in the first grade and has them fill out a series of questionnaires. He has them fill out the same questionnaires each year untilthe longitudinal method
  152. 152while conducting a test for anxiety a boy slips off his chair causing anxiety this is an example ofhistory effects
  153. 153a researcher is conducting a study on how couples communicate. he has 5 research assistants watch videos of couples having conversations and take detailed notes. his assistants become tired and start making mistakesinstrumental decay
  154. 154the sequential method is a combination betweenlongitudinal and cross-sectional methods.the sequential method is a combination betweenthe sequential method is a combination between
  155. 155____ is defined as any time-related factor, such as fatigue, hunger, or boredom of the participant that might result in a change between the pretest and post-test measures of the dependent variable.Maturation____ is defined as any time-related factor, such as fatigue, hunger, or boredom of the participant that might result in a change between ...____ is defined as any time-related factor, such as fatigue, hunger, or boredom of the participant that might result in a change between ...

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Flashcards on Untitled, created by T J on 29/11/2018.
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