Research methods Flashcards
AIM =
A general expression of what the researcher intends to investigate
HYPOTHESIS =
A statement of what the researcher believes to be true. It should be operationalised (clearly defined and measurable)
DIRECTION AND NON-DIRECTIONAL HYPOTHESIS
Directional hypothesis = states whether changes are greater or lesser, positive or negative
Non-directional hypothesis = does not state the direction; just that there is a difference, correlation, association
EXPERIMENTAL METHOD
A researcher causes the independent variable (IV) to vary and records the effect of the IV on the dependent variable (DV)
EXTRANEOUS VARIABLES (EVs) - research issue
Nuisance variables that do not vary systematically with the IV. A research may control some of these
CONFOUNDING VARIABLES (CVs) - research issue
Change systematically with the IV so we cannot be sure if any observed change in the DV is due to the CV or IV. CVs must be controlled
DEMAND CHARACTERISTICS - research issue
Refers to any cue from the researcher or research situation that may reveal the aim of the study.
INVESTIGATOR EFFECTS - research issue
Any effects of the investigators behaviour on the outcome of the research (the DV)
RANDOMISATION - research techniques
The use of chance when designing investigations to control for the effects of bias
STANDARDISATION - research techniques
Using exactly the same formalised procedures for all participants in a research study
CONTROL GROUP - research techniques
Used for the purpose of setting a comparison
SINGLE BLIND & DOUBLE BLIND - research techniques
Single blind = A participant does not know the aims of the study so that demand characteristics are reduced
Double blind = Both participant and researcher does not know the aims of the study to reduce demand characteristics and investigator effects
INDEPENDENT GROUPS - research technique
One group do condition A and a second group do condition B. Participants should be randomly allocated to experimental groups
+ No order effects = participants are only tested once so cannot practise or become bored/tired
+ Will not guess the aim = participants only tested once so are unlikely to guess the research aims. Behaviour is more ‘natural’
- Participant variables = participants in the two groups are different - act as EV/CV
- More participants = need twice as many participants as repeated measures for same data. More time spent recruiting - expensive
REPEATED MEASURES - research technique
Some participants take part in all conditions of an experiment. The order of conditions should be counterbalanced
+ Participant variables = person in both conditions has the same characteristics
+ Fewer participants = half the participants are needed than in independent groups. less time spent recruiting participants
- Order effects = are a problem - participants may do better or worse when doing a similar task twice. Reduces validity of results
- Participants may guess aims = participants may change their behaviour - reduces validity of results
MATCHED PAIRS - research technique
Two groups of participants are used, but they are related to each other by being paired on participant variables that matter for the experiment
+ Participant variables = participants matched on a variable that is relevant to the experiment - enhances the validity of the results
+ No order effects = participants are only tested once so no practise effects - enhances validity of results
- Matching is not perfect = time-consuming - may not address participant variables
- More participants = twice as many participants as repeated measures - time spent recruiting - expensive
LABORATORY EXPERIMENT - type of experiment
A controlled environment where extraneous variables and confounding variables can be regulated. Participants go to the researcher. The IV is manipulated and the effect of the DV is recorded
+ EVs & CVs can be controlled = means the effects can be minimised - cause and effect between the IV and DV can be demonstrated - high internal validity
+ Can be easily replicated = Due to standardised procedures, the experiment can be repeated.
