psychology- research methods

define aim

a statement of what the researcher intends to investigate, the purpose of the study

whats the DV

dependant variable- the things you measure

what is a directional hypothesis

states the direction of the difference or relationship

define experimental method

when a deliberate change is made to an IV to measure its affect on the DV

define hypothesis

a clear statement that states the relationship between the variables to be investigated, involves making a prediction

what is an IV

independent variable- thing you alter so you can measure the effect on the DV

non-directional hypothesis

does not state the direction of the relationship

define operationalisation

clearly defining variables in terms of how they can be measured

variable

any ‘thing’ that can change within an investigation

one-tailed hypothesis

directional

two-tailed hypothesis

non-directional

name the three types of hypothesis

• null

• alternative

• experimental

name 3 research issues

1. extraneous variables

2. demand characteristics

3. investigator effects

list ways of dealing with EV

1. randomisation

2. standardisation

3. control groups

4. counterbalancing

what is standardisation

using the exact same formulised procedure and instructions for all participants in a study

what is counter balancing

assigning half the participants to each condition then swapping them (ABBA)

list different kinds of EV

• order effects- participants become familiar with test

• participant variables- participants differ in each group

• situational variables- eg, time of day

• investigator effects- when behaviour of researcher effects the DV

• demand characteristics- participants guess the true aim of the study and behave accordingly to please the experimenter

name and explain the experimental designs

1. independent group design- participants allocated different groups each with different conditions

2. repeated measures design- all participants take part in all conditions of experiment

3. matched pairs design- pairs of participants matched up on variables that may effect the DV, then one pttp assigned to condition A and the other to condition B

evaluation for independent group design

weakness:

• susceptible to participant variables

• the participants who occupy different groups are not the same in terms of participant variables and this could be the effect on the DV- not the different conditions of each group (IV)

• dealt with random allocation

strength:

• order effects are not a problem

• demand characteristics are less of an issue

evaluation of repeated measures design

strength:

• participant variables are controlled

weakness:

• order effects- dealt with by counterbalancing

• order effects because of two reasons

  • order of tasks may have significance- eg, improve skill

  • pttps may become fatigued or bored which affects performance

• demand characteristics

evaluation of matched pairs design

strength:

• less order effects and demand characteristics

weakness:

• time consuming and expensive

• pttps can never be matched exactly

name the types of experiments

1. lab

2. field

3. natural

4. quasi

discuss lab experiments

conducted in highly controlled environments- not always an actual lab

strengths:

• high control over EVs meaning there is high internal validity

• highly replicable

weaknesses:

• lack generalisability

• they do not always reflect everyday life so pttps may act differently so behaviour cannot be generalised beyond research setting meaning low external validity

• risk of demand characteristics

discuss field experiments

the IV is deliberately changed in a more natural setting

strength:

• high ecological validity/ high external validity

weakness:

• lack of control over EVs

discuss natural experiments

conducted when it is not possible, for ethical or practical reasons, to alter the IV deliberately. Therefore IV varies naturally. DV may be tested in lab but its the IV that is natural- not the setting.

strength:

• allows researchers to study events that would be unethical to create in a controlled environment

weakness:

• naturally occurring events may be rare

• lack of control over IV and EVs

discuss quasi experiments

pre-determined IV. the criteria is selected by researcher

strengths:

• often only practical and ethical way to study

weakness:

• inability to establish a clear cause and effect relationship

name the sampling methods

1. random

2. stratified

3. systematic

4. opportunity

5. volunteer

discuss random sampling

all members of the population have an equal chance of being picked

strengths:

• no bias

weakness:

time consuming

discuss systematic sampling

use a pre-determined system to select participants

strength:

• unbiased

weakness:

• time consuming

• not truly unbiased

discuss stratified sampling

subgroups within a population are identified. pttps obtained in proportion to the population, selection done using a random technique.

strengths:

• representative

weakness:

• time consuming

• not perfect representation

discuss opportunity sampling

recruit those most available, reliable or convenient

strength:

• convenient

weakness:

• bias

discuss volunteer sampling

participants selecting themselves to be part of the sample

strength:

• economical, less time consuming

weakness:

• volunteer bias

list ethical issues

1. informed consent

2. deception

3. protection from harm

4. privacy and confidentiality

list factors to deal with ethical issues

1. informed consent

   1. presumptive consent= assuming they would consent based on answers given by target population

   2. retrospective consent= given after study takes place

   3. prior general consent= agreeing to take part in studies which they may be deceived in

2. deception

   1. study to be approved by ethics committee

   2. debriefing and reminder of right to withdraw

3. protection from harm

   1. stop study if harm is suspected

4. confidentiality

   1. use numbers or initials instead of true names

5. privacy

   1. do not observe people without informed consent

what is the BPS code of ethics

a set of ethical guidelines to be observed by researchers

what is a cost benefit analysis

weighing up the cost of doing the research against the benefits

what is a pilot study

a small scale trial run of the actual study

what are the benefits or aims of piloting

• using a few participants

• the aim is to reveal any flaws in the research study

• saves a lot of time and resources and money

• improves the reliability and validity of the design

what is a single blind procedure

when participants are unclear of the aim and conditions of the study

what is a double blind procedure

the participant and investigator is unaware of the conditions and aims of the study

list 6 observational techniques

1. naturalistic

2. controlled

3. overt

4. covert

5. participant

6. non-participant

evaluate naturalistic observational technique

strength:

• high external validity as findings can be generalised to everyday life

weakness:

• lack of control makes replication difficult

• uncontrolled EVs

evaluate controlled observational technique

strength:

• less EVs so easier to replicate

weakness:

• low external validity

• can’t be applied to everyday life

evaluate overt observational technique

strength:

• more ethical

weakness:

• low internal validity- social desirability or demand characteristics

evaluate covert observational technique

strength:

• reduces demand characteristics

• increases internal validity

weakness:

• unethical

evaluate participant observational technique

strength:

• researcher experiences things participants do so it may increase internal validity

weakness:

• researcher may lose objectivity (low internal validity)

evaluate non-participant observational technique

strength:

• high internal validity

weakness:

• lose insight (low external validity)

unstructured vs structured observation

unstructured= recording all behaviour relevant with no system

• too much to record

structured= use of behavioural categories and sampling

• have to be clear and objective

• cover all possible behaviours

evaluate questionnaires

strengths:

• cost effective

• can gather large amounts of data quickly as they can be distributed to large numbers of people

• can be completed without the researcher being present

• data is usually closed questions so it is easy to analyse and compare

limitations:

• responses given may not always be truthful

• social desirability focus

• response bias (eg- always ticking yes)

evaluate structured interviews

strengths:

• straightforward to replicate due to standardised format

• format reduces differences between interviewers

weakness:

• not possible for interviewers to deviate from topic which will limit richness of data

evaluate unstructured interviews

strength:

• more flexibility

• more detailed data

limitations:

• can lead to interviewer bias

• harder to analyse

• can include irrelevant info

• risk of social desirability

what are the two types of interviews

structured and unstructured

what two questions can a questionnaire involve

open and closed

what things should you consider when writing good questions

• avoiding use of jargon

• avoid emotive language and leading questions

• avoid double-barrelled and double negatives (eg- i am not unhappy at my job)

define correlation

illustrates the strength and direction between two or more co-variables (things that are being measured)

how are correlations plotted

on a scattergram

what is negative correlation

when one variable changes, the other changes in the opposite direction

what is a positive correlation

when one co-variable changes, the other does in the same direction

what does zero correlation mean

there is no relationship between co-variables

what does the (PMCC) value ,r, suggest about the correlation

-1 = strong negative

-0.5 = moderate/weak negative

0 = no correlation

0.5 = moderate/ weak positive

1 = positive

strengths of correlations

• provide a precise and quantifiable measure of how two variables are related

• identify strong patterns if variables are strongly related

• relatively quick and economical to carry out

• can use secondary data

• no need for a controlled environment

weaknesses of correlations

• as a result of lack of control over extraneous variables, correlations cannot show a cause and effect- they only show they are related but not why

what are the four types of correlation

1. positive

2. negative

3. no correlation

4. curvilinear

what are 4 types of data

1. quantitative

2. qualitative

3. primary

4. secondary

evaluate quantitative data

strength=

• relatively easy to analyse

• easy to compare data

• objective data- no bias

weakness=

• may fail to represent real life as it is less detailed

evaluate qualitative data

strength=

• more detailed= greater external validity

• provides researcher with more valuable insight

weakness=

• difficult to analyse

• subjective data- can lead to researcher bias

evaluate primary data

strength=

• specifically targets info that the researcher requires

weakness=

• takes time and effort and money

evaluate secondary data

strength=

• quick and easy

• inexpensive

weakness=

• variation in quality and accuracy of data

• it is not always specific to researcher

• data may be outdated which challenges validity of any conclusions

what are the two measures

1. measures of central tendency

2. measures of dispersion

what is the measures of central tendency and list 3 of them

‘averages’ which give us information on the most typical values in a data set

1. mean

2. median

3. mode

what is the measures of dispersion and list 2 of them

concerned with the spread of data in a data set- how far data differs from one to another

1. range

2. standard deviation

ways to present quantitative data

• histograms

• scattergrams

• bar chart

what are the two types of distribution

1. normal

2. skewed

describe normal distribution

• a symmetrical spread of data and frequency that shows a bell curve

• the mean, median and mode are always located at the highest peak

• the ‘tails’ never touch zero on the bell curve

• most items/values lie in the middle of the curve with only extreme values at the ends

define skewed distribution

a spread of frequency of data that is not symmetrical, data clusters at one end

describe positive skewed

• the long tail is on the right and data clusters on the left

• the mode is at the tip of the curve, then the median next, then the mean more towards the tail

describe a negative skewed

• the long tail is on the left and data clusters on the right

• the mean is pulled to the left, the mode on the peak and the median in the middle of them