Research Methods

Aims: 

• general statements that describe the purpose of an investigation. e.g., 'To investigate whether drinking energy drinks makes people more talkative.' 

Hypotheses: 

• a statement that is made at the start of the study and clearly states the relationship between variables as stated by the theory. 

• In a directional hypothesis the researcher makes clear the sort of difference that is anticipated between two conditions.  

• A non-directional hypothesis simply states that there is a difference between conditions or groups but, unlike in a directional hypothesis, the nature of the difference is not specified.  

• Psychologists tend to use a directional hypothesis when the findings of previous research studies suggest a particular outcome. When there is no previous research, or findings from earlier studies are contradictory, they will instead decide to use a non-directional hypothesis.
  

Levels of IV: 

• In order to test the IV, we need different experimental conditions. The two conditions are the control group and the experimental group.  

Operationalisation of variables: 

• one of the main tasks for the researcher is to ensure that the variables being investigated are as clear and measurable as possible. 

Extraneous variables: 

• The key to an experiment is that an IV is manipulated to see how this affects the DV. Any other variables that might potentially interfere should be removed. These additional variables are called extraneous variables. Extraneous variables don’t vary systematically with the DV 

Confounding variables: 

• Any variable, other than the IV, that may have affected the DV so we cannot be sure of the true source of changes to the DV. Confounding variables vary systematically with the DV. 

Demand characteristics: 

• Any clue from the researcher or from the research situation that may give clues to Ps, revealing the purpose of the investigation - may lead to a P changing their behaviour. 

Investigator effects: 

• Any effect of the investigator's behaviour on the research outcome - everything from the design of the study to the interaction with Ps during the research process.  

Randomisation: 

• The use of chance to control the effects of bias when designing materials and deciding the order of conditions.  

Standardisation:  

• Using the same formalised procedures and instructions for all P in a research study. 

Independent group design: 

• Ps are allocated to separate groups where each group represents one experimental condition. 

• Ps who occupy the different groups are not the same. If a researcher finds a mean difference between the groups on the DV this may have more to do with individual differences than the effects of the IV. 

• less economical than rep Mes as each P contributes a single result only. Twice as many Ps would be needed to produce equivalent data to that collected in a rep Mes design. 

• order effects are not a problem. 

• Ps are also less likely to guess the aims. 

Repeated measures: 

• All Ps take part in all conditions of the experiment. 

• Each P must do at least two tasks and the order of these tasks may be significant. To deal with this, researchers use counterbalancing. 

• Order effects also arise because repeating two tasks could create boredom or fatigue that might cause deterioration in performance on the second task. Alternatively, P's performance may improve through the effects of practice, especially on a skill-based task. 

• More likely Ps will work out the aim of the study when they experience all conditions of the experiment. (DCs arise) 

• The strengths of using repeated measures are that P variables are controlled, and fewer Ps are needed.  

Matched pairs design: 

• Pairs of Ps are first matched on key variables that may affect the DV. Then, one member of the pair is assigned to condition A and the other to condition B. 

• Ps only take part in a single condition, so less order effects and demand characteristics. 

• some attempt to reduce P variables in this design, Ps can never be matched exactly. 

• Matching may be time-consuming and expensive, particularly if a pre-test is required, so this is less economical than other designs. 

Random allocation: 

• An attempt to control participant variables in an independent groups design which ensures that each P has the same chance of being in one condition as the other.  

Counterbalancing: 

• An attempt to control the effects of order in a repeated measures design: half the participants experience the conditions in one order, and the other half in the opposite order. 

Laboratory experiments 

• An experiment that takes place in a controlled environment within which the researcher manipulates the IV and records the effect on the DV, whilst maintaining strict control of EVs. 

• High control over EVs. This means that the researcher can ensure that any effect on the DV is likely to be the result of IV manipulation= more certain about demonstrating c + e (high internal validity). 

• Replication is more possible because of the high level of control.  

• Lab experiments may lack generalisability. (Artificial setting).  

• Ps may respond to demand characteristics. 

• Low mundane realism. 

Field experiments  

• In field experiments the IV is manipulated in a natural, more everyday setting. 

• Field experiments have higher mundane realism because the environment is more natural - may produce behaviour that is more valid and authentic. This is especially the case as Ps may be unaware they are being studied (high external validity). 

• loss of control of extraneous variables. This means cause and effect between the IV and the DV in field studies may be more difficult to establish and precise replication is not possible.  

• If Ps are unaware they are being studied, they cannot consent to being studied and such research might constitute an invasion of privacy. 

Natural experiments 

• Natural experiments are when the researcher takes advantage of a pre-existing independent variable. This kind of experiment is called 'natural' because the variable would have changed even if the experimenter were not interested. 

• Opportunities for research that has practical or ethical complications. 

• High external validity because they involve the study of real-life issues and problems as they happen. 

• A naturally occurring event may only happen very rarely, reducing the opportunities for research. 

• Ps may not be randomly allocated to experimental conditions. 

Quasi-experiments 

• Have an IV that is based on an existing difference between people. For instance, if the anxiety levels of phobic and non-phobic patients were compared, the IV pf 'having a phobia' would not have come about through any experimental manipulation.  

• Quasi-experiments are often carried out under controlled conditions and therefore share the strengths of a lab experiment. 

• Quasi-experiments cannot randomly allocate Ps to conditions and there may be confounding variables. 

Populations and samples 

• The population: A group of people who are the focus of the researcher's interest, from which a smaller sample is drawn. 

• For practical and economic reasons, it is usually not possible to include all members of a target population in an investigation, so a researcher selects a smaller group, known as the sample.  

• Ideally, the sample that is drawn will be representative of the target population so that generalisation of findings becomes possible. 

