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FSU PSY 3213C - The Cycle of Scientific Progress

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The Science Game & The Cycle of Scientific Progress: Ch. 1, Ch. 2 & Ch. 3 (1/10 & 1/15lectures)- The Cycle of Scientific Progress**:o Theory-Data Cycles : the most important cycle in science is the theory-data cycle, in which scientists collect data to test, change, or update their theories. Theory leads researchers to pose particular…- Research questions, which lead to an appropriate…o Research design. In the context of the design, researchers formulate… Hypotheses. Researchers then collect and analyze…- Data, which feed back into the cycle.  If/Then reasoning enables us to test and refine theories- Book calls this the Theory-Data cycleo Basic-Applied Cycle : If/Then reasoning also enables us to take basic findings and apply them to more realistic scenarioso Modifying Theories to accommodate new resultso Empirical Testing & Empirical Evidence Empirical Evidence is:- An observation or measurement that contributes to either verifying or falsifying a claim about what’s true;- Independent of the observer (i.e., objective). The evidence will be the same no matter who observes it. Empirical Testing is:- Any situation or procedure that creates empirical evidence which allows a claim on truth to be verified or falsified. - Empirical tests must be replicable and verifiable. o “Golden Assumption”  If an object of study exists in nature, it is knowable:- In other words, its possible to fully DESCRIBE and EXPLAIN even highly complex things, like brains, beliefs, time, and romantic relationships The object of study is lawful- If we could perfectly control all of the input variables, we could perfectly PREDICT and CONTROL the outcome. o The importance of replication- 3 Types of Claims:o Frequency  A claim that describes a particular rate or level of a single variable.  Claims about what things/people/nature tend to be like and how frequently certain values or scores on a variable occur Ex. Median family income in the US is $51,900.  Ex. Lifetime frequency of mood disorders in the US is 20%. o Association Claim about 2 variables, in which the level of one variable is said to vary systematically with the level of another variable, such that when one variable changes, the other variable tends to change, too. Ex then people who more strongly endorse traditional gender normswill more strongly show the gendered pattern.- Women with less traditional gender attitudes had more sexual partners, r= -.33. Ex: recency & intensity of illness has a stronger relationship with women’s libido than men’s. Claims about the a purported relationship between two measured variables Ex: Time spent playing videogames is positively correlated with creativity Ex: The SAT exists because it is a moderately strong predictor of 1st year GPA.o Causal:  A claim arguing that a specific change in one variable is responsible for influencing the level of another variable.- Ex: Burger King Experiment Claims stating that changes in one variable induce changes in another variable. Ex: Sleep deprivation causes glycogen depletion (and thus poorer executive functioning)Operationalizing Measures: Ch. 5 (1/22 Lecture)- Psychological Construct vs. Operationalized definitionso To even begin to support such claims, we need to determine how to define and then measure the “constructs” of interest. o Psychological Construct:  Any explanatory variable that is not directly observable or tangible Ex. Intelligence, happiness, addictiono Operationalized definitions:  To make claims about constructs, we need to agree on how to operationalize them…- i.e. how to turn abstract constructs into specific, measurable instances that are both reliable and valid. - Operationalization is always a compromise between pragmatically measuring your construct and collecting data that validly tests your hypothesis.- Multiple ways to Operationalize psychological constructs:o Self-Report Recording people’s answers to verbal questions about themselves in a questionnaire or interview- Ex: Diener’s (1993) measure of happiness / subjective well-being (1-7 scale)o ___ In most ways my life is close to my idealo ___ The conditions of my life are excellento ___ I am satisfied with my lifeo ___ So far I have gotten the important things I want in lifeo ___ If I could live my life over, I would change almost nothing. Potential pro’s & con’s of self-report measures?- Pro’s: Easy & low cost, large anonymous samples, may be the most appropriate format (i.e. the study of attitudes)- Con’s: Open to fabrication & social desirability biases, memory distortions, laziness, may not be useful for non-conscious constructs.o Observational (Behavioral Measures) Recording observable behaviors or physical traces of behavior.- Ex: Counting the number of times subjects smile in a given time frame to measure happiness- Ex. Counting the number of problems attempted to measure motivation- Ex. Recording donations given to measure generosity. Potential Pro’s & Con’s of Observational/Behavioral measures?- Pro: More shielded from respondent bias, can be recorded w/ less interference, sometimes most appropriate Operationalization of a construct (e.g. helping)- Con: Can be more complicated to collect, subject to experimenters “seeing what they want to see”, discrepancies may arise over whether the behavior was actually produced (i.e. was that a smile or not?), ethics?o Physiological Recording biological data believed to be associated with a construct- Ex: Dopamine & Endorphin levels in the brain to measure happiness- Ex: Blood flow to the “reward center” (nucleus accumbens) in an fMRI Potential Pro’s and Con’s of physiological operationalizations?- Pro: hard to consciously control or fake, can be quite precise, perceived as more “credible.”- Con: can be expensive & time consuming to collect, may require technical expertise w/ machinery/procedures, may be most sensitive to uncontrollable sources of error. Ethics?- Scales of measurement**o Nominal  Variables in which the values are actually categories or labels Ex: Religions, colors, majors, presence or absence of a reactiono Ordinal Variables in which the values indicate some kind of ranking. Its numeric, but we can’t do any mathematical operations on it. Ex: Favorite movies, Where one finishes in a race.o Interval A quantitative measurement scale that has no “true


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