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kinds of questions

description

prediction

explaination

description questions

what happens

prediction questions

when does it happen (does this happen when a certain something occurs)

explanation questions

why does it happen

after forming a question

form a theory

theory

general explanation of phenomenon

answers why does it occur

exaggerates some factors (those seen as important to explanation) and ignores or minimizes other

a good theory

organizes existing knowledge

explains phenomena in elegant brief way

draws attention to important processes

guide measurement decisions

identifies specific predictions and hypotheses

hypothesis

a specific, testable, and disconfirmable statement of theory to study

social sciences measure

constructs

construct

abstract idea

e.g. love, self-esteem, well-being, happiness, socioeconomic status, health

operationalization

translation of an abstract construct into concrete term to be measured and studied

construct validity

extent to which a measure of a construct is a good and valid measure of that construct

am i really measuring what I say I am measuring

methods of operationalization

self reports, systematic observation

self reports

data provided by the participants themselves

considerations:

-framing of questions

-beware of hidden assumptions in your questions

pros of self report

easy to administer

relatively fast and cheap

can assess exactly what we want to know

cons of self report

people dont always tell the truth

people dont always know the truth

systematic observation

any data not provided by participants

considerations:

-who should do the observing (usually independent of relationship)

-what are they going to observe

observable points

verbal communication

non verbal communication

written communication

physiological responses

pros of systemic observation

very powerful- can watch how people actually behave

rich data, great detail

cons of systemic observation

very expensive and time consuming

hard to observe some things

design of study

correlational research, experimental research

correlational research

determines whether two naturally occurring variables are related to one another

what can be concluded from correlational research

strength of association

direction of association

directions of association

positive correlation (a^ b^)

negative correlation (a^ bv)

zero correlation (a^ b neither ^ or V)

pros of correlational research

can be used to study variables that you cannot experimentally manipulate (ethically or practically)

cons of correlational research

correlation does not imply causation

possible explanations for a correlation between x and y

x causes y

y causes x

relation is the result of a third variable that causes both x and y

kinds of correlational studies

cross-sectional, longitudinal

cross-sectional

all variables are measured at one point in time

longitudinal

measures of same individual are collected at multiple time points

used to describe and predict changes over time

gets closer to causal statements

correlational studies work best if

controlled or adjusted for possible third variables

issues related to longitudinal data

how long should interval between measurements be (need enough time for change to occur)

daily diary studies: spouses answer questions each day (helps reduce sentiment override)

experimental research

manipulate one factor while controlling other factors (holding them constant)

some people exposed to a factor (experimental group) others not (control)

allows you to determine whether x CAUSES y

four defining features of an experiment

dependent variable

independent variable

control

random assignment

dependent variable

the outcome you wish to measure

independent variable

the variable you manipulate thought to cause the DV

control

all aspects of the situation must be help constant, except for the IV

random assignment

each participant must have the same chance of being on a given condition

if there is no random assignment,

it is not an experiment

if it is not an experiment,

you cannot make causal conclusions

five components of a research article

title and abstract

introduction

methods

results

discussion

title and abstract

provides an overview or concise summary of the paper (map for understanding)

what to look for in title and abstract

what are the major ideas addressed in the paper? are the studies correlational or experimental? what were the main findings

introduction

describes what is being studied and why

introduction includes

discussion of the theory guiding the research

reviews prior research on this topic

highlights a gap in out understanding of the topic

presents the hypotheses that will be tested

what to look for in introduction

why is this interesting or important to study

what is the gap the authors hope to fill

what specific hypothesis are tested

what constructs will the author focus on

do the authors make a compelling case for their hypotheses

methods

describe in detail how the study was conducted

methods includes

participants: who was the sample? how were they selected for the study

measures: describes how the constructs were operationalized

procedure: explains the step-by-step process of conducting the study

what to look for in methods

is the sample appropriate for the research question

what were the predictor variables/IVs and outcomes variables/DV’s used in the study? how were they assessed

was there anything about the study design that may affect the interpretation of results?

results

presents the statistical analyses used to test the hypotheses

often very technical but contain descriptions of findings in everyday language as well

you are not expected to understand the ins and outs of all

what to look for in results

did the results support the authors’ hypotheses? did they find what they expected to find?

did any finding emerge (or fail to emerge) that call the authors’ conclusions into question

were any of the results surprising

discussion

describes the implications of the findings

discussion includes

begins with a conceptual overview of the results

explains why the results are important and how the extend our understand of the topic

speculates on future directions for this line of research

discusses the potential limitations of this study

what to look for in discussion

are the authors’ conclusions justified, or do they overstate their case?

do the data strongly, moderately, or weekly support the conclusions

are there other ways to interpret the results?

what are the implications of the findings? what future research would you like to see on this topic

the fundamental theory of interpersonal attraction

we are attracted to those who

have the capacity to reward us

who may be willing to do so

#1 predictor of desire for second meeting, the only indicator

physical attractiveness

self report on physical attractiveness (American Couples Data)

males value attractiveness more than females regardless of sexual orientation

females value social resources more than males, regardless of sexual orientation

what we say we want in an ideal mate

does not necessarily predict which potential mate we actually pursue

speed dating on physical attractiveness

both were just as likely to chose physical attraction, none cared about earnings

why is physical attractiveness so important

halo effect

halo effect

knowing abt one quality makes you assume that you know a lot abt other qualities

ex. what is beautiful is good

We assume that beautiful people

possess other desirable traits, and we seek to benefit from these traits.

attractive people are more sociable

experience less rejection?

we are attracted to others who have similar

demographics, attitudes, values, and personality

caveat similarity attraction

perceived similarity matters more than actual similarity

why does similarity promote attraction

validating

ease of interaction

anticipate greater acceptance

attitudes and background

often matter the most in attraction

exposure is directly proportionate to

attraction

proximity and familiarity

we like what we know, more exposure, more we tend to like it

similarity effects may bias against interracial attraction but familiarity with other races

may reduce this bias

stage one

appraisal of initial afftraction

stage two

decision to make an overture

reciprocity principle

we like those who like us

“golden rule of attraction”

Why is reciprocity so attractive

people dislike rejection

once reaching a moderate to high chance of success

chance acting increases

we like people who

like us despite being generally selective

dyadic reciprocity

tendency for you to like a person who uniquely likes you

generalized reciprocity

tendency for you to like a person who generally like others

platonically we like

people who like everyone

stage three

strategic self-presentation

moderate confidence leads to

strategic self presentation

high confidence leads to

self expression

Time and place

of the overture matters

stage four

build-up of rapport

if no build of rapport

abort!