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Research Methods Comps

Laura Hill Englisch 72 Karten

Karten in diesem Stapel (72)

  1. 1Independent Variablevariable that is being manipulated in an experiment in order to observe the effect on a dependent variable
  2. 2Dependent VaraibleIn an experimental design, the independent variable is the variable that is manipulated by the experimenter to determine its relationship to an observed phenomenon, called the dependent variable. More generally, the independent variable is the “cause,” while dependent variable is the “effect” of the independent variable.
  3. 3Non-experimental StudyObserve the Independent Variable (IV) as it naturally occurs. DO NOT physically manipulate the IV
  4. 4Confounding VariableOther explanations (besides IV) that may influence the outcome (DV). Extraneous Variables.
  5. 5Hypothesis: DirectionalPredict which group will be higher or have more of something
  6. 6Hypothesis: Non-directionalNo predicted direction. Used when wanting to explore topic but unable to predict outcome.
  7. 7Type of Research: Non-ExperimentalObserve subjects and describe as they naturally exist. 5 types of non-experimental studies (Descriptive, Historical, Correlation, Qualitative, Casual Comparative)
  8. 8Non-Experimental: DescriptiveSurvey Research. Describe characteristics of a phenomenon. Using: Questionnaire, face to face interviews.
  9. 9Non-Experimental: HistroicalExamine information in order to understand the past
  10. 10Non-Experimental: CorrelationStudy relationship between quantitative variables
  11. 11Non-Experimental: QualitaiveGoal is to understand a phenomenon in context. Gather open ended interview data to ID common themes.
  12. 12Non-Experimental: Casual ComparativeUsed when experiments are not possible due to ethics.
  13. 13Types of Research: ExperimentalExplore cause and effect relationship. Two types. Assign treatment and observe change in outcome variable (DV)
  14. 14Experimental: True ExperimentalRandomly assigned participant groups. Control/ Comparison Group. Randomly assigned treatment to groups.
  15. 15Experimental: Quasi-ExperimentalNaturally occurring groups (gender, race)
  16. 16Ecological FallacyDrawing conclusions about individuals solely from observations of the group.
  17. 17ReductionismStrict limitation of kinds of concepts to be considered relevant to the phenomenon to study.
  18. 18Criteria for CausalityVariables must be correlated.
    Cause precedes the effect in time. Variables are non spurious.
  19. 19Non-Experimental ResearchDescribe relationship between variables.
    Cannot test cause-and-effect relationships.
    4 types.
  20. 20Primary SourcesA primary source provides direct or firsthand evidence about an event, object, person, or work of art. Primary sources include historical and legal documents, eyewitness accounts, results of experiments, statistical data, pieces of creative writing, audio and video recordings, speeches, and art objects.
  21. 21Secondary SourcesSecondary sources describe, discuss, interpret, comment upon, analyze, evaluate, summarize, and process primary sources. Secondary source materials can be articles in newspapers or popular magazines, book or movie reviews, or articles found in scholarly journals that discuss or evaluate someone else's original research.
  22. 22Non-Experimental Research: CorrelationalAsks what several events have in common
    Asks whether knowing one event can allow precision of another
    Does NOT imply causation
  23. 23Non-Experimental Research: QualitativeExamines behavior in natural social, cultural, and political contexts.
    Results in non-quantitative data.
  24. 24Experimental ResearchTries to discover casual relationship. Type types
  25. 25Experimental Research: TrueParticipants assigned to groups, treatment variable is controlled by researcher, control of potential causes of behavior.
  26. 26Experimental Research: Quasi-ExperimentalParticipants are preassigned to groups, useful when researcher cannot manipulate variables
  27. 27Time Dimension: LongitudinalFollows a group of people
    Measures at several points
    Look at changes over time
    Pro: Extensive details. Con: Expensive
  28. 28Time Dimension: Cross-SectionalMore than 1 group
    Measure at ONE point
    Look at differences
    Pro: Inexpensive
    Con: Group comparison is limited
  29. 29LongitudinalTrend Study: Purpose-study changes within general population. Repeated cross-sectional design, data collected at 2 or more time points, dif samples of same population
  30. 30CohortStudy same cohort over time
  31. 31PanelData are collected from same set of people at several points in time.
  32. 32Sampling: PopulationGroup of individuals researchers are interested in for a study
  33. 33Sampling: SampleRepresentative subset of population
  34. 34SamplingAggregate characteristics of sample approx. same aggregate characteristic in population.
  35. 35ProbabilityLikelihood of any member of the population being selected is known. Need to be able to ID each member of the population.
  36. 36Probability: Random SelectionEach member of the population has EQUAL chances of being included
    *Gold standard in quantitative research*
  37. 37Non probabilityLikelihood of member of the population being selected is unknown.
  38. 38Non probability: Non random selectionAny kind of sampling that gives some individuals GREATER chances of being selected in the study than others.
