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experimental methodology
a systematic approach that’s designed to be carried out under controlled conditions, w/ the goal being to test the hypothesis & establish a relationship between independent variable & dependent variable
non-experimental methodology
used in research where a controlled experiment is not possible or ethical
only DESCRIBE behavior, they cannot explain behavior
CANNOT be used to establish a causal relationship between independent & dependent variables
non-experimental methodologies
case studies
correlational studies
meta analysis
naturalistic observation
case study
examines an individual, group of people, event, or situation to provide detailed info & insight into the topic of interest
downside: the risk of being impacted by the hawkthorne effect - when the subject of a study alters their behavior due to them being aware they’re being observed
correlational studies
allows researchers to gain insight into the relationship between two variables & can help determine the strength of the relationship between the variables
downside: they do NOT show cause & effect, it does NOT gain insight about causation
which type of methology gains insight into causation?
through a controlled experiment
negative of non-experimental methods
the third variable problem - always at risk for an outside variable (confounding variable) impacting the study
meta analysis
a statistical technique that combines the results of multiple studies on the same topic to reach a conclusion
naturalistic observation
when the researcher observes individuals in a real world setting, the goal being to try & gather authentic data, by observing people in their environments
downside: depending on how long the observations are taking place, the observer might lack the proper context for what they’re observing.
ex. if an observer spends only a short time in a public park, they might see a group of kids playing & assume they’re always this energetic.
however, without understanding the broader context— like the kids’ usual behavior, the influence of a special event that day, or prior interactions —> they might draw incorrect conclusions about their typical behavior, as this lack of context can lead to misinterpretations & oversimplifications of complex social dynamics.
first step to designing a study
state the hypothesis - a specific, testable prediction about the relationship between two or more variables. the hypothesis must be falsifiable (can be proven wrong).
after the hypothesis is set, we must identify the operational definitions.
operational definitions outline the exact procedures used in the study & outlines how the variables are measured or manipulated in the study.
having clear operational definitions allows for other researchers to replicate the study under the exact same conditions.
ex. if you studied the effects of sleep on academic performance, your hypothesis can be “students who get more sleep the night before the exam will score higher on the exam compared to students who get less sleep.”
operational definitions:
more sleep = at least 8 hours of continuous sleep the night before the exam, which we could have reported by having students track their sleep w/ apple watches. less sleep = fewer than 8 hours of continuous sleep before the exam.
the exam= the ap psychology national exam
we can measure performance by using the scale of 1-5 as reported by college board.
difference between the independent & dependent variable?
independent variable - what is being manipulated or controlled by the researcher, the CAUSE
dependent variable - the outcome that’s measured in the study, the EFFECT
<3
hypothesis = students who use the ultimate review packet will score higher on the ap psychology exam compared to students who don’t use the packet.
independent variable = the ultimate review packet
dependent variable = the exam score
confounding variables = students’ study habits, amount of stress, overall health
confounding variables
factors other than the independent variable that could impact the dependent variable, that an experimenter was not able to remove from an experiment or study.
ex. students’ study habits, amount of stress, overall health as these could all impact the students’ performance on the exam regardless of the amount of sleep they get.
the more control there is in the study, the less confounding variables there will be.
however, in the real world, this is not always possible: the more you try to control an experiment, the more you risk creating an inauthentic environment —> could create new confounding variables as participants might change their behaviors
what’s the difference between population & sample?
population - the entire group that the research is studying
sample - the selected group of individuals in a population that are selected to represent the population in the study.
ex. if you conduct a study on students at your school, the population would be the entire student body. the sample would be the students that you selected out of the student body
when trying to select individuals from a population to create a sample group, researchers can use random sampling - meaning each individual in a population has an equal chance of participating in the study.
researchers can also use stratified sampling which is when the population is divided into different subcategories & a random sample is taken from each subcategory.
whenever researchers are creating a sample the goal is always to create a representative sample - meaning the sample group in the study represents all the different people in the population.
one issue that comes up when picking a sample group is sampling bias - meaning the sample group that’s representing the population in the study does NOT represent the entire population accurately
occurs when the process of picking the sample group is flawed. ex. if certain members of a population have a higher chance of being selected compared to other people in the population. one reason this can happen is by convenience sampling - when individuals are selected to participate in a study based on their availability. it’s an easy way to get a sample group but it can often introduce sampling bias into the study, limiting the generalisability of the results. generalisability - the extent to which the findings of a study can be applied to the larger population.
once a sample’s chosen, the researcher will need to set the experimental & control group.
experimental - the group in an experiment receiving the independent variable
control group - gets a placebo
placebo - something that’s as close to the independent variable as possible, but is missing a key component of the independent variable. this way the placebo does not impact the participants but also doesn’t let the participants know that
concept application - psychology perspectives
BIOLOGICAL (NEUROSCIENCE) PERSPECTIVE - our feelings, behaviors, & thinking is influenced by our brain: genetics, body chemistry (hormones, neurotransmitters), brain's structure.
EVOLUTIONARY PERSPECTIVE - our feelings, behaviors, & thinking exists because they are inherited. they serve an evolutionary purpose as they aid in survival & reproduction. key concept: charles darwin's survival of the fittest, natural selection.
PSYCHODYNAMIC PERSPECTIVE - our feelings, behaviors, & thinking is influenced by our unconscious mind. early childhood experiences, personal relationships explain our behavior. we repress many past experiences & negative feelings (ex. trauma), not consciously knowing it but it stays in our unconscious.
BEHAVIORAL PERSPECTIVE - behavioral processes exist because we're conditioned to act that way. it focuses on observable, measurable behaviors INTERNAL FEELINGS & EXPERIENCES ASIDE & how behaviors are learned & reinforced (rewarded or punished). key concepts: positive reinforcement, negative reinforcement & positive punishment, negative punishment. classical & operant conditioning.
COGNITIVE PERSPECTIVE: behavioral processes is influenced by our thoughts & mental processes: memory, thinking, problem-solving, language, & decision-making. it focuses on how we perceive the world. key concept: cognitive therapy tries to change the way you think.
SOCIAL-CULTURAL PERSPECTIVE: behavioral processes, feelings, & thinking is influenced by your culture, religion, ethnicity, gender, community, & even income level.
HUMANISTIC PERSPECTIVE:
BIOPSYCHOSOCIAL PERSPECTIVE