Developing hypothesis day 3

• -idea-generating phase
• -problem-definition phase
• -procedures-design phase
• -observation phase
• -data-analysis phase
• -interpretation phase
• -communication phase

• -ideas come from many places
• *own interests
• * research and theories of others

• -nurture and develop ideas
• *be curious
• *read what others think and what they have done

-ideas are formalized into testable research questions

• -need to be more critical in this phase
• *how does idea compare to existing theory and research?
• *is idea logical?
• *what does idea predict?

-translate ideas into testable hypothesis

-variables must be defined and procedures selected

-each step should be planned

-ethical issues must be considered

- "doing the research"

• - central acitivty of research
• *early=planning, later= interpret findings

-data gathered here will answer questions you raised early

-takes up most time

-cannot make major adjustments

-evaluate the data, usually using stats procedures

• -stat procedures are selected in the procedures-design phase
• *many types of stats are available
• **depends on question and nature of data

• -making sense out of results
• *interpret stat findings
• *how does finding relate to research question?
• *any alternative interpretations of data?
• **find ways to falsify the alt. data

• - try to published work
• *allows others to...
• judge
• build on it
• challenge

-conference presentations

-publishing in journals or books

-personal interests

-unanswered questions from previous research

-applied questions

-theory testing

-explain new phenomenon

- test contrasting

-develop/expand existing theory

-inductive thinking

-deductive thinking

-start with observation> develop hypothesis

-typically used when we do not know much of phenomena

-need to be careful and not miss important factor

-start with theory/hypothesis> collect observations

-used when we have defined theories

-allows for stronger conclusions

-simplified framework for explaining complex phenomena

• -scientific theory must be..
• *testable
• *falsifable

-theoreis organize data and help predict new data

-they are generative

-they make precise predictions

-they can be ambigously tested (falsifiable)

-they are simple (parsimonious

-has a "good track record"

is a statement that specifies in concrete terms the causual relationship between conceptual variables

-logical

-testable/falsifiable

• -concrete
• *variables can be operationally defined
• *variables are quantifiable (numbers)

• measured by researcher and assumed to cause change in another variable
• *does not mean causation
• **correlational

• any variable that causes change in the dependent variable
• *Z in X n Y equation

ensures that inconsistent observations will be recorded

ensures that inconsistent observations will be counted against the theory

theory is revised in light of tests and hopefully becoames accurate