L6 mock Paper 2 (just research methods)

define sampling

how we recruit our participants

define population

the group of people the researcher is interested in

what are sampling techniques?

the various methods we have in order to choose participants

what is bias?

systematic distortion in sampling – some types of people are over or under represented

define generalisation

the extent to which the findings of research on the sample can be generalised back to the population

what is volunteer sampling?

involves participants selecting themselves to be part of the sample (they self-select)

what are pros and cons of volunteer sampling?

pros:

• easy to recruit/cheap/quick

• enthusiastic, engaged and motivated people who want to take part

cons:

• certain type of person will volunteer (e.g. confident, people pleaser etc.)

• participants may change their behaviour (please you effect or screw you effect)

define validity

how genuine or legitimate something is

what are the 2 types of validity?

• internal

• external

define internal validity

the extent to which we measured what we set out to measure

define external validity

• the extent to which the findings and conclusions are generalisable beyond the context of the study

• how representative of real life was the study?

what are the 4 types of validity that make up external validity?

• population validity

• temporal validity

• ecological validity

• mundane realism

what is population validity?

• sample

• is the sample representative of the population?

• can we generalise beyond the participants in the study

what is temporal validity

• time period (historical validity)

• is the time period the study was conducted in representative of of today

• can we generalise from time study was done to today?

what is ecological validity?

• setting/context

• is the setting representative of real life (where the behaviour would usually occur)?

• can we generalise beyond the setting/context of the study?

what is mundane realism?

• the specific task

• is the task representative?

• can we generalise?

what is an effective evaluation paragraph structured like?

P- point

E- explain, evidence, elaborate

T- therefore, this suggest

what are the levels of measurement?

• nominal

• ordinal

• interval

what is the average can be used for each level and which is the best?

nominal - mode (mode is only one so is also best)
ordinal - median and mode (median = best)

interval - mean, median and mode (mean = best)

what is nominal data and some examples?

• categorical data

• freq. count of a particular variable is recorded at this level of measurement (e.g. how many boys and girls in a class)

• data is discrete - one item can only appear in one category e.g. blood type

• examples: hair colour, blood type, eye colour

what is ordinal data and some examples?

• same properties as nominal data (a form of categorical data) but has a natural order

• doesn’t have equal intervals between each unit

• subjective

• examples: position in a competition, relative height among a group

what is interval data and examples?

• numerical scales with units of equal, precisely defined size

• continuous: 2.35cm, 24.34572558362527g

• ratio is the same but cannot go below 0

• example: length

in a race what would the nominal, ordinal and interval data be?

nominal - the country they are representing, the colour they are wearing

ordinal - order they finished the race

interval - their finishing time

how do you convert between levels of measurement?

can only convert down levels:

-rank order

-interval -> ordinal

^ e.g. reaction time in seconds (interval) -> order from fastest to slowest (ordinal)N

 

-ordinal -> nominal

^e.g. liker scale -> 3 categories e.g. happy, neutral and sad

what are measures of central tendency?

a descriptive statistic that provides information about a ‘typical’ value for a given data set

• informs about the central value for a data set

• are basically averages

• each one is appropriate for different situations

what are the different measures of central tendency?

• mean

• mode

• median

what are the strengths and limitations of the mean?

Strengths:

• most representative - included all scores in the data set so more representative

Limitations:

• easily distorted by extreme values (outliers/anomalous values)

what are some strengths and limitations of the median?

strengths:

• not affected by extreme scores (like the mean)

• easy to calculate

Limitations:

• less sensitive than the mean as it ignores the value of the highest and lowest values

what are some strengths and limitations of the mode?

strengths:

• easy to calculate

• only measure of central tendency appropriate for nominal data

limitations:

• very crude measure

• can have more than one mode (e.g. bimodal) - not very useful

what are measures of dispersion?

a descriptive statistic that provides information about the spread or variation in a set of data

• tell us how far scores vary and differ from one another

what are the different measures of dispersion?

• range

• standard deviation

what is the range?

• the arithmetic difference between the highest and lowest values in a data set

what is the standard equation for the range?

• range = (highest value - lowest value)+1

• we always add 1 to correct for rounding errors in psychology

why do we add one to the range in psych?

to account for numbers that have probably been rounded

what are some strengths and limitations of the range?

strengths:

• easy to calculate

• useful for ordinal data

limitations:

• affected by extreme values

• doesn’t take into account the distribution of the data

what is standard deviation?

