Research Methods - Year 12 Flashcards
What Are Experimental Methods?
These are basically types of experiments that can be conducted,
In a posh way: they attempt to find a cause and effect relationship between an independent variable and a dependent variable,
They also want to measure the extent of this effect.
Four Types Of Experimental Method?
(Four types of experiments that can be conducted):
Laboratory experiments,
Field experiment,
Natural experiment,
Quasi experiment.
Lab Experiments?
- Test effect of the IV on the DV,
- Controls as many variables as possible,
- Can be in any environment as long as it is controlled.
Advantages And Disadvantages Of Lab Experiments?
Advantages:
- High degree of control,
- Replication is easy,
- Cause and effect can be determined easily,
Disadvantages:
- Variables are difficult to control,
- Low ecological validity,
- Demand characteristics,
- Low external validity.
Natural Experiments?
- IV occurs naturally, it is not manipulated by the experimenter,
- Could be an earthquake.
Advantages And Disadvantages Of Natural Experiments?
Advantages:
- More representative,
- No demand characteristics,
- Real life makes it generalisable,
- High ecological validity,
- High external validity.
Disadvantages:
- Harder to replicate,
- Rime consuming and expensive,
- Difficult to replicate.
Field Experiments?
- Experiment performed in the real world rather than a lab.
Advantages And Disadvantages Of Field Experiments?
Advantages:
- High ecological validity,
- Real life so generalisable,
- No demand characteristics,
- Results are more realistic,
Disadvantages:
- Environments may differ,
- Harder to control variables,
- Harder to replicate,
- Ethical issues.
Quasi Experiments?
- When you group individuals into separate groups.
E.g. cannot randomly allocate participants.
Advantages And Disadvantages Of Quasi Experiments?
If the quasi experiment is controlled, the advantages and disadvantages are the same as LAB,
If the quasi experiment is not controlled then the advantages and disadvantages are the same as NATURAL.
Controlled - Advantages: - High degree of control, - Replication is easy, - Cause and effect can be determined easily,
Disadvantages:
- Variables are difficult to control,
- Low ecological validity,
- Demand characteristics,
- Low external validity.
Uncontrolled - Advantages: - More representative, - No demand characteristics, - Real life makes it generalisable, - High ecological validity, - High external validity.
Disadvantages:
- Harder to replicate,
- Rime consuming and expensive,
- Difficult to replicate.
Observational Techniques?
Simply: these are ways a psychologist can observe an experiment.
- Covert or overt,
- Participant or non-participant,
- Naturalistic or controlled,
- Structured or unstructured.
Covert Observations?
- Also known as ‘undisclosed’,
- Observing people without their knowledge,
- Participants might be informed after the study observation has taken place.
Evaluating Covert Observations?
Strength,
- Investigator effects are less likely because the investigator is hidden.
- Less chance the investigator will impact the study directly or indirectly,
- Less chance of demand characteristics occurring from participants,
- Participants behaviour is more representative of their every day behaviour.
Weakness,
- Ethical issues associated with the covert method,
- Participants are not aware they are taking part in a study and therefore cannot give fully informed consent nor exercise their right to withdraw,
- However, it is perfectly acceptable to observe human behaviour in a public place (e.g. shopping centre).
- Internal validity is good.
Overt Observations?
Is an observational technique where the observations are ‘open’ and the participants know/are aware that they are being observed.
E.g. filming or joking a class and informing the other students that you are carrying out an observation.
Evaluating Overt Observations?
Strength,
- The overt method is often more ethical.
- The participants are aware that their behaviour is being observed for the purposes of an investigation.
- It is possible for the participants to give consent. This also allows participants to exercise their right to withdraw themselves from the investigation.
Weakness,
- Investigator affects that reduce the internal validity. - It is possible for a bias to occur whereby what the investigator influences the behaviour of the participants in a way that was not intended.
- The participants may change their behaviour through demand characteristics and act in accordance with their perception of the research aims.
- This reduces the internal validity of the observation.
Participant Observations?
In a participant observation, the person who is conducting the observation also takes part in the activity being observed.
It can be either covert (a group member quietly observing the others without their knowledge) or overt (a group member using a camera to record the other members with their full knowledge.