  39. 39Probability Sampling: Simple Random SamplingEach member of the population has an equal and independent chance of being chosen
    Can be generated by: drawing slips, table of random numbers, random number generator
  40. 40Probability Sampling: Systematic SamplingEvery "n" person is selected
    Sampling Internal (n)= pop size/sample size
  41. 41Probability Sampling: Stratified SamplingGoal is to select a sample that is representative of the population. If people in population differ systematically along some characteristics and they relate to factors being studied use stratified sampling
    Purpose: Ensure different subgroups are represented in correct proportions
  42. 42Probability Sampling: Cluster SamplingInstead of drawing individuals, draw groups at random.
    2 steps: select clusters at random, select respondents within each of the selected clusters at random
  43. 43Secondary AnalysisA form of research in which the data collected and processed by one researcher are reanalyzed by another
  44. 444 levels of measurementCategorical (nominal): such as gender, religion, race
    Ordinal: Order of rank (SES, grade level)
    Interval: Number indicate value of a variable, NO absolute zero (temperature)
    Ratio: Number indicate values of a variable, DO HAVE absolute variable (height, income)
  45. 45Continuous VariablesValues can range along a continuum. Height, Income. Interval and Ratio
  46. 46Discrete VariableValues are defined by category boundaries. Mutually exclusive categories. Gender, categorical
  47. 47Construct ValidityA collection of related behaviors that are associated in a meaningful way.
  48. 48ReliabilityWhether the measurement will produce the same results each time it is administered
    Reliability is necessary for validity but not
  49. 49What alpha for high reliability?Want alpha of greater or equal to .7. Talking about alpha is .2, point out this study is using an instrument with low reliability.
  50. 50Internal ValidityLinking power; refers to whether the evidence of a study supports the existence of a relationship between its variables
  51. 51External ValidityRelated to the generalizability of the research
    Can the results be generalized beyond the study circumstance
  52. 52Sampling ErrorsRefers to a lack of representativeness and difference between the characteristic of a sample and characteristics of a population
  53. 53Inferential StatisticsHelp us make inferences from samples to the populations from which the samples were drawn
    T-Test, Chi-Square, ANOVA
  54. 54Null HypothesisStates that there is no relationship between the independent and dependent variable
    H0 NO SIGNIFICANT DIFFERENCE
  55. 55StatisticsValues from studies on which samples are examined
  56. 56ParameterValues from all members of a population (values from a census)
  57. 57Samples yield...?Statistics
  58. 58Populations yields.....?Parameters
  59. 59T-Test and ANOVAComparing mean groups
    example: compare depression scores between males and females
  60. 60Chi-Square (Chi TEA LATTE LOL)The Chi Square statistic is commonly used for testing relationships between categorical variables.
    Categorical (nominal): such as gender, religion, race
    Females are more likely to vote for democrats
  61. 61Random SelectionSelecting cases by chance to represent the population
    Always desirable, but not feasible
  62. 62Random AssignmentRandomly assigning cases to multiple conditions
    Randomly assign treatment to groups
  63. 63Threats to Internal ValidityHistory: uncontrolled outside influences on participants between pretest and post-test
    Maturation: Subject mature, naturally grows
    Instrumentation: Changes in the test between pretest and posttest
    Testing
    Statistical Regression
    Selection
    Morality
    Interactions between above factors
  64. 64Factors Influencing External ValiditySelection Bias
    Reactive effect of experimental arrangments (experimental setting is different from the natural setting, observed effect may not generalize)
    Reactive effect of testing (pretest may influence post-test)
    Multiple treatment interface (same subjects are given more than 1 treatment)
  65. 65Qualitative Research Looks To...Discover Something
    Use inductive logic and reasoning
    Unstructured
    Observed naturally
    No treatment
    Use natural case studies
  66. 66Mixed Methods ResearchProcedure for collecting, analyzing, and mixing both quantitative and qualitative data in a single study to provide a better understanding of research problems than either approach alone
  67. 67Unit of AnalysisThe WHAT and WHOM being studied
    Individuals, families, communities
  68. 68ANOVACategorical predictors and interval outcomes
    Influences of several categorical predictors and interval level outcome variables
    Ex: Influence of gender and religion on depression -or- the influence of family structure and religion on depression
  69. 69Sample Size30 is the magic number. Want to look at differences in gender need 30 males AND 30 females
    Increasing sample size increases precision
  70. 70Sampling ErrorsRefers to the lack of representativeness
    As sample size increases-> sampling error decreases
  71. 71Sampling DistributionThe distribution of means repeated random samples from the same population
  72. 72BreathBREATH!!!

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Karteikarten am Research Methods Comps, erstellt von Laura Hill am 25/09/2019.
Erstellt von
Laura Hill
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