- May lack generalisability = controlled lab environment may be rather artificial and participants are aware they are being studied. Behaviour may not be natural - cannot be generalised to everyday - low external validity
- Demand characteristics = cues in the environmental situation invite a particular response from participants
FIELD EXPERIMENT - type of experiment
A natural setting. Researcher goes to participants. The IV is manipulated and the effect of the DV is recorded
+ More natural experiment = participants are more comfortable in their own environment - results are generalisable to everyday life
+ Participants are unaware of being studied = more likely to behave as they normally do so the findings can be generalised - greater external validity
- Ethical issues = participants may have no given informed consent - invasion of privacy
NATURAL EXPERIMENT - type of experiment
The experimenter does not manipulate the IV. DV may be naturally occurring
+ May be the only ethical option = may be unethical to manipulate the IV
+ Greater external validity = involves real life issues - findings are relevant to real life issues
- Natural event may only occur rarely = many natural events are ‘one-offs’ which reduces the opportunity for research
- Participants are not randomly allocated = experimenter has no control over which participants are placed in which condition as the IV is pre-existing
QUASI-EXPERIMENT - type of experiment
IV is based on pre-existing difference between people e.g age or gender. No one has manipulated this variable, it simply exists. DV may be naturally occurring
+ Often high control = carried out under controlled conditions - increased confidence about drawing conclusions
+ Comparison made between people = IV is the difference between people - means comparison between different types of people can be made
- Participants are not randomly allocated = experimenter has no control over which participants are placed in which conditions
- Casual relationships are not demonstrated = researcher does not manipulate/control the IV.
POPULATION - sampling
Large groups of people that a researcher is interested in studying.
SAMPLE - sampling
It is not usually possible to include all members of the population in the study, so a smaller group is selected - the sample
GENERALISATION - sampling
The sample that is drawn should be representative of the population so generalisations can be made
BIAS - sampling
The majority of samples are biased in that certain groups may be over or under-represented
OPPORTUNITY SAMPLE - sampling
People who are simply most available e.g the ones nearest/easiest to obtain
How? Ask people nearby
+ Quick method = convenient because you just make use of the people who are closest - makes it the most popular method
- Inevitably biased = sample is unrepresentative of the target population as it is drawn from a very specific area- means findings cannot be generalised
VOLUNTEER SAMPLE - sampling
Participants select themselves
How? Advertise
+ Participants are willing = participants have selected themselves and know how much time and effort is involved - likely to engage more people stopped in the street
- Likely to be a biased sample = participants may share certain traits e.g keen and curious. Generalisation limited due to volunteer biased
RANDOM SAMPLE - sampling
Every person in the target population has an equal chance of being selected.
How? Lottery method - all members of the target population are given a number and placed in a hat
+ Potentially unbiased = researcher has no influence over who is selected - free from researcher bias
- Representation not guaranteed - still possible that a random method may provide a biased sample - limits ability to generalise
SYSTEMATIC SAMPLE - sampling
Participants are selected using a set ‘pattern’ (sampling frame)
How? Every nth person is selected from a list of the target population
+ Unbiased = first item is usually selected at random - objective method
- Time and effect = a list of the population is required - may as well use random sampling
STRATIFIED SAMPLE - sampling
Participants are selected according to their frequency in the target population
How? Subgroups are identified, such as age groups or gender. The relative percentages of the subgroups in the population are reflected in the sample
+ Representative method = characteristics of target population are represented - generalisability more likely than other methods
- Stratification is not perfect = cannot reflect all the ways in which people are different
OBSERVATIONAL TECHNIQUES - observation
A way of seeing or listening to what people do without having to ask them. Observation is often used within an experiment as a way of assessing the DV.
+ Can capture unexpected behaviour = people often act differently from how they say they will in self-report techniques - observations are useful - give insight into spontaneous behaviour
- Risk of observer bias = researchers interpretation of the situation may be offered by expectations - bias can be reduced using more than one observer
NATURALISTIC - observation
Takes place where the target behaviour would normally occur
+ High external validity = in a natural context, behaviour is likely to be spontaneous. More generalisable to everyday life
- Low control = there may be uncontrolled EVs - makesit more difficult to detect patterns
COVERT - observation
Participants are unaware they are being stratified.
