2973213
Descripción
Fichas por sarah_walatka, actualizado hace más de 1 año
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Creado por sarah_walatka
hace más de 9 años
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| Pregunta | Respuesta |
| most popular data collection technique | surveys |
| collect data at 2 or more time periods | longitudinal research |
| data collected at one point in time, across a population | cross-sectional |
| cohort effect | your life experiences will greatly affect how you view things (you are not the same as your parents were at your age) |
| pros and cons of cross sectional research | (+): quick, easy, cheap (-): less telling of the "true nature" of a population; only shows what occurred at a single point in time |
| pros and cons of longitudinal research | (+): provides a more accurate picture of a population (-): expensive, difficulty tracking subjects |
| research that uses quantitative terms to describe the degree to which variables are related | correlational research |
| a comparison of the amount of variability between two variables | correlational reseach |
| small r means what? | large variance |
| do you want small or large variance? | small variance; indicates a pattern means the data is more compact and similar |
| the correlation coefficient | r |
| r always falls within what range? | +/- 1 |
| common variance shared between 2 variables | r^2 |
| how much error you will take | significance |
| what kind of studies use correlations to gain insight into factors for future studies? | relationship studies |
| what kinds of studies assess complex issues with a variety of factors using correlations (what variables are related to each other)? | relationship studies |
| what are the benefits of relationship studies? | cheaper and faster than experimental studies |
| what kind of studies have two variables that are highly related and can be used to make predictions (example?) | prediction studies ex: can GRE predict grad school success |
| do prediction studies have IV and DVs? are they scientific? measurement based? | no IV/DV; just used of variables as predictors highly scientific and measurement based |
| what is the difference between experimental and causal-comparative research? | C-C does not have manipulation of variables |
| what kind of study has observation of differences between groups to see why conditions exist or why something happened? ...describes conditions which already exist?... attempts to determine causes? | C-C |
| what kind of research starts with the effect, then investigates the cause? (retrospective approach) | C-C |
| what are the limitations of C-C research? | - the IV has occurred - interpreting results must be done carefully - cause and effect can never really be known unless we do experimental (think butterfly effect) |
| how do you conduct C-C research? | 1. select 2 groups differing on one IV (experimental and control or comparison groups) 2. compare then on some DV |
| how do you randomize the assignment of control and experimental groups in C-C research? | you can't randomize, so try and make two groups similar pair-wise matching of subjects |
| which kind of research tests hypotheses that concern cause and effect? | experimental research |
| in the following hypothesis, what is the IV?DV? experimental group? TINSD in the blood triglycerides of those consuming a low carbohydrate diet versus those who are not consuming a low carbohydrate diet | IV: diet DV: blood TG Experimental group: low CHO diet |
| what are threats to experimental validity | - any uncontrolled, extraneous variables - if the results seen are due to a reason other than the IV |
| internal validity vs. external validity | internal: conditions observed are a result of the IV, within the study external: results are generalizable outside of the study |
| an event occurred which is not part of the study (ex: Sept 11) threat to internal or external validity? what is it called? | history effect internal validity |
| physical or mental changes of subjects (ex: puberty) - threat to internal or external validity? what is it called? | maturation effect internal validity |
| pretest sensitization - potential of a treatment's effect on subjects - threat to internal or external validity? what is it called? | testing effect internal validity |
| invalid assessment tool - threat to internal or external validity? what is it called? | instrumentation effect internal validity |
| subjects selected on their extreme scores - threat to internal or external validity? what is it called? | statistical regression effect internal validity |
| loss of subjects - threat to internal or external validity? what is it called? | attrition effect (mortality) internal validity |
| 6 threats to internal validity - name 2 | - history - maturation - testing - instrumentation - statistical regression - mortality/attrition |
| subjects respond differently d/t pretest given - threat to internal or external validity? what is it called? | pre-rest treatment interactions external validity |
| same subjects get more than 1 treatment - threat to internal or external validity? what is it called? | multiple treatment interference external validity |
| differential selection of subjects - threat to internal or external validity? what is it called? | selection treatment interaction external validity |