Evaluating Participant Observations?
Strength,
- The Researcher can obtain in-depth data.
- The observer is in close proximity to the participants, so they are able to gain a unique insight into the phenomenon on in question.
- They are also unlikely to overlook any behaviour that, as an external observer, would be missed.
- This means that a comprehensive understanding of human behaviour can be achieved using this method of observation.
Weakness,
- Possibility of investigator effects and the impact of the researcher on the other participants behaviour.
- The participants may change their behaviour through demand characteristics and act in accordance with their perception of the research aims.
- Consequently, natural behaviour is not being observed, that’s reducing the internal validity of the observation because the investigator is a participant.
Non-Participant Observations?
In a non-participant observation, the person who was conducting the observation does not participate in the activity being observed.
This type of observation is quite common in educational settings, as in teacher evaluations, for example, when an observer sits in the corner of the room and watch is the lesson.
The aim is for the observer to be as an unobtrusive as possible and not engage with any of the activities happening.
Evaluating Non-Participant Observations?
Strength,
- Investigator effects are less likely compared to a participant observation.
- The researcher is often observing at a distance from the participants and in some situations, not visible to them at all.
- The behaviour of the investigator is unlikely to have a negative impact on the behaviour of the participants.
- This means that behaviour observed is more likely to be representative of natural and an altered human behaviour.
Weakness,
- Due to a lack of proximity to the participant behaviour being studied, the researcher might miss behaviours of interest.
- This means that unique insights which contribute to their understanding of the human behaviour being observed will be overlooked because of not being involved personally.
Naturalistic Observations?
Is an observation carried out in an un-altered setting in which the observer does not interfere in any way and merely observes the behaviour in question as it happens normally.
An example of this would be an observer observation carried out in a shopping centre as people go about their daily business.
Evaluating Naturalistic Observations?
Strength,
- A higher level of ecological validly can be achieved.
- In an observation of this type, the researcher records naturally occurring behaviour in the original environment in which it originally occurs. This means that the behaviour being recorded is likely to be more representative of every day activities and reflect spontaneous actions that sometimes occur incidentally.
Weakness,
- There are issues of gaining reliability with naturalistic observations. Since observations of this kind record behaviours which are occurring naturally as they unfold, it is difficult, if not impossible, for the exact same conditions to be replicated.
- Consequently, the test re-test method of checking reliability cannot be used with this type of observational design, as the researcher is not in control of variables.
(Basically, it lacks replicability).
Controlled Observations?
A controlled observation is conducted under strict conditions, such as in an observation room or lab setting, where extraneous variables (such as time, noise, temperature and visual distractions) can be controlled to avoid interference with the behaviour being observed.
Sometimes one way mirrors can be used. If participants know they are being observed, this is an overt method which is most commonly the case for controlled observations.
Evaluating Controlled Observations?
Strength,
- They can be replicated to check for reliability since the conditions are very controlled.
Weakness,
- Lower level of external validity.
- The high level of control creates an unnatural feeling. The participants behaviour may alter in response - meaning that the observation is no longer representing real life occurrences causing the ecological validity of the findings to be questionable.
Structured Observations?
In structured observations, the researcher uses coded schedules according to a previously agreed formula to document the behaviour and organise data into behavioural categories.
A behavioural category is when psychologists must decide which specific behaviours should be examined. This involves breaking the target behaviour (e.g. aggression) into components that can be observed and measured (e.g, hitting + kicking).
Evaluating Structured Observations?
Strength,
- The researcher can compare behaviour between participants and across groups.
- The use of behavioural categories makes the coding of the data more systematic.
- When there is more than one observer, the behaviour schedule results in greater INTER-OBSERVER RELIABILITY.
- It is important for research methodologies to be consistent so that accurate comparisons can be made.
Weakness,
- Problems with gaining high internal validity.
- This is because the researcher may miss some crucial behaviours during the observation which could be important to the aim.
- As a result, the findings portrayed may not provide the full picture about the behaviour in question.
- This is a problem because what was intended to be measured was not achieved and it’s entirety.
Unstructured Observations?
