TOPIC 2: PSYCHOLOGY AND RESEARCH Flashcards
THEORY, HYPOTHESIS, AND RESEARCH
goal is to create a useful theory: an organized set of principles.
- helps simplify facts about an aspect of the world.
- serves as coherent explanation.
- should allow testable predictions
scientific theories
are well substantiated, well-supported, well documented explanations for our observations.
theories are not absolute, they are open to change if better evidence is found.
scientific laws
can describe, but only theories can explain.
the scientific method
- ask questions, make observations, describe the phenomenon
- develop an explanation (theory)
- generate a hypothesis: testable prediction derived from a theory
- design research study
- collect relevant information
6 analyze and interpret the info; compare results with hypothesis
- solicit peer reviews and report findings.
what is a hypothesis
a prediction which is testable and is originally derived from a theory .
case study
an in-depth study of an individual, group, m or event by observation. in person meeting, structured psychological tests, recording of physiological activity, on performance on certain tasks, or from archival records.
pros and cons of case study
PROS:
-can be revealing and detailed
CONS:
-cannot determine cause of behaviour.
-atypical subject precludes generalization.
survey
peoples self-reports to a questionnaire or interview
pros and cons to surveys
PROS :
- reveals patterns in large numbers of people.
- easy to administer and score
CONS:
- effects of extremes are mediated
- demand characteristic : response can be influence by the questions itself
(how wording effects)
naturalistic observation
recording behaviour in organisms natural environment
pros and cons to naturalistic observations
PROS:
- subjects unaffected by presence of researches
- describes behaviour in natural contexts; wide applicability
CONS:
- cannot determine cause of behaviour
- loss of experimental control
correlation
two different variables are measured form individuals, and statistically analyzed for a relationship
positive correlation
direct relationship between two variables, when one is effected so does the other.
negative correlation
inverse relationship between two variables, when one is effected a certain way, the other variables is affected I the opposite direction.
zero correlation
no relationship, the variables have no effect on on one another,
pros and cons for correlation
PROS:
- may reveal relationship between variables
- can guide future by generating hypotheses
CONS:
- correlation does not mean that one variable causes the other (correlation does not imply causation)
components of an experimentation
- indépendant variable
- dependant variable
- experimental group
- control group
independent variable
factor of interest manipulated by experimentor
dependant variable
factor measured by experimenter (“effect”)
- all extraneous factors are controlled or held constant
experimental group
receive manipulated level of independent variable
control group
receive normal level independent variable
pros and cons to experimentation
PROS:
- allows cause and effect conclusions
CONS:
- unexpected variables
- some variables cannot be manipulated
why are experiments conducted ??
- we learn cause and effect explanations
- thus, we control factors in an experiment
why are experiments valid ??
- experiments provide support for a theory
- theory explains universe principles of behaviour
- these occur in a lab, as well as in real life.
hindsight bias
- events aren’t obvious beforehand, but they seem very predictable after they occur.
over confindence
false image of how confidence means correctness when it doesn’t.
confirmation bias
seeking evidence confirming your beliefs–even to the exclusion of contradictory information
SOLUTION: replication of observation by others
sampling bias
sample is not representative of the population.
SOLUTION: random selection.
experimenter bias
researcher expectations influence change in dependant variable
SOLUTION: double-blind procedure, neither participant nor experimenter knows which treatment the participant is receiving.
MODE
most common score, typically the highest score.
MEDIAN
model score (50th percentile)
MEAN
arithmetic average ( sum of scores divided by the numbers obscures)
RANGE
difference between the highest score and lowest score
standard deviation
average distance of the scores from the mean; indicates spread of scores around the mean
normal curve
regular pattern of variability of human characteristics In the population
correlation coefficient
- index of degree and directions of relationship between two variables
- positive / negative sign indicates relationship
- (0.00-1.00) indicates strength of relationship
inferential statistics
allows interpretation of sample data; generalization
statistically significant
if the probability is unlikely
<0.05
Null hypothesis (H0)
in an experiment, the null hypothesis typically states that there is no difference between the experimental groups and control groups
complications of inferential statistics
- larger samples are better (closer match to population)
- less variability is preferable ( can be more confident in stable results)
- there is no such thing as an average person.
