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8/13/2019 AP Psych Prep 2 (Part I) - Research and Experimental Method
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Part I: Psychological Research and the ExperimentalMethod
8/13/2019 AP Psych Prep 2 (Part I) - Research and Experimental Method
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Psych is a Research Based Subject
Because it’s a science, it is based on research, andusing the scientific method.
We don’t use guesses, assumptions, or “common sense”to decide what is right or wrong
Hindsight bias: when you learn something, and think
“of course that’s the way it is!” E.g “birds of a feather” vs. “opposites attract”
8/13/2019 AP Psych Prep 2 (Part I) - Research and Experimental Method
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Very Important
Understanding this chapter is very important forunderstanding psychology, AND for doing well on the AP Psych. Exam.
(8-10% of exam, very likely to be part of writtenquestion)
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Some Basic Vocabulary:
Applied Research: has clear practical applications; e.g.helping depressed people, helping increase learning…
Basic Research: no clear use right now, just curious.But later we might find a use for it; e.g. how does thebrain work, how do people learn…
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Some Basic Vocabulary:
Variable: something that can VARY (change); we willchange or measure these when we do research.
Independent Variable (I.V.): We change the I.V.; it ismanipulated by the scientist
Dependent Variable (D.V.): Changes BECAUSE of our
manipulation; it DEPENDS on the I.V.
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Variables
And sometimes we don’t really have an I.V.
Some studies we don’t change a variable, we just
measure two or more variables and compare them.(Correlational Study, we’ll study that in a little bit).
If it’s difficult/impossible to change the variable, or if
it’s unethical to change it
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Variable Example
Imagine we are going to give students coffee and see ifthe coffee helps them to study longer and get bettergrades.
What is the I.V.? _____________________
What is the D.V.? _____________________
Is there only one I.V. and D.V.?_____________________________________
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Hypothesis
Usually we have a statement of the relationshipbetween two variables that we are testing. Thisstatement is called the Hypothesis (plural hypotheses)
What might our coffee study hypothesis be?
_____________________________________
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Theory
Theory: an organized explanation for somephenomena. Theories are NEVER 100% proven. Canalways be changed if we find new information.
Theories can produce hypotheses for us to test.
E.g. Theory of Evolution. Large explanation, that we
test using many studies.
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Theory
• Large Explanation
• Can suggest hypothesis
Hypothesis
• One statement of relationship
• We will test it
Research
• The way we test the hypothesis
• Result will support or not supp.1. Support
2. NotSupport
Change Theory, or even trash itand start a new one.
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Operational Definitions
Operational Definition of Variables: The definition ofour variables by which we OPERATE. This is how we will use and measure our variables.
Must be very specific, and include HOW you willmeasure the variable. So other scientists can repeat your procedure.
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Operational Definition Example
Imagine we will be measuring people’s height in ourstudy. How would you operationally define height?
Your def:
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Person with no shoes or socks on stands straightagainst a wall with a 6 meter “Johnson” tape measuretaped to it. The 0 mark of the tape measure is placedfirmly at the joint of the floor and wall. The personmeasuring places a 30 cm long “Spirit” levelhorizontally on the middle of the person’s head,ensuring the level is level. The measuring person readsthe height mark that comes next BELOW the point where the bottom edge of the level and the tapemeasure touch.
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Operational Definition Example
What about our student coffee study? How would youoperationally define our variables?
Coffee intake: ______________________________________________________________
Longer Study: ______________________________________________________________
Better Grades: ______________________________________________________________
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More about Variables
Validity – a measure REALLY measures what we wantit to measure. Our height measurement was probably valid.
E.g. What if we measure student frustration bycounting how many times they put their head on theirdesk?
Maybe frustrated students will place their heads ontheir desks more often… But…
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More about Variables
Reliability – a measure can be repeated, and find thesame result.
E.g. IQ test should measure intelligence. Intelligenceshouldn’t change quickly. So if we measure today, andagain next week, it should give us a very similar result.
If not, it is probably not be a reliable measure.
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Sampling
When we do research, we will have participants – people we do research on; research subjects.
Sampling – how we choose our participants
Sample – the group of participants we choose to use inour research
Population – the WHOLE group that you want toknow more about. Our sample is a small part of ourpopulation.
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Sampling
Population examples: all humans, all teachers inKorea, all female students at SGHS
Population doesn’t have to be humans. Schools, companies, animals, etc.
We almost never sample the WHOLE population. We
choose only SOME to be in our sample.
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Sampling
We want to get a representative sample.
Representative Sample – shares the characteristics ofthe population as a whole group. It REPRESENTS the
whole population.
So when we finish our study, hopefully we can say“What we learned is likely also true for the whole
population” Generalizing the results to the pop.
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ow o a e a epresen a veSample?
To get a represent. sample of the SGHS studentpopulation, should I choose class 6 of 1st grade to bemy sample? Why not?
How should we select our coffee study sample?
__________________________________________________________________________
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ow o a e a epresen a veSample?
Random Selection – any method where each memberof the population has an equal chance of beingselected.
If we use random selection, high probability that oursample is representative of the population.
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Representative?