And unstructured observation involves every instance of the observed behaviour being recorded and described in as much detail as possible. This is useful if the behaviour that researchers are interested in does not occur very often.
Common in naturalistic observation.
Evaluating Unstructured Observations?
Strength,
- Richness in data obtained.
- Since behaviour is recorded in great detail, researchers are able to obtain a comprehensive view of human behaviour. This adds to the internal validity of the observational technique.
Weakness,
- This type of observation is also prone to OBSERVER BIAS due to the lack of behavioural categories.
- This is a problem because the observer may then only record behaviour which is of subjective value to them, and not a valid representation of what is being displayed.
- As a result, there may be a problem with INTER-OBSERVER RELIABILITY as there will be a lack of consistency in the observations recorded.
Dependant Variable?
What is being studied in the experiment. This variable DEPENDS on the in-dependant variable.
In-dependant Variable?
This is what is being changed in order to directly affect the dependant variable.
Types Of Observational Design?
Event sampling,
Time sampling,
Behavioural categories.
Time Sampling?
This is where an observer records behaviour at prescribed intervals, e.g. every 10 seconds.
Event Sampling?
This is where the observer records the number of times that the target behaviour occurs, e.g. using a tally.
Time Sampling - Strengths and Weaknesses?
Strength - allow for a better use of time since fewer observations are made. This could result in more accurate data.
Weakness - Not every behaviour of relevance to the investigation will be counted if it occurs in between the time frames allocated.
Event Sampling - Strengths and Weaknesses?
Strength - Every behaviour of relevance in the perspective of the researcher is counted from beginning to end.
Weakness - Possibility that some behaviours could be missed if there is too much happening at the same time, resulting in some not being coded.
What Are Questionnaires?
A type of ‘self-report’ technique, where participants provide information relating to their thoughts, feelings and behaviours.
They can be open, closed or a mixture of both.
Open Questionnaires?
Allow participants to answer however they wish.
This makes qualitative data.
This results in detailed data.
Closed Questionnaires?
Restrict the participant to a predetermined set of responses.
This makes quantitative data.
There are 3 types of closed questions that can be asked in a closed questionnaire:
- Checklist,
- Likert response scale,
- Ranking.
What Is A Checklist?
A type of question that is asked in a closed questionnaire.
This is a type of question where the participants tick the answers that apply to them (basically multiple choice).
What Is A Likert Response Scale?
A type of question that is asked in a closed questionnaire.
This is a type of question where participants rate on a scale their views/opinions on a question.
E.g. circle the number that applies:
1 - Strongly agree, 2 - Agree, 3 - Not sure, 4 - Disagree, 5 - Strongly disagree.
What Is A Ranking Scale?
A type of question that is asked in a closed questionnaire.
This is where participants place a list of items in their preferred order.
E.g. rank the following 4 activity’s in order from your most preferred activity to your least. Scale: 1 = your favourite activity, 4= your least favourite activity.
Evaluation Of Open Questionnaires?
Strength - less chance of researcher bias. This is especially true if the questionnaire is anonymous. There is not a limitation to what you can write (there’s not just a multi choice) so there is less chance of the responses being influenced by the researcher’s expectations.
Weakness - participants might answer in a socially desirable way, where they try to portray themselves in the best possible way to the researcher. This means an open question may lack validity.
Evaluation Of Closed Questionnaire?
Strength - the data is quantitative. This type of data is easy to analyse statistically or in a graphical format. Direct comparisons can be made to compare groups of people or individuals. The researcher can also look for patterns which can lead to further research to be conducted.
Weakness - the researcher is unable to pursue and explore responses that are of particular interest. Closed questions often produce a RESPONSE BIAS. This can happen because the participant doesn’t take time to read all questions properly, e.g. select ‘yes’ for every answer. This means the data collected will LACK VALIDITY.
What Is Important When Designing A Questionnaire?
- Keep the terminology simple and clear.
- Keep it as short as possible.
- Be sensitive; avoid personal questions. If you must, collect personal information at the end.
- Do not use leading questions.
- Do not use questions that make assumptions or sweeping statements.
- Pilot and modify the questionnaire.
What Are Interviews?
Another type of self-report technique which predominately take place on a face-to-face basis, although they can also happen over the telephone.