+ Demand characteristics = participants do not know they are being studied, so their behaviour will be more natural - increases validity of the findings
- Ethically questionable = people may not want behaviour recorded, even in public. Participants rights to privacy may be affected
OVERT - observation
Participants are aware of being studied
+ More ethically acceptable = participants have given their consent to be studied - have the right to withdraw if they want
- Demand characteristics = knowledge of being studied influences behaviour - reduces validity of findings
PARTICIPANT - observation
When the researcher becomes apart of the group they are studying
+ Can lead to greater insight = researcher experiences the situation as the participants do - enhances the validity of findings
- Possible loss of objectivity = researcher may identity too strongly with those they are studying - threatens the validity of the findings
NON-PARTICIPANT - observation
When the researcher remains separate from the group they are studying
+ More objective = researcher maintains an objective distance to less chance of bias - may increase validity of findings
- Loss of insight = researcher may be too far removed from those they are studying - may reduce validity of findings
BEHAVIOURAL CATEGORIES - observation
The target behaviour to be observed should be broken up into a set of observable categories
TIME SAMPLING - observation
Observations are made at regular intervals e.g every 25 seconds
+ Reduces the number of observations = data is recorded at certain intervals - more structured and systematic
- May be unrepresentative = researcher may miss important details outside of the time-scale - may not reflect the whole behaviour
EVENT SAMPLING - observation
A target behaviour/event is recorded each time it occurs
+ May record infrequent behaviour = researcher will still ‘pick up’ behaviours that do not occur at regular intervals - such behaviours could easily be missed using time-sampling
- Complex behaviour oversimplified = if the event is too complex, important details may go unrecorded - affect validity of findings
QUANTITATIVE DATA - types of data
Numerical data e.g reaction time
+ Easier to analyse = can draw graphs and calculate averages - can ‘eyeball’ data and see patterns at a glance
- Oversimplifies behaviour = e,g using the rating scale to express feelings - means individual meanings are lost
QUALITATIVE DATA - types of data
Non-numerical data expressed in words
+ Represents complexities = more detail included can also include information that is unexpected
- Less easy to analyse = large amount of detail is difficult to summarise - difficult to draw conclusions
PRIMARY DATA - types of data
First hand data collected for the purpose of an investigation
+ Fits the job = study designed to extract only the data needed - information is directly relevant to research aims
- Requires time and effort = design may involve planning and preparation - secondary data can be accessed within minutes
SECONDARY DATA - types of data
Collected by someone other than the person who is conducting the research
+ Inexpensive = desired information may already exist - requires minimal effort
- Quality may be poor = information outdated or incomplete - challenges the validity of the conclusions
META-ANALYSIS - types of data
A type of secondary data that involves combining data from a large number of studies
+ Increases validity of conclusions = eventual sample size is much larger than individual samples - increases the extent to which generalisations can be made
- Publication bias = researchers may not select all relevant studies, leaving out negative or non-significant results - data may be biased as it only represents some of the data and incorrect conclusions are drawn
MEAN - measures of central tendency
Arithmetic average, add up all the scores and divide by the numbers of scores
+ Sensitive = includes all the scores in the data set within the calculation - more of an overall impression of average than median or mode
- May be unrepresentative = one very large or small number makes it distorted - median or mode tend not to be so easily distorted
MEDIAN - measures of central tendency
Middle value, place scores in the ascending order and select middle value. If there are two values in the middle, the mean is calculated
+ Unaffected by extreme scores = median only focuses on the middle value - more representative of the data set as a whole
- Less sensitive than the mean = not all scores are included in the calculation of the median - extreme values may be important
MODE - measures of central tendency
Most frequent or common value, used with categorical/nominal data
+ Relevant to categorical data = when data is represented in categories, sometimes the mode is the only appropriate measure
- An overly simple measure = there may be many modes in a data set. It is not a useful way of describing data when there are many modes
RANGE - measures of dispersion
Difference between highest and lowest value
+ Easy to calculate = arrange values in order and subtract largest from smallest. Simple formula, easier than SD
- Does not account = for the distribution of the scores - the range does not indicate whether most numbers are closely grouped around the mean or spread out evenly. Standard deviation is a better measure of dispersion
STANDARD DEVIATION - measures of dispersion
Measure of the average speed around the mean. The longer the standard deviation, the more spread out the data are
+ More precise than the range = includes all the values with the calculation. A more accurate picture of the overall distribution of the set of data
- It may be misleading = may ‘hide’ some of the characteristics of the data set. Extreme values may not be revealed, unlike the range
QUESTIONNAIRES - self-report technique
Made up of a pre-set list of written questions to which a participant responds. Can be used in an experiment to assess the DV.
