distribution curves - NORMAL
symmetry at the middle, end points meet x axis, bell shaped, measure of central tendancy are the same, this is expected from normal target population
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distribution curves - POSITIVE SKEW
more low scores than high, measures of central tendancy decrease
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distribution curves - NEGATIVE SKEW
more high scores than low, measures of central tendancy increase
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Errors - 2 types and why
type 1 = false positive, type 2 = false negative; happen when significance levels are set too low or high
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significance levels
determine whether we accept or reject the hypotheses; most common is p
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probability =
desired outcome/total possible outcomes
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< less than, > greater than, , ~ approximately, ∝ proportional
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my practicals - experiment
controlled setting, chewing gum affect concentration, opportunistic, independant measure, had to use deception, anonymous and debriefed afterwards, may have been individual differences - practice, intelligence
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my practicals - self report
do colours affect mood/emotions; open and closed 8 questions, opportunistic, anonymous and written consent, didn't always answer questions correctly and i didn't find this in my pilot study
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my practicals - correlation
gcse score and age; opportunistic, weak positive correlation, wasn't significant because didn't meet calculated critical value for n=15
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my practicals - observation
observed flirting behaviour, non pp + covert (to maintain e.v and prevent dc), structured - coding frame, event sampling, inter rater was 0.96, could improve this by explaining behaviours clearly and training observers beforehand with pilot study
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types of observations - 8
naturalistic = natural setting of pps; controlled = control all factors affect behaviour; structued = coding frame; unstructured = record everything; cover = undercover; overt = know and consented; participant or non pp
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designing observations - 3 types and whats used
time point sampling = record whats happening at certain intervals; time event sampling = record everything within a set time; event sampling = record behaviours each time they happen; we use coding frames
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self report - 4 types (first 2)
questionnaire - gathers lots of data quickly, may be cultural limitations, low response rate; structured interview - data easy to compare, standardised, pps can't explain/elaborate;
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self report - 4 types (second 2)
semistructured - clarify/explain, both types of data, not standardised; unstructured - can build rapport, rich data with explanations, time consuming so may use less pps?, difficult to analyse, higher ecological validity
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experiments - what are their features ?
have IV and DV, hypothesis which predicts, aims to establish cause and effect
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experiments - lab
controlled setting; eliminates EV's, can test replicability so is reliable, lacks ecological validity
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experiments - field
natural environment of pps; higher ecological validity, less likely to alter behaviour, can't control EV's and isn't standardised
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can be positive or negative; look for relationship between 2 variables; allow us to investigate things couldn't do ethically in experiments, but correlation doesn't mean cause and effect
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experiments - quasi
IV is naturally occurring and can't be directly manipulated by researcher; allows us to measure how these IVs affect behaviour, little sample bias, but may be variance in pps due to different upbringings, hard to replicate
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Extraneous variables
can be participant (e.g. intelligence) or situational (e.g. room temp); a confounding variable is one that hasn't been eliminated or controlled and so affects the DV
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hypotheses - what are they and 3 types
arise from previous research or an event; can be alternate: one tailed (directional) or two tailed (non directional), or null
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how to get a sample
general population -- target population -- sample that is representative of who we're going to generalise to
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types of sampling - opportunity
use whoevers available; quick and easy, not very representative
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types of sampling - self select
volunteers from adverts; know they will fit the criteria, but may have strong opinions = bias
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types of sampling - random
everyone in TP has equal chance of being chosen; very representative but may give unequal gender distribution
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types of sampling - snowball
one person from odd group is chosen and they suggest others; more ethical than asking prying questions, but may not reply and are all from same area as first person
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experimental designs - independant measures
randomly allocate pps to IV; simple and quick, no order effects/demand characteristics, may be individual differences
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experimental designs - repeated measures
tested on all IV levels; more data, may be order effects/demand characteristics, no individual differences
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experimental designs - matched pairs
pps matched on similar factors then split; trys to eliminate individual differences, no order effects/demand characteristics, time consuming and may be hard to match exactly
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demand characteristics
pps act unnaturally as they know they're being researched; can be a confounding variable
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social desirability - what can we use to check for it
pps don't answer truthfully, but answer to appear a better person; can use face validity to check for this
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researcher effects
things researcher does that affects quality of data
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researcher bias
attitudes/actions that threaten quality of research as a whole
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3 types of self reports
rating scale - measure variables e.g 1-10; likert scale - choose response that matches feeling, e.g agree/disagree; semantic differential scale - choose point between 2 opposites, e.g expensive----cheap
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sections of a report - the order
abstract, intro, method, results, discussion, appendices, references
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sections of a report - abstract
brief summary and what was found