Three different interview designs:
- Structured interviews,
- Unstructured interviews,
- Semi-structured interviews.
Interviews are usually recorded, with the use of an interview schedule that the interviewer completes and/or audio or video recording, with the informed consent of the interviewees.
Structured Interviews?
Involve the questions decided in advance and they are asked in exactly the same order for each interviewee taking part.
The interviewer uses an interview schedule and will often record the answers to each question by taking notes/ticking boxes on their schedule.
Unstructured Interviews?
Conduced more like a conversation, with the interview only facilitating the discussion rather than asking set questions.
Very little decided in advance (only topic and questions needed to identify the interviewee). Therefore, this type of interview usually produces lots of qualitative data. Answers are usually audio or video recorded. Writing them down would ruin the relaxed atmosphere of this interview and there is too much said to write down.
Evaluation Of Structured Interviews?
Strength - quantitative data is easier to analyse statistically or in a graphical format. Direct comparisons can be made to compare groups of people or individuals. The researcher can also look for patterns which can lead to further research to be conducted.
Strength 2 - this interview is easily replicated to test for reliability because questions are asked in same order each time.
Weakness - investigator effects may play a role when the interview is replicated over so many times. The interviewer may, consciously or unconsciously, bias any responses given to the questions by the tone of voice, intonations, body language. This is based on the interviews perception, and might not be what the interviewee really means.
Evaluation Of Unstructured Interviews?
Can increases the VALIDITY of findings by reducing INVESTIGATOR EFFECTS - the reduction of investigator effects occurs because the investigator has less control over the questions and, therefore, answers. Because of this, it is less likely that participants will display demand characteristics in their interview responses.
Unstructured interviews generate large quantise of qualitative data. This allows the interviewer to gain lots of information on human behaviour. However, this also means that the data takes longer to analyse and is also costly to do so.
Statistical analysis can also be challenging, as the data collected is qualitative, making it more difficult to identify patterns without undergoing a content analysis first.
Semi-Structured Interviews?
Involve mostly prepared questions that can be supplemented with additional questions as seen fit by the interviewer at the time.
The interviewer can deviate from the original questions and consequently, this type of interview also typically produces a large amount of qualitative data.
Evaluation Of Semi-Structured Interviews?
Strength - the use of these interviews can increase VALIDITY of findings. Open questions in these interviews may increase the chance of participants being honest and thus, reducing SOCIAL DESIRABILITY BIAS. Participants are able to justify their answers in their own words with options.
However, the interviewer still retains control over the interview schedule which can cause investigator effects which can effect the behaviour of the participants negatively.
Semi-structured interviews also generate qualitative data. This allows interviewers to clarify the meaning of participants responses and gain further information that is required. This provides a unique insight into explaining human behaviour.
However, as a result of this qualitative data, the analysis of the data can be more difficult, time consuming and expensive to conduct compared to quantitive data.
What Are Correlation Techniques?
Correlational techniques take place in correlational studies.
Correlation techniques are non-experimental methods used to measure how strong the relationship is between two (or more) variables.
There are 3 types of correlation:
- Positive,
- Negative,
- Zero.
In An Experiment, What Is Measured?
In an experiment, the effect of an independent variable upon the dependant variable is measured.
What Is A Correlational Study?
The movement and direction of co-variables in response to each other is measured.
There is no claim of a cause and effect relationship, although after a correlational study has been conducted, further research will often be conducted to determine if one variable is affecting the other.
Positive Correlation?
As one variable increases, the other also increases.
Negative Correlation?
As one variable increases, the other variable decreases.
Zero Correlation?
Occurs when a correlational study finds no relationship between variables.
Correlation Coefficient?
A correlation coefficient is to measure the strength and nature (strength and nature) of the relationship between two co-variables.
The correlation coefficient number is +1 - -1.
The stronger the correlation, the closer the number to +1 - -1.
Perfect negative correlation is -1 and perfect positive correlation is +1.
Scattergram?
A scattergram is a graph that shows the correlation between two sets of data (co-variables) by plotting points to represent each pair of scores.
Indicates the correlation between co-variables.
Evaluation Of Correlational Techniques?
