Research Methods- Year 1 Flashcards
Why study research methods ?
We need to gather evidence to help develop and support psychological theories
Aim
general statement of what the researcher intends to investigate the purpose of the study.
Hypothesis
A clear, precise and testable statement that states the relationship between the variables to be investigated, stated at the outset of any study
Variables
Factors that change in an investigation. They are usually used in experiments to determine if changes in one thing result in changes to another
Independent variable
Researcher manipulates or it changes naturally so the effect on the DV can be measured
Dependent variable
Is measured by the researcher to see how it changed. Any effect on the DV should be caused by the IV
Levels of the independent variable
In most experiments the IV has two conditions, the control group and the experimental group
Operationalism
Turning abstract concepts from your aim into clearly defined variables that can be measured
Directional hypothesis (one tailed)
States the kind of difference or relationship between the IV and DV.
Non- directional hypothesis (Two tailed)
Simply predicts that there will be a difference between conditions.
How do researchers decide what type of hypothesis to use
- One tailed if previous research suggests an outcome.
- Two tailed if no previous research or it’s inconclusive
Extraneous variable
Any variable other than the IV that may have an effect on the DV (if it is not controlled). They do not vary systematically with the IV
Confounding variable
A kind of extraneous variable that systematically change with the IV.
Any variable other than the IV that may have affected the DV so we cannot be sure of the reason for the DV changing.
Participant variable
any individual differences between participants that may affect DV
Situational variables
any features of the experimental situation that may affect DV
Examples of participant variables
Personality, age, gender, motivation
Examples of situational variables
weather, instructions, temperature, time of day, noise
Demand characteristics
Any cue from the researcher or from the research situation that may be interpreted by participants as revealing the purpose of an investigation. This leads to a participant changing their behaviour within the research situation
Investigator effects
Any effect of the researcher’s behaviour that could change the outcome of the results.
How can we control extraneous and confounding variables ?
- standardisation- All participants should be subject to the same experimental conditions
- Randomisation- Using chance in order to control for the effects of bias in an experiment
Participants
People who take part in research
Population
the group of people from which the sample is drawn
Bias
when certain groups are under-or overrepresented in a sample (not representative)
Random sampling
Every member of the target population has an equal chance of being chosen.
How is random sampling done ?
- compile a list of all target population
- assign each a number
- select a sample using a random number generator
Advantages of random sampling
-No researcher bias
- Confounding variable should be distributed evenly
Disadvantages of random sampling
- Difficult to get a complete list of target population
- time consuming
- participants might not be willing to partake
Systematic sampling
Every nth member of the target population is selected. (e.g. every 5th person on the register)
How is systematic sampling done ?
- create list pf the target population in an order (e.g. alphabetical) - this is a sampling frame.
- take a sample from the list
Advantages of systematic sampling
-objective, avoids researcher bias as there is no influence once the system is chosen
Disadvantages of systematic sampling
- could draw a non-representative sample
- time consuming, costly
- participants may refuse to take part
Stratisfied sampling
composition of the sample reflects proportion of certain subgroups in the target population
How is stratified sampling done ?
- Identify different subgroups in the population
- work out the proportion of each group
- participants in each subgroup are selected randomly in the same proportion as the target population
Advantages of stratified sampling
- avoids researcher bias
- more representative of the whole population so findings are more generalizable
Disadvantages of stratified sampling
- stratification is never perfect, complete representation of population is not possible.
Opportunity sampling
sample from people who are available and willing when the study is carried out.
