Research Design - Theories, Hypotheses And Variables Flashcards
theory
- A formal statement of relations among the observable phenomena.
- May contain hypothetical and unmeasurable constructs.
- Can give order to a body of scientific data.
Are not just merely descriptive but can be used to make testable predictions about unknown outcomes.
its a set of logically consistent statements about some phenonmenon that best summarises existing empirical knowledge of the phenomenon, organises this knowledge in the form of precise statements of relationships among variables ie laws, proposes sn explanation for then phenomenon and serves as the basis for making predictions. these predictions are then tested with research. theories in psychology differ in scope. some cover broad expanses of behaviour and are general theories. however more often a theory is focused on a specific aspect of behaviour. theories also differ in levels of precision some are strict in mathematical terms and others
described more simply as a set of logically connected statements.
an important feature of any theory is its continual evolution in light of new research. no theory is ever complete.
theories in psychology
- STM and LTM memory
- Attachment theory
- Cognitive dissonance theory
Triangle theory of love
hypothesis
- specific and way of testing a theory
- An attempt to organise certain data and specific relationships within a specific portion of a larger, more comprehensive theory.
- Generated from a theory.
- Can be precisely stated as a relationship between two measurable properties.
Can be falsifiable.
generate hypotheses from these theories
- Selective serotonin reuptake inhibitors (SSRIs) reduces depression…
- A lack of access to books in the home reduces child literacy…
- Listening to Mozart improves pupils’ learning…
Attending lectures improves grades…
null hypothesis
- What must be true if the hypothesis is not true.
- H1: SSRI treatment reduces BDI scores
- H0: SSRI treatment has no effect or increases BDI scores
- H1: Women have different IQs than men
H0: Women have the same IQs as men
directionality of hypothesis
- Directional hypothesis: one tailed
- Specifies a specific direction of effect
- Group A will have higher scores than Group B
- H1: A > B. H0: A ≤ B
- Non directional hypothesis: two tailed
- Direction of difference not specified
- Group A will have different scores than Group B
H1: A ≠ B. H0: A = B
a hypothesis leads an experiment
Experiments can provide evidence that a hypothesis is true.
* Typically, by showing the null hypothesis to be probably false.
* Experiments need variables…
What is a variable?
* Something that varies or can be varied!
* Must have at least two possible values.
* Must be observable and recordable.
Research is all about operationalized variables
operationalisation
- Each variable needs to be described clearly and unambiguously:
- A description of a construct such that another researcher can produce or measure the same thing.
- It is typically not a definition.
Eg An IQ test is not a definition of intelligence but it might be the operationalization of intelligence for the purpose of the experiment.
what do experimental psychologists do?
How does ______ affect _____?
e.g.:
How does smiling affect mood?
How does authority affect compliance?
How does inversion affect face recognition?
How does SSRIs affect depression scores?
How do hormones affect perception?
Independent variables
Dependent variables
Dependent variables
What we measure as outcomes (effects)
Dependent variable
* A response or behaviour that is measured that may be affected by changes to the independent variable.
* It needs to accurately reflect the performance being assessed.
It must show good variability over legitimate changes.
Independent variables
What we manipulate as predictors (causes)
variables must be
- Valid: That it measures what is supposed to be measured.
- How valid is recalling numbers strings a measure of cognitive function?
- The write up of a results should discuss what was measured (recalling digits) rather than what we hope we measured (cognitive function).
- Validity is a continuum not an absolute.
- Reliable: Produces consistent measurement in the same situations.
- Can be assessed by test-retest procedure
- Test of correlations between individual items
Cronbach’s Alpha - Multiple measurements are more reliable.
- Inter-rater reliability
Reliability is a continuum not an absolute. - test-retest and split-half
Becks depression inventory 21 four-option questions -
· Validity - good
· Good face validity
· Good correlation with clinical assessment through symptoms. (.66 - .76)
· BDI correlates with sense of humour loss
· BDI correlates with pessimism
· Reliability - good
· Test-retest reliability .90
· Cronbach’s Alpha .75 - .90
Over .7 is considered reliable
Hypothesis testing
- H1: A ≠ B. H0: A = B
- Tests whether we can reject the null hypothesis.
- Finds a p value. [Probability of the observed difference if the null hypothesis were true]
- p < .05 ‘accept’ the hypothesis
- Significant.
If stats are not significant (often p > .05) then we cannot reject H1 or H0.
More than one dependent variable
- With one IV and 100 different DVs (from 100 different cognitive tests) we are bound to find some ‘significant effects’.
- In fact, increasing the number of DVs means that it is harder to get a real significance effect (Bonferroni correction).
- Target p value (alpha) is divided by number of tests.
So if there are 5 tests done, p must be less than .05/5 which is .01.
significance and publishing the scientific literature
two conflicting theories - identify different predictions - construct a hypothesis that would be true for only one of the theories - operationalise the hypothesis into IVs and DVs - run the experiment to test the hypothesis
- nonsignificant - p > 0.05 - can’t distinguish between theories, don’t publish results
- significant - p < 0.05 - support one theory over the other, publish results
publication bias
significant results get published
non - significant ones do not
file-drawer effect
Meta- analysis
- Select all studies that looked at a particular topic.
- Published and unpublished
- Code the size of the effect found and the confidence of rejecting null.
Find the average effect and the confidence of rejecting the null given all of the data.
you find a topic, select the studies and assess overall effect
summary
- Theories lead to hypotheses which lead to experiments.
- Experiments need operationalised independent and dependent variables.
- Variables should be valid and reliable.
Other terms: Significance; Publication bias; Meta Analysis.
construct
a hypothetical factor that is not observed directly , its existence is inferred from certain behaviours and assumed to follow from certain circumstances.
the relationship between theory and research
the move from theory to research and back begins with the logical process of deduction, reasoning from a set of general statements towards the prediction of a specific event. deduction takes the form of the scientist reasoning that if the theory is correct then a specific reasearch outcome can be predicted and should occur with some probability greater than chance. The prediction about outcomes that is derived this way is called a hypothesis, which in general can be considered a reasonable prediction about a research result that should occur under certain circumstances. Hypotheses lead to the design of a study, which produces results as predicted or fails to produce them. In the former case, the theory is supported, and in the latter case it is not. If the theory is supported by a large number of research outcomes, a researcher’s confidence is high that the theory is a good one; to put it another way, we could say that inductive support for the theory increases when individual studies keep producing the results as predicted from the theory. Induction is the logical process of reasoning from specific events (the results of individual research studies) to the general (the theory).
theories being called into question
research project don’t always come out as expected. the study might not be a good test of hypothesis eg operational definitions of the variables might not be the best ones, it might have methodological flaws or it might fail for a reason that is never discovered. also measurements of psychological phenomena are imperfect so a failed experiment could be the result of measurement error. any study that fails to come out as it hopes it rarely calls a theory into question. if results repeatedly fail to support a theory however especially if they are conducted in different laboratories, confidence in the theory begins to lessen and it may be discarded or more likely altered.
psychologists don’t use the words prove and disprove as prove implies 100% truth and scientists can never be 100% sure their results are true.
theories
they may be supported and may be discarded but what happens most frequently is that they evolve as research accumulates and as challenges to the theory emerge. this happened in the case of cognitive dissonance.
attributes of good theories
- productivity - good theories advance knowledge by generating a great deal of research, an attribute that can be applied to dissonance theory.
- falsification
- parsimony