SGHS Population:
E.g. if we stand in the hall on the 1st f loor, and choosepeople who walk by?
If we stand outside the gym at 12:45pm and choosepeople who walk by?
If we randomly select one student using a computerprogram?
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Random Selection
Randomly selecting with a computer, a randomnumber table, or names in a hat.
Also, larger samples are more likely to berepresentative.
Too large a sample will be expensive to study. On AP
Test, if you’re asked to design a study, be sure tomention your sample methods, sample size, etc.
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Stratified Sampling
Sometimes it’s really important to be representative incertain categories. One study might want to make sureit’s representative for males and females.
Stratified sampling – divide into important groupsfirst, then sample participants from those groups.
E.g. men 20%, women 80%. We would take 20% of oursample from the men, 80% from women.
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Types of Research Methods!
Now we will talk about a few different types of researchmethods. Try to see how they are different, what mightbe advantages or disadvantages of each type, and why we might use one instead of the others.
Research methods: different ways to try to gatherinformation and learn about or test something
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Experimental Method
In an experiment, we control the I.V., eliminate allconfounding variables, and measure the D.V.
If the D.V. changes when we ONLY change the I.V., wecan see how they are connected. We know that the I.V.is CAUSING the D.V. to change.
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Confounding Variables
Experiments will tend to have more than one group:one is experimental group that gets the treatment, andother is control group that does not get the treatment.
Confounding variable (C.V.) – Other than the I.V., anydifference between the participants or their treatment. We need to get rid of all these differences, so that the
I.V. is the ONLY difference. Otherwise C.V. might bethe real CAUSE.
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Confounding Variables
In our student coffee example, what could be:
Experimental Group: ____________________
Control Group: _________________________
Confounding Variables: ____________________________________________________________________________________________
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Random Assignment
Participant-relevant confounding variables – differences between the groups of participants otherthan the I.V.
E.g. all coffee drinkers are male, control group is allfemale…
A good way to get rid of confounding variables israndom assignment - putting our selected
participants into experimental or control groupRANDOMLY.
*How is this different from random selection?
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Same Treatment
situation-relevant confounding variables – differencesbetween how the groups are treated, other than theI.V.
E.g. coffee drinkers study in colder place, better litplace, study different material, etc.
We need to make sure we treat both groups EXACTLYthe same, except for the I.V.
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Group Matching
Just like stratified sampling, maybe we want to makesure our groups are similar on some characteristic thatis important for our study.
We can use group matching – group by some desiredcriteria first, then randomly distribute half of thesegroups into our experimental and control groups.
E.g. Sample of 20 men and 80 women, then menrandomly into 2 groups, women randomly into twogroups. (10+40, 10+40)
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Experimental Method
Experiments are the preferred method, because it isthe only way we can show CAUSE. we want to findcauses, so we can start to control, change or fix things.
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Experimental Method
LabExperiments
Done in a lab,highly controlled
environment
Advantage: morecontrolled,
strongerconclusions
FieldExperiments
Done out in real world
Advantage: Moretrue to real life;more realistic
But BOTH are kinds or experiments, where we change the I.V.
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Sources of Bias:
Experiments can be influenced by a lot of differentforms of bias, and we need to be aware of these andfight against them.
Demand Characteristics – clues that hint at purpose ofstudy. Participants can notice these, and try to respondin ways that support that purpose. E.g. responding in
a sad way if they think that is what you are looking for.
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Sources of Bias:
Single blind method- used to help eliminate demandcharacteristics. Method where participants don’t know which group they are in.
We must be careful not to give any hints that couldinfluence how our participants act.
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Sources of Bias:
Response bias – tendency for participants to behave incertain ways; e.g. choosing the right side option moreoften. Solution: mix up options
Social Desirability – one kind of response bias,subjects pick responses that make the subject lookgood. Especially a problem for sensitive subjects
(helping others, violence, sex)Solution
: anonymity,other way to measure
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Sources of Bias:
Experimenter Bias – A kind of situation-relevantconfounding variable. Where experimenter treatsgroups differently to increase the chance of confirmingthe experimenter’s expected results.
Unconsciously. If on purpose, then called fraud.
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Sources of Bias:
Double blind procedure – Used to solve experimenterbias. BOTH the experimenter and the participantsdon’t know which group each participant is in.
Often we might use one or more research assistants, who don’t know the purpose of the study, or whichgroup is which. E.g. medicine, alcohol, watching a
film, etc.
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Other Sources of Bias:
Placebo effect – where just getting some medicine orattention will have an effect, even if the treatment isnot effective by itself.
Problem for testing medications, but also otherpsychological research studies.
So Placebo method – give a “treatment” to bothgroups, but one is missing the I.V.
So they will have equal treatment, except I.V.
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Other Sources of Bias:
Sometimes, we use within-subjects design – whereeach participant gets BOTH the experimental andcontrol conditions.
e.g. all people do alcohol and a motor task, or noalcohol and motor task, then compare the two.
What problem is possible?
_____________________________________
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Coffee Example Sources of Bias:
What are some possible sources of bias for our coffeeexperiment example? How could you solve them?
__________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________