Chapter 2 Review (Research Methods)

Front 1

Why do we need to design experiments"

Back 1

Psychology is first and foremost a science and must be based on research

Front 2

Hindsight Bias

Back 2

The tendency to believe, after learning the outcome, that you knew it all along.

Hint 2

Monday Morning quarterbacking

Front 3

Overconfidence

Back 3

•Wetend to think we know more than we do.

Hint 3

ExampleS:

•82% of U.S. drivers consider themselves to be in the top 30% of their group in terms of safety.

•81% of new business owners felt they had an excellent chance of their businesses succeeding. When asked about the success of their peers, the answer was only 39%.

Front 4

The Barnum Effect

Back 4

the tendency for people to accept very general or vague characterizations ofthemselves and take them to be accurate.

Hint 4

Like fake fortunetellers telling you about yourself

Front 5

Applied vs Basic Research

Back 5

•AppliedResearch has clear, practical applications.•YOUCAN USE IT!!!

•BasicResearch explores questions that you may be curious about, but not intended tobe immediately used.

Hint 5

Applied:" how people learn multisyllabic words most easily.

Basic: How kissing changes as you age

Front 6

Methods of psychological reserach

Back 6

1. Experimental

2. correlational

3. Survey

4. Naturalistic observation

5. Case studies

Front 7

Experimental method

Back 7

•Lookingto prove causal relationships.

•Cause= Effect

•Laboratoryv. Field Experiments

Front 8

Hypothesis

Back 8

•Expressesa relationship between two variables.

•Avariable is anything that can vary among participants in a study.

Hint 8

Example:

Participating in class leads to better grades than not participating.

Front 9

Independent Variable

Back 9

•Whateveris being manipulated in the experiment.

•Hopefullythe independent variable brings about change.

Hint 9

If there is a drug in an experiment, thedrug is almost always the independent variable.

Front 10

Dependent Variable

Back 10

•Whateveris being measured in the experiment.

•It isdependent on the independent variable.

Hint 10

Example: Effect of the drug

Front 11

Operational Definitions

Back 11

•Explainwhat you mean in your hypothesis.

•Howwill the variables be measured in “real life” terms.•Howyou operationalize the variables will tell us if the studyis valid and reliable.

Front 12

Sampling

Back 12

•Identifythe population you want to study.

•Thesample must be representative of the population you want to study.•GET ARANDOM SAMPLE.•StratifiedSampling

Front 13

Confounding Variables

Back 13

•Theobject of an experiment is to prove that A causes B.

•Aconfounding variable is anything that could cause change in B, that is not A.

Front 14

Random Assignment

Back 14

•Once you have a random sample, randomly assigning them into two groups helps control for confounding variables.

•ExperimentalGroup v. Control Group.

•GroupMatching

Front 15

Hawthorne Effect

Back 15

•even the control group may experience changes.

•Justthe fact that you know you are in an experiment can cause change.

Front 16

Experimenter Bias

Back 16

•Anotherconfounding variable.•Not aconscious act.

•Double-BlindProcedure protects against this.

Front 17

•Placeboeffect

Back 17

Effect of thinking you feel something even though you are given a non-drug

Front 18

Order Effects

Back 18

how the positioning of question or tasks in a survey, test, etc., influences the outcome.

This is designed to measure whether the order of the questions makes a difference in the outcome of the survey.Read more: http://www.alleydog.com/glossary/definition.php?term=Order%20Effect#ixzz3xYwF2AQj

Front 19

correlational method

Back 19

•Correlationexpresses a relationship between two variable.

•Doesnot show causation.

Hint 19

Positive: effects go in same direction

Negative - effects go in opposite directions

Front 20

Survey Method

Back 20

Most common type of study inpsychology

Measures correlation

Cheap and fast

Need a good random sample

Low-response

Front 21

Naturalistic observation

Back 21

•Watchsubjects in their natural environment.

•Donot manipulate the environment.

•Thegood is that there is no Hawthorne effect.

•Thebad is that we can never really show cause and effect.

Front 22

Correlation Coefficient

Back 22

A number that measures the strength of a relationship.

Range is from -1 to +1

The relationship gets weaker the closer you get to zero.

Front 23

Case studies

Back 23

•Adetailed picture of one or a few subjects.

•Tellsus a great story…but is just descriptive research.

•Doesnot even give us correlation data.

Front 24

Statistics

Back 24

•Recordingthe results from our studies.

•Mustuse a common language so we all know what we are talking about.

Front 25

Descriptive statistics

Back 25

•Justdescribes sets of data.

•Youmight create a frequency distribution.

•Frequencypolygons or histograms.

Front 26

Central tendency

Back 26

•Mean,Median and Mode.Watch out for extreme scores oroutliers

Hint 26

Ex: Dunder Mifflin paper company - boss has huge salary that skews the results of average.

Front 27

Normal Distribution

Back 27

mean, median and mode are all the same.

Hint 27

Middle of bell curve

Front 28

Issues with distribution

Back 28

•Outliersskew distributions.

•Ifgroup has one high score, the curve has a positive skew (contains more lowscores)

•If agroup has a low outlier, the curve has a negative skew (contains more highscores)

Front 29

Range and Standard Deviation

Back 29

•Range: distance from highest to lowest scores.

•StandardDeviation: thevariance of scores around the mean.

•Thehigher the variance or SD, the more spread out the distribution is.

Hint 29

•Do scientists want a big or small SD?

Front 30

z scores

Back 30

•Aunit that measures the distance of one score from the mean.

•Apositive z score means a number above the mean.

•Anegative z score means a number below the mean.

Front 31

Normal distribution

Back 31

Bell curve

Front 32

Inferential statistics

Back 32

•Thepurpose is to discover whether the finding can be applied to the largerpopulation from which the sample was collected.

•T-tests,ANOVA or MANOVA

•P-value=.05 for statistical significance.

•5%likely the results are due to chance.

Front 33

APA Ethical guidelines

Back 33

•IRB-Internal Review Board•Bothfor humans and animals.

Front 34

Guidelines for animal research

Back 34

Clear purpose

Treated in a humane wayAcquire animals legally

Least amount of suffering possible.

Front 35

Human resewarch guidelines

Back 35

•NoCoercion- must be voluntary•Informedconsent

•Anonymity

•Nosignificant risk

•Mustdebrief