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sections of a report - intro
area of psychology, aims and hypotheses
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sections of a report - method
sample, design, procedure, apparatus
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sections of a report - results
raw data and summaries of it
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sections of a report - discussion
evaluation of results, alternate explanations
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sections of a report - appendices
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sections of a report - references
use harvard referencing system - name of researcher, date of publication, title of study, title of journal, volume, page numbers
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peer review
work sent to others with expertise in the field; can either approve for publication or give recommendations for improvement, maintains quality of journals, prevents plagiarism/fabrication, may be biased - might not approve if don't agree
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how science works - cause and effect
research can show one factor causes another; improve with controls/standardisation
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how science works - falsification
testing other hypotheses and proving them wrong makes our study more reliable
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how science works - replicability
study can be repeated and get the same results; improve with controls/standardisation
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how science works - hypothesis testing
test using observation/experiments to gain new knowledge
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how science works - objectivity
researcher isn't influenced by personal opinions, no bias
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how science works - manipulation of variables
see if results change with/without presence of IV
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how science works - quantifiable measures
quantitative, objective, observable, scientific
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how science works - controls
eliminate evs to be sure cause and effect is true
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how science works - standardisation
control apparatus, procedure, instructions to control situational evs - makes it replicable
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how science works - induction
bottom up theory; think of hypotheses and test them, look for patterns then develop theory
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how science works - deduction
top down theory; think of theory, create testable hypotheses then test them to prove our theory
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levels of measurement - nominal
NUMBER of pps in categories
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levels of measurement - ordinal
data can be ORDERED from highest to lowest
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levels of measurement - interval
data measured in equal intervals
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levels of measurement - ratio
interval, but with a true zero - time
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reliability - define
where a study can be used more than once and produce consistent results
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reliability - internal
within, first half same as second? split half test
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reliability - external
gives same results over time; test retest
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reliability - inter rater
2 observers get same results, shows there's no observer bias
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validity - define
how accurate research is at measuring what it aims to
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validity - internal
ev's aren't causing an effect
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validity - external
can be generalised due to being conducted realistically
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validity - face
how good it appears to be
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validity - construct
measure actual behaviour it aims to
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validity - concurrent
gives same results as other tests measuring the same thing
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validity - criterion
how accurately one measure predicts another
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validity - population
how accurately measures behaviour in general population
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validity - ecological
same as real life
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measures of central tendancy - mean
uses all data values so is most sensitive; don't use with extreme anomalies
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measures of central tendancy - median
is less sensitive to variations; less sensitive so may not show true picture
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measures of central tendancy - mode
good for data in categories; may be no/more than one mode
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types of data - primary
conducted by researcher, find exactly what we want, may not be as accurate as large companies with access to lots of pps
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types of data - secondary
published/official statistics, accurate and reliable, may be dated
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charts - bonus
describes data and makes it easier to analyse
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charts - pie
shows data as a percentage of a whole
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charts - line
shows 2 conditions over a period of time
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charts - bar
data from table; not continuous
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charts - histogram
data from table; continuous
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charts - scatter
shows relationship between 2 variables
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ethical considerations - what and why?
CRIR; ethics are the science of morals; give psychology a good name and means pps with take part again
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ethical considerations - C
competence - understand limits of knowledge, accept responsibility to try and resolve issues
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ethical considerations - R
respect - respect cultural differences, right to withdraw, confidentiality, informed consent
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ethical considerations - I
integrity - value honesty, avoid deception
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ethical considerations - R
responsibility - ensure pps come to no physical/psychological harm; used debriefing if they do
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Other cards in this set

Card 2


distribution curves - POSITIVE SKEW


more low scores than high, measures of central tendancy decrease

Card 3


distribution curves - NEGATIVE SKEW


Preview of the front of card 3

Card 4


Errors - 2 types and why


Preview of the front of card 4

Card 5


significance levels


Preview of the front of card 5
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