Advantages of opportunity sampling
- quick
- convinent
Disadvantages of opportunity sampling
- unrepresentable
- researcher bias
Volunteer sampling
self- selected sampling- participants become part of the study when asked or in response to an advert.
advantages of volunteer sampling
- convenient
- less time consuming
- no researcher bias
disadvantages of volunteer sampling
- often unrepresentative- volunteer bias
Experimental design
refers to how you allocate your participants to the different conditions in an experiment
what are the 3 experimental designs
- independent groups
- repeated measures
- matched pairs
Independent groups
Participants only take part in one condition
Requires a separate group for each condition
Results from each group are compared
Advantages of independent groups
- avoids order effects
- Reduces demand characteristics
Disadvantages of independent groups
- needs lots of participants (costly)
-differences between groups may affect the results (random allocation may help to overcome this)
Order effects
When the order of the conditions in an experiment has an effect on particular behaviour
Repeated measures
Participants take part in all conditions
Everyone experiences the control and the experimental condition
Results for the two conditions are then compared.
Advantages of repeated measures
- Avoids participant variables as everyone does all conditions
-fewer people needed
Disadvantages of repeated measures
-Order effect more likely-requires counterbalancing
-Demand characteristics more likely as participants are more likely to guess the aim
counterbalancing
Alternating the order in which participants take part in different conditions
Matched pairs
-Participants are matched in each condition for any characteristics that may affect performance (age,gender,IQ)
-Results are compared between members of each pair
Advantages of matched pairs
Reduces participant variables
reduces order effects and demand characteristics
Disadvantages of matched pairs
Very time consuming - costly
impossible to match pairs exactly (even for twins) may be unexpected confounding variables
Types of experiment
Lab, field, natural, Quasi
What is an experiment ?
There is an IV sometimes manipulated by the researcher
The effects of the IV on the DV are observed or measured so that the hypothesis can be tested
The participants are allocated randomly to the conditions, where possible.
Lab experiments strengths
control extraneous variables- increases objectivity + validity
- can be standardised, easy to replicate
Lab experiments limitations
Artificial conditions-low ecological validity, demand characteristics, experimenter bias, low mundane realism, ethics
Field experiment strengths
Greater ecological validity, more mundane realism, behaviour more valid, fewer demand characteristics
Field experiment limitations
Less control- more possible extraneous variables, harder to replicate, ethics
Natural experiments strengths
High ecological validity, can research areas that would make experiments impossible forethical reasons
natural experiments limitations
Very difficult to replicate, fewer opportunities for research, little control over extraneous variables
Quasi experiments
Not true experiment
IV based on existing differences between people (E.g., age, gender)
Pilot study
small scale version of a study carried out before the main study
BPS code of conduct
In Britain ethical guide- lines for research are published by the British psychological society
informed consent
Participants should be given as much information as possible to enable them to make an informed judgment on whether they will partake
Deception
Should only be used when there is no other alternative
Right to withdraw
participants must know they are free to leave the study at any time (even if they have been paid)
Protection from physical and psychological harm
Participants safety must be ensured
Cannot be exposed to greater risk than in their normal life experiences
Confidentiality
Information about participants is protected by the data protection act
- participants must not be identifiable in published research
-Participants are given numbers or referred to by code
Privacy
Participants right to privacy must be maintained
-Often tricky when conducting observations and participants are unaware they are being observed
-We should only observe people where they would expect to be observed by others in pubic places
Debriefing
Participants should be debriefed following study:
- Allow them to ask questions
- Remind them of the right to withdraw
Dealing with informed consent
-Participants issues with a consent letter or form detailing all relevant information that might affect their decision to participate
-If they are under 16 parents need to sign
What if getting consent would ruin the study ?
- Presumptive
- Prior general
- Retrospective
Right to withhold data
Participants can object to their data being used
Single blind procedure
Participants does not know which experimental condition they are in
Double blind procedure
Participant and researcher do not know which experimental condition the participant is exposed to
observations
watching how people behave without asking them to complete in an experiment
Naturalistic
Watching/recording behaviour in the setting where it would normally take place
-All aspects of the environment are free to vary
Controlled
Watching/recording behaviour in a controlled setting
- control certain variables
Covert
Participants behaviour is watched and recorded without their knowledge or consent
Overt
Participants behaviour is watched and recorded with their knowledge or consent
participant observation
researcher becomes a member of the group whose behaviour they are observing
Non - participant observation
Researcher remains outside of the group whose behaviour they are observing
Issues in observational design
-ways of recording data
-behavioural categories
- sampling methods
Unstructured recording
write down everything you see which provides rich detail - often too much
Structured recording
Target behaviour for a main focus
- allows the researcher to quantify their observations using a pre-determined list of behaviours and damping methods
behavioural categories
targeted behaviour is broken up into components that are observable and measurable.