| problems with subject selection, variable definition, instruments, etc - threat to internal or external validity? what is it called? | specificity of variables external validity |
| biases, personal impact, influence subjects' behavior, etc. - threat to internal or external validity? what is it called? | experimenter effects external validity |
| number of factors used to control the study - threat to internal or external validity? what is it called? | reactive arrangements external validity |
| 6 threats to external validity - name 2 | - pre-rest treatment interactions - multiple treatment interference - selection treatment interaction - specificity of variables - experimenter effects - reactive arrangements |
| degree to which a test measures an intended area | content validity |
| 2 kinds of content validity | item validity: do questions/items represent measurement in the content area sampling validity: are the questions/items a good representation of the content area (do they cover all bases) |
| does the test appear to do what it wishes | face validity (non-scientific concept) |
| degree to which a test measures a desired observable trait | construct validity (measures obscure concepts) |
| degree to which a test is related to another test | concurrent validity |
| degree to which a test can predict how a subject will do in the future | predictive validity |
| 7 types of validity - name 2 | content item sampling face construct concurrent predictive |
| degree to which scores are consistent over time | test-retest reliability |
| two tests that are identical except the actual items included (same structure, # of items, content is different) | equivalent forms reliability |
| make comparisons on two halves of a test used to measure internal consistency, appropriate when a test is long | split-half reliability |
| determines how all items on a test relate to all other items on the total test (Kuder-Richardson formula) | rationale equivalence reliability |
| important for subjective questions and when more than one person is scoring the test | scorer/rater reliability |
| 5 types of reliability - name 2 | test-retest equivalent forms split-half rationale equivalence scorer/rater |
| format considerations for questionnaire construction | eye appeal logical arrangement of items off-set or underling important words number consecutively put name of who form should be returned to at beginning include brief, clear instructions avoid words "questionnaire" or "checklist" |
| problems with survey questions | o Double barreled o Response categories don’t align, don’t make sense, don’t match the questions o Badly worded sentences |
| condition that exists in quantitative research when 2 or more variables measure the same things | Multicollinearity - Want to be careful you don’t have this, but If you have this scale them together |
| narrative and visual (non-numerical) data | descriptive data (qualitative research) |
| research usually done over a period of time, with intensive data collection in a naturalistic setting, not trying to control, looks at bigger picture (feeling, beliefs, meanings) | qualitative research |
| T/F: Generalizability is not important in qualitative research | true |
| what kind of sampling is often used in qualitative research? | purposive sampling (since it is difficult to recruit) |
| main data collection method for qualitative research | interviews |
| what are some things to consider when interviewing subjects for qualitative research | - have a list of guiding questions related to study goals - allow questions to evolve between interviews - tape record as much as possible - make a paper trail |
| "How education changed through history" is an example topic for what kind of qualitative research? | historical research |
| what kind of research involves watching participants | observational |
| non-participant observation - what is it? what are benefits? | observer is not directly involved in the situation being observed - less intrusive, less likely for researcher to become emotionally involved |
| participant-based observation - what is it? pros and cons? | observer becomes participant in the situation being observed (+): may get data that was otherwise impossible to get if not involved (- ): more intrusive, more likely for researcher to become emotionally involved |
| research where participants are observed in their natural setting | naturalistic observation |
| research where participants role-play in a fake setting | simulation |
| study of how different humans experience the world around them; involves photos and written accounts about experiences and meanings attached | narrative research |
| study of cultural patterns and perspectives in a natural setting... what is it called? what is the goal? | ethnographic research goal: to understand a group and their culture of people over time |
| research that focuses on one unit; to study phenomena that are not easily studied by other research methods | case study research |
| goals in data analysis/interpretation of qualitative research? | - identify themes/patterns that keep arising - look for validity |
| degree to which observations accurately reflect what was observed | validity |
| what method is used to ensure validity in qualitative research | triangulation |
| multiple methods used to verify the truth of what is being observed | triangulation (use interviews, observations, records, documents) aka: "chunking" the data |
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