- Correlational studies are an ideal place to begin preliminary research investigations. They measure the strength of a relationship between two or more variables, this provides valuable insight for future research.
This type of analysis can be used when a laboratory experiment would be unethical as the variables are not manipulated, merely correlated. Secondary data can also be used in correlational studies which gets rid of the concern about informed consent as the information is already public.
- There are limitations with using correlational studies. It is not possible to know what the cause and effect is. There is a third variable problem. Correlations also only identify the linear relationships, not the curvilinear.
Third Variable Problem?
This is a problem that occurs with correlation studies and techniques.
This means the researcher is not able to conclude that one variable is the causation of another variable decreasing/increasing. There could be other factors that influence a relationship between two variables.
This other factor is a third variable.
Curvilinear?
The relationship between temperature and aggression is curvilinear.
This means the relationship is positive to a point. However, at very high temperatures, aggression declines.
Writing Aims For Investigations?
E.g.
“To examine the effect of hunger on memory of food-related words”.
There is no specific way you should write it as long as it sounds something like ^.
What Is A Hypothesis?
A clear and precise prediction about the difference or relationship between the variables in a study.
Hypothesis should always contain an operationalised I depend at variable and dependant variable.
There are two types of experimental hypotheses:
- Directional,
- Non-directional.
What Is Operationalisation?
A term used to describe how a variable is clearly defined by the researcher. The term operationalisation can be applied to independent and dependant variables or a co-variable (in a correlational design).
Directional Hypothesis?
Predicts the specific nature of the difference between two or more variables. This prediction is typically based on past research, accepted theory or literature on the topic. A directional hypothesis is sometimes called one-tailed.
E.g. there will be a significant increase in the number of food-related words correctly recalled by participants who are hungry, in comparison with those who are not hungry.
Non-Directional Hypotheses?
Predicts that a difference will exist between the variables without predicting the exact direction of the difference.
These hypotheses are given usually when there is no conclusive research done before this study. These hypotheses are usually called two-tailed.
E.g. there will be a difference in the number of food-related words correctly recalled for participants who are hungry, in comparison with those who are not hungry.
What Are Sampling Techniques?
Sampling involves selecting participants from a target population.
What Is A Target Population?
This is the particular subgroup time be studied, and to which the research findings will be generalised.
A target population is usually too large to study everyone so sampling techniques are used to choose a representative sample .
Types Of Experimental Design?
Repeated measures,
Independent groups,
Matched pairs.
Repeated Measures?
Repeated measures is a design where the same participants take part in each condition of the experiment.
The data obtained from both conditions is then compared for each participant to see if there was a difference.
Repeated Measures Evaluation?
Strength - The same participants are taking part in all the conditions, so fewer participants are required. This makes the design less costly and time-consuming.
Strength - The use of the same participants across conditions reduces the possibility of participant variables such as individual differences playing a part in the results obtained. This means the effect on the dependent variable can be attributed to the independent variable with more confidence.
Weakness - Repeated measures experiments are also prone to demand characteristics as participants are more likely to guess the aim of the experiment when they take part in both conditions.
Weakness - The same participants take part in both conditions, therefore, order effects (the order at which the experiment takes place) can occur. Participants who experience practice affects may perform better in the second condition because they know what is expected of them. Participants who experience fatigue may perform worse in the second condition. To address this issue, researchers can use counterbalancing which eliminates any order effects. Counter balancing includes allowing half of the participants to take part in condition age followed by condition be while the other half complete condition be followed by condition eight. Any order effects experienced by those who started in condition age should be offset by those who started in condition B.
Independent Groups?
Independent groups design uses two separate groups of participants: one group in each condition of the experiment.
Participants should be allocated the group condition by random allocation. This is important to reduce investigator affects, resulting in a biased sample being placed into the two conditions. This is also important to reduce individual differences whereby participant variables influence the measurements taken in the dependent variable.
Independent Groups Evaluation?
Strength - Avoid order effects. Participants only take part in one condition so they are less likely to become fatigued or practice which would impact the results of the study.
Strength - This research design also reduces demand characteristics, as participants are only taking part in one condition. This means they are less likely to get the aim of the experiment and display demand characteristics, making the results higher in validity.