Target behaviours should be:
-precisely defined
-observable
-measurable
Event sampling
Count the number of times a particular behaviour occurs
Time sampling
Record behaviour with a pre-established time frame
Strengths and limitations of naturalistic
strengths - more external validity, findings can be generalised to real life
limitations- replication is difficult
Controlled strengths and limitations
Strengths - replications is easy due to control
limitations - lacks ecological validity, cannot be generalised
Covert strengths and limitations
Strengths - removes participant reactivity, increases validity
limitations - ethical issues
Overt strengths and limitations
strengths- ethically accepted
Limitations- could increase participant reactivity
Participant strengths and limitations
strengths - researchers experience the whole situation, gives them insight
limitations- lose objectivity
non participant strengths and limitations
Strengths - maintain objective in observations
limitations - may lose insight due to being on the outside
self reporting methods definition
state or explain their own feelings, opinions, behaviours and/or experiences related to a given topic.
Questionnaires
Set of written questions used to assess a persons thoughts and/or experiences.
- May be used to asses the DV
2 types of questions ?
open or closed
Open questions
Provide qualitative data but it’s hard to analyse (rich data)
- Allows people to give opinions and feelings
Closed questions
Fixed choice (yes/no, tick box) provide quantitative data - easy to analyse
Strengths of questionnaires
-cost effective
- large amount of data
- easy to distribute to large numbers of people
- easy to analyse data
Weaknesses of questionnaires
-demand characteristics (social desirability bias)
-response bias (acquiescence bias)
acquiescence bias
tendency to agree with items on a questionnaire regardless of the content of the question
Scale of questionnaires
-likert scale
- rating scale
- fixed choice options
writing good questions
- don’t overuse jargon
- don’t use emotive language or leafing questions
-Don’t use double negative or double barrelled words
Interviews
may be conducted over the phone however most involve face-to-face interactions between interviewer and interviewee
structured interview
made up of pre-determined set of questions that are asked in a fixed order
Unstructured interview
-no set questions
- there is a general aim that a certain topic will be discussed
- interactions are free flowing
Semi structured interview
- a list of questions had been worked out in advance
- interviewers are feee to ask follow up questions
Designing interviews
- interview schedule
- should be standardised to reduce bias
- interviewers usually record/take notes to analyse later
- normally one-to-one
- conducted in quiet rooms
- start with neutral questions
Qualitative data
Data that is expressed in words and non-numerical
Quantitative data
Data that can be counted, usually given as numbers.
primary data
Information that has been obtained first-hand by a researcher for the purposes of a research project. In psychology, such data is often gathered directly from participants as part of an experiment, self-report or observation.
secondary data
Information that has already been collected by someone else and so pre-dates the current research project. In psychology, such data might include the work of other psychologists or government statistics.
Meta analysis
The process of combining the findings from a number of studies on a particular topic. The aim is to produce an overall statistical conclusion (the effect size) based on a range of studies. A meta-analysis should not be confused with a review where a number of studies are compared and discussed
Correlation
A mathematical technique in which a researcher investigates an association between two variables, called co-variables.
Co-variable
Co-variables The variables investigated within a correlation.
Positive correlation
As one co-variable increases so does the other
Negative correlation
As one co-variable increases the other decreases.
Zero correlation
When there is no relationship between the co-variables.
The difference between correlation and experiments
In an experiment the researcher controls or manipulates the independent variable
(IV) in order to measure the effect on the dependent variable
In contrast, in a correlation, there is no such manipulation of one variable and therefore it is not possible to establish cause and effect between one co-variable and another.
