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Created by sarah_walatka
over 11 years ago
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| Question | Answer |
| steps in a research plan | 1. select and define the problem 2. execute research procedures (collect data) 3. analyze data 4. draw and state conclusions |
| the scientific method | 1. identification and definition the problem 2. formation of hypotheses 3. collecting data 4. organizing and analyzing data 5. rejecting/accepting the hypotheses 6. conclusion |
| chapters in a thesis | 1. intro and statement of the problem (+ assumptions and limitations) 2. review of lit 3. methodology 4. results 5. summary, conclusions, recommendations |
| ch. 1 of a thesis | intro, statement of problem, purpose statement, objectives, research questions, hypotheses, definitions of terms, limitations, assumptions |
| ch. 2 of thesis | review of lit, summary, headings that relate to purpose statement |
| ch. 3 of thesis | methodology, instrumentation, sample selection, procedure, explanation of coding, statistical tests |
| ch. 4 of thesis | results, tables |
| ch. 5 of thesis | summary, conclusion, discussion, recommendations |
| what is a hypothesis? | a tentative explanation for certain behavior, phenomena, or events that have occurred or will occur |
| characteristics of a good hypothesis | based on sound rational clear specific testable brief |
| types of hypotheses | null, directional, and non-directional null: predicts no difference directional: predicts a direction non-directional: predicts no direction, assumes a difference |
| formula to write a null hypothesis | There is no significant difference in DV by IV |
| formula of a non-directional hypothesis | There is a significant difference in DV by IV |
| formula of a directional hypothesis | IV (a) is higher/lower on DV than IV (b) |
| how is research used? | to investigate on a continuum of basic to applied --> R&D, theory development, action research (for a localized setting), evaluation research |
| qualitative vs. quantitative reseach | qualitative: induction (specific to general); generates Ho's; process-oriented; biases quantitative: deduction (general to specific); tests Ho's; outcome-oriented; objective |
| historical research | qualitative studying, understanding, and explaining past events not common from primary (people) or secondary (media) source data |
| pure qualitative research | investigates how people feel, believe, and what are the meanings they attach to things contextual study uses many methods lots of data |
| descriptive research | simplest form of quantitative data reporting on how things are, attitudes, opinions (snapshot in time) observational through surveys, polling |
| correlational research | determines relationships between 2 or more variables does not prove causation |
| experimental research | looks at cause/effect relationships, group comparisons highest level DV = IV + IV manipulation of IV and randomization of subjects to ascertain true cause |
| IV | cause or treatment |
| DV | effect or outcome |
| causal comparative research | quantitative method IV is not manipulated |
| meta analysis | contrast and combine results of different studies |
| quasi-experimental | experimental with out random assignment or IV is not really manipulated |
| is there a cause and effect: experimental, descriptive, causal-comparative, correlational | experimental causal comparative |
| IV manipulated: experimental, descriptive, causal-comparative, correlational | experimental |
| relationship prediction: experimental, descriptive, causal-comparative, correlational | correlational |
| why legislation around research? | to protect subjects; make sure they give consent and are aware of risks (d/t WWII Nazi experiments, Tuskegee Syphilis study, Milgram Obedience study) |
| FERPA | Family Education Rights and Privacy Act (1974) provides confidentiality of student records |
| National research act | 1974 human subjects review committee subjects must be informed and give consent study must be approved |
| HIPAA | Health Information Portability and Accountability Act protection of medical information |
| a researchable problem should... | be measurable be theoretical/practical in significance lead to the development of good research questions or hypotheses |
| statement of the problem | the "so what" leads into the purpose of the thesis |
| purpose statement | 1-2 sentence statement that is the basis of your study includes: variables of interest, subjects to study, hypotheses (quantitative) /research questions (qualitative) /objectives (DP) |
| why is a lit review important? | can help you discover what has been done, results of previous attempts, what to expect, good measures/methodology, mistakes to be avoided |
| what is a population | the group of interest in your study to whom your results relate your target or group of interest |
| how do you select your sample? | ID your population determine the necessary sample size choose sample method --> a good sample should be representative of your population and reasonable with respect to resources |
| random sampling | all people in the population have the same chance of entering your sample does not guarantee representation |
| stratified sampling | identification of subgroups as they exist in the population; sample mimics the strata of the pop. (ex: political groups in CA) |
| cluster sampling | groups within a population are randomly selected convenient, efficient may randomly pick an unrepresentative sample |
| systematic sampling | take every Xth person from a group can be considered random is the list is randomly ordered |
| accidental/haphazard sampling | aka convenience sampling use volunteers and whoever is available may affect data; list as a limitation |
| quota sampling | just finding people to fill quote ex: 100 blacks, 100 whites, 100 hispanics used in large group surveys when you do not care about representing the pop often used in qualitative methods |
| purposive sampling | aka judgement sampling using clear criteria to find out about a specific pop. ex: veteran men in final stage of AIDS not generalizable |
| benefits of a large sample size | more generalizable easier to do statistical crunching |
| sampling error vs. bias | sampling error: beyond the control of the researcher sampling bias: error from the researcher |
| which sampling techniques do not allow for equal chance to enter sample? | non-probability sampling convenience sampling quota sampling purposive sampling |
| generalizability is important in what kind of research? | very important in quantitative research, not as important in qualitative research |
| what are scales? | groups of questions or surveys with subscales |
| nominal scales | categorical lowest level (no ability to number crunch) classify into true categories or false categories |
| ordinal scales | ranking ex: test scores, ht, GPA (-): diff b/w #s may not be consistent (ex: diamond carats) |
| interval scales | combination of ordinal and nominal no true zero; max and min scores are arbitrary, used to measure performance not often used |
| ratio scales | has a true zero ex: ht, wt, time, distance, speed highest level; most precise generalizations possible |
| likert scales | strongly agree, agree, neutral, disagree, strongly disagree most common scale |
| semantic differential | give a quantitative rating ex: on a scale of 1-10... |
| Thurstone scales | forced choice select from an option of statements |
| Guttman scales | agree or disagree with each statement answers become dichotomous (add together for a final score) |
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