Weakness - More participants are required as different people take part in different conditions of the experiment. This makes the design more expensive and time-consuming.
Weakness - Participant variables may affect the results. For examples, difference in age, sex or social background may affect the results by acting as an extraneous variable and the dependent variable which means that psychologist cannot be certain that the independent variable cause the changes measured.
Matched Pairs?
Pairs of participants are matched from the sample, in terms of key variables such as age or IQ.
After matching takes place, the participants are treated much like those in independent measures. One member of each pair is placed in the experimental group and the other member in the control group.
Matched Pairs Evaluation?
Strength - The research of pairs up the participants so that each condition has people with similar abilities and characteristics, this reduces participant variables.
Strength - Order effects (such as practice or fatigue) are less of an issue compared to a repeated measures design as the participants only take part in one condition of the experiment and therefore are less likely to become bored and give up.
Weakness - More participants are required, which increases the cost and time of the study.
Weakness - It is very difficult, if not impossible, to match people who are exactly the same. This means that individual differences may still play a role in the measurement of the dependant variable. This reduces the certainty that the independent variable solely caused the results.
Pilot Studies?
A pilot study is a small scale prototype of a study that are carried out in advance of the full research to find out if there are any problems with the following:
- experimental design,
- instructions for participants,
- and measuring instruments.
Carrying out a pilot study beforehand is a way to ensure time, effort and money are not wasted on a flawed methodology.
It is important that a pilot study uses a sample that (although smaller) is representative of the target population that will be used in the main research.
Example of why you would do a pilot study?
Check equipment.
Check behavioural categories.
Apply to question (if certain equipment is described, e.g. cameras, then use this in answer).
Ensure no time, money or effort is being wasted.
Five Types Of Sampling?
Common types:
- Random,
- Systematic,
- Stratified,
- Opportunity,
- Volunteer.
Random Sampling?
Every member of the target population has an equal chance of being selected.
This involves identifying everyone in the target population and then selecting the number of participants you need in a way which gives an equal chance of being selected.
E.g. pulling names from a hat, or using a computer software package which generates names/numbers randomly and without bias.
Random Sampling Evaluation?
Strength - It is free from researcher bias. The researcher does not have any input into who is selected. This significantly reduces the possibility of a researcher choosing a biased sample of participants who would serve to support their aims. This means the sample is likely to be representative so can be generalised to the target population.
Weakness - Ensuring that everyone in the target population has an equal chance of being selected is difficult and time-consuming. It is also a possibility that individuals who are picked may be unwilling to take part. This results in a sample being more akin to a volunteer sample.
Systematic Sampling?
Systematic sampling involves using a predetermined system to select participants.
For example, every fifth person is chosen and the same individual is then consistently applied to the whole of the target population such as the 10th, 15th, 20th person and so on.
Systematic Sampling Evaluation?
Strength - Free from researcher bias because the researcher is not selecting participants by choice, but by following a predetermined system. This reduces any potential influence that the investigator may have over obtaining the sample. They cannot choose a biased sample of participants who would serve to support their aims.
Weakness - However, the systematic sampling method may not be truly unbiased. There may be a coincidence that every Nth person has a particular characteristic in common, for example being right-handed. Although it would be fairly unlikely and unlikely to get a sample who were all similar on a particular trait. It remains a possibility when using this technique. Therefore, if this were to happen, the sample generated may not be representative meaning generalisation to the population would be more difficult.
Stratified Sampling?
In stratified sampling, subgroups within a population are identified.
Participants are obtained from each stratum (layer or category) in proportion to their occurrence within the population.
Stratified Sampling Evaluation?
Strength - It is largely free from researcher bias. The sample is generalised randomly once the subcategories/strata have been identified. This reduces the possibility of the researchers choosing a biased sample of participants who would serve to support their aims. This means the sample is likely to be representative because each subgroup, if selected appropriately, will be represented within the sample. This means findings can be generalised to target population with greater confidence.
Weakness - Ensuring that the subgroups/strata in target population are all accurately identified is sometimes a difficult and time-consuming task.
Weakness - Stratification is not a perfect process since the subgroups identified cannot possibly reflect all the individual differences that exist between those in the target population. Therefore a truly representative sample would be extremely difficult to obtain using this technique.