Testing the strength of a correlation
We can calculate a correlation coefficient to show how strong the association is between two variables
Correlational hypothesis
Can’t be written the same (no IV or DV)
Bar chart
-results in categories
- also called discrete data or discontinuous data
Histogram
Used when the data is continuous in the form of intervals
Scattergrams
Used to show the relationship between 2 co-variables
- each point usually represents 1 participant
Line graph
used to show a trend
Descriptive statistics
the use of graphs, tables and summary statistics to identify trends and analyse sets of data.
Measures of central tendency
General term for any measure of the average value in a set of data.
Mean
The arithmetic average calculated by adding up all the valued and dividing by how many there are
+ includes all data (representative)
- can become easily distorted by extreme values
Median
The central value in a set of data when values are arranged lowest to highest.
+extreme values don’t affect it, easy to calculate
- less representative
Mode
The most frequently occurring value in a set of data.
+ easy to calculate
- not representative
Measures of dispersion
The general term for any measure of the spread or variation in a set of scores.
Range
Simple calculation of the dispersion in a set of scores which is worked out by subtracting the lowest score from the highest and adding 1 as a mathematic correction
+ easy to calculate
- only take into account extreme values
Standard deviation
Sophisticated measure of dispersion in a set of scores. It tells us by how much on average each score deviated from the mean
+ precise
- distorted by a single extreme value
small standard deviation
scores cluster around the mean
large standard deviation
scores are spread out from the mean
Normal distribution
A symmetrical spread of frequency data that forms on a bell shaped pattern
Skewed distribution
A spread of frequency data that is not symmetrical, where the data clusters to one end
positive skew
frequency distribution in which the long tail is on the positive (right) side of the peak and most of the distribution is concentrated on the left
negative skew
The opposite to a positive skew
Probability
Probability refers the likelihood that the results in a study occurred by chance. The accepted level of probability level used in psychology is 0.05 = 5%
P< 0.05
This means there is less than or equal to, 5% probability the results occurred by chance, or to put it another way we can be 95% certain the results are due to manipulating the independent variable.
The researcher can be pretty certain the difference found was because of the independent variable not just chance.
Requirements for a Sign test
o use the Sign test we need to be looking for a difference in our data sets (not a correlation)
We need to use a repeated measure design in our experiment (we assign each participant with a +, - or = depending on how their performance has changed or not).
We need data that is organised into categories (nominal data)
Calculated and critical value
When the data has been put through the Sign test we are left with a small number
This is known as the calculated value/observed value
This needs to be compared with a critical value (see pg 200) course text book, to establish if the result is significant or not.
Peer Review
The assessment of scientific work by others who are specialists in the same field to ensure that any research intended for publication is of high quality.
What is peer review used for
Validate quality and relevance of research
Suggest amendments or improvements
Allocate research funding
(e.g. by Medical Research Council)
Problems with the Peer Review Process
Anonymity
Reviewers may use anonymity to negatively affect other researchers (their competitors).
Publication Bias
Journals may prefer to publish ‘headline’ research to increase readership of their journal.
Also tend to favour research with positive results.
Maintaining the Status Quo
Reviewers are usually established researchers.
May be less likely to pass innovative research (especially if it contradicts their own research!).
This may slow down the progress of research.
Define ‘economy’
The state of a country or region in terms of the production and consumption of goods and services.
“The implications of psychological research for the economy”
How does psychological research affect, benefit or devalue financial prosperity?
Treatment of mental health disorders
Absence from work estimated to cost £15 billion per year.
1/3 related to mental health (anxiety, depression, stress).
Effective treatment allows patients to manage their conditions and return to work.
Randomisation
the use of chance methods to control for the effects of bias when designing materials and deciding the order of experimental conditions
Standardisation
using exactly the same formalised procedures and instructions for all participants in a research study