• a precise measure of the dispersion in a set of data

• tells us by how much, on average, each value deviates from the mean

what do high standard deviation values mean and low ones?

high SD:

• not all Ps are affected in the same way

• there is a lot of variation within the data set

low SD:

• values are clustered around the mean

• all the Ps may have responded in a similar way

what are the strengths and limitations of standard deviation?

strengths:

• precise measure of dispersion - takes all scores into account

• useful for interval data

limitations:

• affected by extreme values

• extreme values may be ‘hidden’ within the data

fill in the gaps

what is quantitative data?

information that represents how much or how long, or how many etc. there are of something (measured in numbers)

what is qualitative data?

information in words that cannot be counted or quantified, can be turned into qualitative data by placing them in categories and counting the frequency

what are some characteristics of quantitative data?

• Quantity

• Numbers

• Dependant variable in an experiment is quantitative

• Closed questions in questionnaires - how many hours a week you work, numerical info about your age etc.

• In an observational study a tally of behavioural categories is quantitative 

• Data that can be measured

• Psychologists develop measures of psychological variables

• Looking at averages and differences between groups

what are some characteristics of qualitative data?

• Quality

• Descriptions (words)

• In an observational study the researcher can describe what they could see

• Can't be counted or quantified but can be turned in quantitative data by placing data into categories then counting frequency

• Allows people to freely express their thoughts and feelings in own words - contrasts with quantitative which gives limited options

• Open questions in questionnaires may collect qualitative data like descriptions

• Data that is observed but not measured

• Observing people through the messages they produce and the way they act

• Concerned with attitudes, beliefs, fears and emotions

what is a strength of quantitative data?

Easy to analyse making conclusions be able to be drawn easily

what is a limitation of quantitative data?

• May oversimplify reality

• e.g. questionnaire with close questions may force people to tick answers that don't really represent their feelings therefore the conclusions may be meaningless

what is a strength of qualitative data?

• Provides rich and detailed info about peoples experiences

• Can provide unexpected insights into thoughts and behaviour because answers are not restricted by previous expectations

what is a limitation of qualitative data?

• complexity of data makes it more difficult to analyse the data and draw conclusions

is primary data qualitative or quantitative? and secondary?

both primary and secondary data can be quantitative and/or qualitative

what is primary data?

info observed or collected directly from first hand experience

what is secondary data?

• info used in a research study that was collected by someone else for a purpose other than the current one

• for example, published data or data collected in the past

what would the collection of primary data include?

• designing the study

• gaining ethical approval

• piloting the study

• recruiting and testing Ps

• analysing the data collected and drawing conclusions

when collecting primary data what will the data relate to?

the data will specifically relate to the aims and/or the hypothesis of the study?

where may a researcher get secondary data from?

Researcher may make use of government material/stats such as info about the treatment of mental health or make use of data held by a hospital or other institution

what type of study often uses secondary data?

a correlation study and review studies conducting a meta-analysis

what is a strength of primary data?

• researcher has big control over the data

• the data can be collected can be designed so it fits the aims and hypothesis of the study

what is a limitation of primary data?

• Very lengthy and expensive process

• simply designing a study takes a lot of time and then time is spent recruiting participants, conducting the study and analysing the data 

what are 2 strengths of secondary data?

• Simpler and cheaper to just access someone else's data because significantly less time and equipment is needed

• Such data may have been subjected to statistical testing and thus is known whether it is significant

what is a limitation of secondary data?

the data may not exactly fit the needs of teh study

define extraneous variable

• Any variable which is not being investigated but has the potential to affect the outcomes (results and conclusions) of the research  

• e.g. weather, time of the day – all that might affect behaviour  

define confounding variable

• Any variable which is not being investigated but affects the outcomes (results and conclusions) of the research (harder to know if there will be an impact than extraneous) 

• e.g. Monday morning traffic – in August  

define reliability

• The consistency of a research study or measuring test  

• Often assessed by replication  

• Repeat and get same results = reliable  

define observational studies 

• The researcher watches or listens to participants engaging in whatever behaviour is being studied. 