•  often difficult to represent populations - most samples contain some degree of bias.  

• Samples are selected using a sampling technique that aims to produce a representative sample. 

Random Sample 

• A form of sampling in which all members of the target population have an equal chance of being selected. 

• 1) a complete list of all members of the target population is obtained. 2) all the names on the list are assigned a number. 3) the sample is generated using some lottery method (computer randomiser or picking numbers from a hat). 

• Free from researcher bias. They have no influence over who is selected, and this prevents them from choosing people who they think will fit their hypothesis. 

• difficult and time-consuming to conduct. A complete list of the target population may be difficult to obtain. 

•  may end up with a sample that is still unrepresentative.  

• Selected Ps may refuse to take part. 

Systematic sample 

• when every nth member of the target population is selected, e.g., every 3rd house. 

• A sampling frame is produced, which is a list of people in the target population organised into, for instance, alphabetical order. A sampling system is nominated, or this interval may be determined randomly to reduce bias. The researcher then works through the sampling frame until the sample is complete.  

• The sampling method avoids researcher bias. Once the system for selection has been established the researcher has no influence over who is chosen.  

•  usually fairly representative. 

Stratified sample 

• form of sampling in which the composition of the sample reflects the proportion of people in certain sub-groups within the target population or the wider population.  

• Researcher first identifies the different strata that make up the wider population, the proportions needed for the sample to be representative are worked out, the Ps that make up each stratum are selected using random sampling. 

• avoids researcher bias. Once the target population has been sub-divided into strata, the Ps that make up the numbers are randomly selected and beyond the influence of the researcher.  

• produces a representative sample because it is designed to accurately reflect the composition of the population. This means that generalisation of findings becomes possible.  

• The identified strata cannot reflect all the ways that people are different, so complete representation of the target population is not possible. 

Opportunity sample 

• Given that representative samples of the target population are so difficult to obtain, many researchers simply decide to select anyone who happens to be willing and available.  

• saves a researcher a good deal of time and effort and is much less costly in opportunity cost than other sampling methods.  

• sample is unrepresentative of the target population as it is drawn from a specific area, so findings cannot be generalised to the target population.  

• Researchers have complete control over the selection of Ps (researcher bias).

Volunteer sample 

• A volunteer sample involves Ps selecting themselves to be part of the sample; hence, it is also referred to as self-selection. 

• Researchers may place an advert in a newspaper or willing Ps may simply raise their hand when the researcher asks. 

• Collecting a volunteer sample is easy. It requires minimal input from the researcher and do is less time-consuming than other forms of sampling.  

• Volunteer bias is a problem. Asking for volunteers may attract a certain 'profile' of a person, that is, one who is helpful, keen and curious; this also affects generalisation.

Ethical issues:  

• These arise when a conflict exists between the rights of Ps in research studies and the goals of research to produce authentic, valid, and worthwhile data. 

Informed consent:  

• Involves making Ps aware of the aims of research, the procedures, their rights (inc. the right to withdraw), and what their data will be used for. Ps should make an informed judgement whether to take part without being coerced or feeling obliged.  

Deception:  

• Means deliberately misleading or withholding information from Ps at any stage of the investigation. Ps who have not received adequate information when they agreed to take part cannot be said to have given informed consent. 

Protection from harm: 

• Ps should not be placed at any more risk than they would be their daily lives and should be protected from any harm. Ps are to be reminded of their right to withdraw.  

Privacy and confidentiality:  

• Ps have the right to control information about themselves. This is the right of privacy. Confidentiality refers to our right, under the Data Protection Act, to have any personal data protected. 

Pilot studies 

• a small-scale version of an investigation that takes place before the real thing is conducted. The aim is to check that procedures, materials, measuring scales etc. work and to allow the researcher to make changes or modifications. 

Single blind: 

• Ps will not be told the aim of the study. Other details may be kept from Ps, such as which condition of the experiment they are in or whether there is another condition at all. This is an attempt to control the confounding effects of demand characteristics.  

Double blind: 

• participants + researcher aren’t aware of the aims of the investigation. E.g., drug trials. Treatment may be administered to patients by someone who is independent of the investigation and who does not know which drugs are real and which are placebos. 

Observations 

• Observations provide psychologists with a way of seeing what people do without having to ask them. Allow researchers to study observable behaviour within a natural or controlled setting. Gives researchers the flexibility to study more complex interactions between variables in a more natural way.  

• Note that observation is often used within an experiment as a way, for example, of assessing the DV. 

• A mathematical technique in which a researcher investigates an association between two variables, called co-variables.  

• Correlation illustrates the strength and direction of an association between two or more co-variables - plotted on a scattergram.  

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

•  may suggest ideas for possible future research if variables are strongly related or demonstrate an interesting pattern 

• Correlations are quick and economical to carry out.  

• no need for a controlled environment and no manipulation of variables is required.  

• Data collected by others can be used, correlations are less time-consuming than experimenters. 

• cannot demonstrate cause and effect between variables  

• Maybe another untested variable is causing the relationship between the two co-variables - an intervening variable.  

• correlations can occasionally be misused or misinterpreted 

Co-variables:  

• The variables investigated within a correlation, for example height and weight.  

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 correlations and experiments 

• In an experiment the researcher controls or manipulates the IV to measure the effect on the DV. As a result of this it is possible to infer that the IV caused any observed changes in the DV. 

• 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. 

Qualitative data:  

• Data that is expressed in words and non-numerical. (a transcript from an interview, extract from a diary, notes within a counselling session).  

Quantitative data:  

• data that is expressed numerically, is open to being analysed statistically and can be easily converted into graphs, charts, etc. 

Measures of central tendency:  

• The use of graphs, tables, and summary statistics to identify trends and analyse sets of data.