+ Can be distributed to lots of people = can gather large amounts of data quickly. Reduces effort involved and it cost-effective
+ Respondents may be willing to ‘open up’ = share more personal information than in an interview - less self-conscious
- Respondents may not always be truthful = tend to represent themselves in a positive light - social desirability bias is possible
- Response bias = respondents may favour a particular kind of response e.g always agree
INTERVIEWS - self-report technique
Face-to-face interaction between interviewer and interviewee
Types - structured and unstructured
STRUCTURED INTERVIEW - self-report technique
List of pre-determined questions asked in a fixed order
+ Easy to replicate = because of standardised format - reduces differences between interviews
- Interviews cannot elaborate = interviewees cannot deviate the topic or elaborate their points - may be a source of frustration
UNSTRUCTURED INTERVIEW - self-report technique
There are no set of questions. There is a general topic to be discussed but the interaction if free-flowing and the interviewee is encouraged to elaborate
+ Greater flexibility = points can be followed up as they arise - more likely to gain insight into the interviewees views
- Difficult to replicate = lack structure and are not standardised - greater risk of interviewer bias
SEMI-STRUCTURED INTERVIEW - self-report technique
List of questions that have been worked out in advance but interviewers are free to ask follow-up questions when appropriate
CLOSED QUESTIONS - design of questionnaires
Respondent has limited choices. Data are quantitative
+ Easier to analyse = can produce graphs and charts for comparison - makes it easier to draw conclusions
- Respondents are restricted = forced into an answer that may not be representative of true feelings - may reduce validity of findings
OPEN QUESTIONS - design of questionnaires
Respondents provide their own answers expressed in words. Date is qualitative
+ Respondents not restricted = answers more likely to provide detailed, unpredictive information - likely to have more validity than statistics
- Difficult to analyse = wider variety of answers than produced by quantitative data - may be forced to reduce data to statistics
PILOT STUDIES
Used in all types of research
Trail run = A pilot study is a small-scale trail run of a research design before doing the real thing
Aim of piloting = To find out if certain things don’t work so you can correct them before spending time and money on the real thing
DISTRIBUTIONS - Graphs
Normal distribution = symmetrical bell-shaped curve. Most people are in the middle area of the curve with very few at the extreme ends. The mean, median and mode all occupy the same mid-point of the curve
SKEWED DISTRIBUTIONS - graphs
Skewed distributions = distributions that lean to one side or the other because most people are either at the lower or upper end of the distribution
Negatively skewed = most of the distribution is concentrated towards the right of the graph - long tail to the left
Positively skewed = most of the distribution is concentrated towards the left of the graph - long tail on the right
Psychology and the economy
The findings of psychological research can benefit our economic prosperity
- Development of treatment for mental illness = a third of all days off work are caused by mental disorders such as depression. Psychological research into the causes and treatments of mental disorders means that patients have their condition diagnosed quickly. Patients have access to therapies or psychotheraputic drugs such as SSRIS - suffers manage their condition effectively, return to work and contribute to the economy.
Correlations
Association = illustrates the strength and direction of an association between two co-variables
Scattergram = correlations are plotted on a scattergram. one co-variable is on the x-axis, the other on the y-axis
Positive correlation = co-variables rise of fall together
Negative correlation = one co-variable rises and the other falls
Zero-correlation = no relationship between the two variables