• Allows researchers to study behaviour within a natural or controlled setting  

• The researcher records observations in some sort of way e.g. tally chart 

 

observational studies pros

• Capture what people actually do 

• Can be very different to what they think or say they will do  

• Also captures unexpected or spontaneous behaviours  

• High internal validity – internal validity is a measure of whether results obtained are solely affected by changes in the variable being manipulated (e.g. by the independent variable) in a cause and effect relationship 

observational studies cons

• Risk of observer bias  

• Observer bias = observers interpretation of a situation may be affected by their expectations and previous experiences  

• Cannot demonstrate casual relationships (unless in an expt) 

define naturalistic observations

• take place in the setting/context where the behaviour world normally occur  

• All aspects of the environment are free to vary  

• Everything is left as it normally is – no interference from researcher  

Naturalistic observation pros 

• High external validity  (a measure of whether data can be generalised to other situations outside of the research environment they were originally gathered in) 

• More likely to be spontaneous  

• More generalisable  

Naturalistic cons

• Low control 

• There may be uncontrolled variables (extraneous and confounding variables) 

• More difficult to detect patterns in behaviour  

• Difficult to replicate  

define controlled observation

some variables in the environment are controlled by the researcher

controlled observation pros

• Can focus on particular aspects of behaviour

• Replication easier as extraneous and confounding variables (EVs and CVs) are minimised 

controlled observation cons

• Low external validity

• Environment not as natural

• Causes behaviour to not be as natural

define covert observation (and some characteristics)

– participants are unaware they are being observed

• Being secretly observed

• Observing behaviour across a room or public location

• MUST be a public behaviour and happening anyway

covert observation pros

• Demand characteristics are reduced

• Behaviour is more natural

• Increases internal (and external validity)

covert observation cons

• Ethics (invasion of privacy?, consent?)

• e.g. observation of shopping – shopping = public behaviour, but amount of money spent = private and therefore invasion of privacy if observed and recorded.

define overt observation (and some characteristics)

 – participants are aware that they are being observed

• Have given consent before hand

• Strange situation

overt observation pros

• more ethically acceptable

overt observation cons

• Demand characteristics are increased

• Change behaviour when know being watched

• Reduces internal validity

define participant observations

• Researcher becomes part of the group they are observing

• Being undercover

participant observation pros

• Can lead to greater insight and understanding of the target behaviours

• Researchers experiences situation as participants do

• Enhances external validity

participant observation cons

• Possible loss of objectivity

• Researcher may identify too strongly 'too native' (get too far in, can't get out)

• Threatens the internal validity

define non participant observation (and characteristics)

• the observer remains separate from the group being studied

• Sometimes not possible to be participant

• e.g. female researcher in boys school

non participant observation pros

• More objective

• Less chance of observer bias

• Increases internal validity

non participant observation cons

• Loss of insight

• Too far removed

• Reduces external validity

what can validity and reliability be pictured like?

• on scales

• when one increases the other usually decreases

define time sampling

an observational technique in which the observer records behaviours in a given time frame.

define sampling

the method used to select participants, such as random, opportunity and volunteer, or to select behaviours in an observation.

define event sampling

an observational technique in which a count is kept of the number of times a certain behaviour (event) occurs.

define behavioural categories

dividing a target behaviour (such as stress or aggression) into a subset of specific and operationalised behaviours.

define operationalised

defining a variable in a clear, precise and measurable way so it can be tested and replicated.

define a structured observation

a researcher uses various systems to organise observations.

what is the difference between structured and unstructured observations?

Unstructured has no system and records all relevant behaviour but structured uses various systems to observe specific behaviours

the more that you control the variables in the experiment the more….

• internal validity increases

• external validity/realism decreases

what does standardisation mean?

• means all Ps experience identical procedures and materials

• all Ps have the same experience of being involved in the study

• controls for extraneous variables

• e.g. watching the same video at the same volume in the same room

what are standardised instructions?

• all Ps given exactly the same instructions, delivered in the same way

• instructions are scripted and read aloud to Ps or are read aloud to Ps or are read by Ps - this helps control investigator effects or investigator bias

what are investigator effects?

anything an investigator does (consciously or unconsciously) that has an affect on a Ps behaviour in a study.

It can be:

• direct (interacting with P)

• indirect (as a consequence of how the study was designed)

what is investigator bias?

a type of investigator effects which results in some kind of skew or bias e.g. putting all most intelligent Ps in same group

what is an extraneous variable?

any variable which may effect the DV, other than the IV - either P variables or situational variables

what are situational variables?

features of a situation/environment e.g. time, weather

what is randomisation?

• the use of chance wherever possible in the design of the study

• e.g. generating a word list - random generation of words, random order of words in the list

what is random allocation?

• the use of chance to allocate Ps into the conditions

• controls for investigator effects and for participant variables (characteristics of individual Ps e.g. age, motivation, intelligence, traits, experience - type of extraneous variables

when are control groups used?

• 2 or more levels or conditions of IV

• environmental group - change in IV

• control group - no change in IV, exactly same experience except for the IV