PSC 41 Week 3 Notes
PSC 41 Week 3 Notes PSC 41
Popular in Research Methods in Psychology
Popular in Psychology
This 4 page Class Notes was uploaded by Kayla Dillard on Saturday October 8, 2016. The Class Notes belongs to PSC 41 at University of California - Davis taught by Dr. Cross in Fall 2016. Since its upload, it has received 5 views. For similar materials see Research Methods in Psychology in Psychology at University of California - Davis.
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Date Created: 10/08/16
10/3/16 Lecture 4 Studying Behavior Variables • any characteristic or quality that varies • something we measure of manipulate (under our control) • operational definition: defining the variable by the means used to measure it • variables must vary, if there is only one level, then it is a constant • some are measured in categories (ex: variable: freshman housing, levels: dorm or not) • some are measured continuously (ex: variable: time, values: milliseconds) external, physiological, emotional, cognitive, behavioral variables • • measuring variables: • directly observe behavior (action, performance, archive, giving a test and seeing how many were answered correctly) • self-report (best way to find out attitudes, beliefs, feelings, memories) • monitor physiology (biological responses, physical states) Thing to Measure Method Used actions observation ideas self-report physical state monitor • associated claims: I wonder if x is related to y? • x is the predictor variable • pre-existing characteristic • y is the outcome • outcome, response • causal claims: What is the effect of x on y? • x is the predictor variable (independent) • directly manipulated by the experimenter • y is the outcome variable (dependent) • “depends on” the level of independent variable outcome, response, measured • • predictor variables • pre-existing characteristics • individual differences of the participants • not under the experimenter’s control • participants are grouped according to their level or value • independent variables • manipulated • under the experimenter’s control • participants are assigned a level or value Ex: What is the most therapeutic approach to treat depression? Predictor Variable= type of therapy (manipulated) • levels= meds, group, breathing exercises • categorical Outcome Variable= level of depression • levels= self-report (1. I can't get out of bed SA(5)A(4) N(3) D(2) SD(1)) • categorical Ex: Do boys and girls play in the same size groups of friends? Predictor Variable= gender (pre-existing characteristic) • levels= male, female • categorical Outcome Variable= group size • levels= 0,1,2,3,4… • continuos Claims Goals of Research in Psychology • Describe Behavior (frequency claims) • identify regularly occurring sequences of events • clarify behaviors • Predict Behavior (association of claims) • identify relationships between variables • strength of relationship leads to degree of confidence in prediction • Explain Behavior (casual claims) • understand the cause and effect Relationship Between Variables • Positive linear relationship • as one variable increases, the other variable increases Negative linear relationship • • as one variable decreases, the other variable increases • Curvilinear relationship • No relationship • Ex: Negative linear GPA Time on Facebook 10/5/16 Lecture 5 Determining Causation • Observing a relationship between two variables does to mean that one cause the other • Correlation does not imply causation • To conclude causation, we need to isolate the effect of one variable • start with two groups that are the same —> use random assignment • manipulate one variable • observe the outcome • Cause and Effect Criteria • Co-occurance • when v1 is present, is v2 also present? • when v1 is absent, is v2 also absent? if yes, then there is a relationship • • Time sequence • Alternative causes must be ruled out • if single headed arrow between v1 and v2, then it is a causal • if double headed arrows between v1 and v2, then there is a relationship • Method Overview • Correlational Research/Association Claims • two measured variables • searching for an association • • Experimental Research/Causal Claims • one manipulated variable, on measured variable • searching for causation • isolating the effect of the independent variable • goal: eliminate all but one explanation • starting with different groups and treating them the same is not an experiment Things to keep in mind: • no overall “best” method • question drives methodology • multi-methodological replication • scientists are skeptical and persistent Measuring VariablesAccurately and Consistently • “If you can’t measure it, it doesn’t exist” • Almost all measurements include some degree of error or noise • We must evaluate the accuracy and consistency of the measurement • Some things can’t be directly measured • create a construct that can be measured and approximates the variable of interest • Aconstruct: hypothetical variable that we can’t direct observe (intelligence, happiness…) • Validity (accuracy) • genuine, credible, true • accuracy or correctness • can be very narrow or very broad • not directly measurable • Construct validity • is the operational definition of a variable accurate? • Face Validity: does your operational definition appear to measure the construct? • procedure: did anything about the procedure add noise or error to the measurement? • • what was it like to be a participant? • method match: • is there an appropriate method to measure the construct? • Reliability (consistency) • repeat, replicate • if measured again, will you get the same result? • calculate correlations to assess reliability • test-retest • split-half • parallel or alternate forms • item-total • coefficient alpha (cronbachs) • inter-rater reliability • high: judges example 10/10, 9/10, 10/10 • low: judges example 10/10, 5/10, 1/10 “What might have been” • getting 2nd place in a race • better than 3rd but so close to 1st • bronze medalists displayed more positive emotions that silver medalists both immediately and later on the podium