Opportunity Sampling?
Opportunity sampling consist of selecting anyone who is available and willing to take part in the study at the time.
This is often used in psychological research due to its ease of application.
Opportunity Sampling Evaluation?
Strength -It is a convenient technique. It’s quicker and easier since it requires less effort on behalf of the researcher. It’s likely to save money and is therefore favoured as the most economical technique.
Weakness - There are issues of bias. The sample is drawn from a very specific area or location (e.g. university). This means that it is likely only students will be available to take part who are not representative of the target population.
Weakness - In addition, there is an increased risk of investigator bias as the researcher has complete control over who they approach. This means that they may select particular individuals or avoid others according to their own subjective preferences.
Volunteer Sampling?
Volunteer sampling consists of participants self-selecting to take part in a study by either volunteering when asked or by responding to an advert.
Volunteer Sampling Evaluation?
Strength - Participants generally approach the researcher rather than the other way around. This means that the technique requires minimal effort and input on behalf of the researcher. This makes it quicker and easier.
Weakness - There are issues of bias. Very often, it is a particular type of person that is likely to take part in research as only those who see that advert will come forward to participate. Those individuals who are more curious or inquisitive by nature may volunteer more readily. Therefore, the sample is likely to be biased and not representative of the target population which makes generalisation of the findings more difficult.
How Can Researchers Control A Study?
Researchers need to be able to control extraneous variables.
They do this by following measures:
- random allocation,
- counterbalancing,
- randomisation,
- standardisation.
What Are Extraneous Variables?
Extraneous variables are any variable other than the independent variable that might affect the dependent variable and therefore affect the results of the study.
What Are Confounding Variables?
Extraneous variables that are important enough to cause a change in the dependent variable are called confounding variables.
If they are not important enough to cause a change in the dependent variable, they stay known as extraneous variables.
Situational Variables?
A type of extraneous variable.
Situational variables are variables connected with the research situation.
For example, the temperature, time of day, lighting, materials, etc.
They are controlled through standardisation, ensuring that the only thing which difference between the two groups is the independent variable.
E.g. standardisation for situational variables would include making sure that the temperature is the same for both groups.
Participant Variables?
Participant variables are in example of extraneous variables. They are variable is connected with the research participants.
For example, age, intelligence, gender, etc.
They are controlled through the experimental design, such as matched pairs design, or by randomly allocating participants to conditions. This helps reduce bias.
Random Allocation?
This involves randomly allocating participants to groups.
Random allocation greatly decrease is the possibility that participant variables in the form of individual differences, such as mathematical ability, will adversely affect the results.
Counterbalancing?
Counter balancing combat the problem of order effects with in the repeated measures design.
They do this by splitting the sample in half with 1/2 completing the two conditions in one order and the other half completing the conditions in the reverse order.
Any order effects should be balanced out by the opposing half of the participants.
Randomisation?
This is when trials are presented in a random order to avoid any bias that the order of the trials might be present.
Standardisation?
This is the process in which all situational variables of a procedure used in research are kept identical, so that methods are sensitive to any change in performance.
Under the circumstances changes in data can be attributed to the independent variable.
In addition, it is far more likely that result will be replicated on subsequent occasions when research is standardised.
Demand Characteristics Are?
Could be a possible confounding variable.
Demand characteristics occur when the participants try to make sense of the research and change their behaviour accordingly to support what they believe are the aims of the investigation.
This is a problem as the participants act in a way to support the hypothesis rather than displaying natural behaviour, making the results lack validity. The participants may also deliberately try to disrupt the results, a phenomenon known as the ‘screw you’ affect.
Demand characteristics can be controlled by not allowing the participants to guess the aim of the research or identify the independent variable. This can be achieved by using single-blind experimental technique. This is when only the research and of the true aim of the experiment.
Investigator Effects?
Could be a possible confounding variable.
Investigator affects our where we say chair (consciously or unconsciously) act in a way to support their production.
This can be a problem when observing events that can be interpreted in one or more away. For sample, one researcher might interpret children fighting as an act of violence, while another might observe this as play.
Investigator Fx are controlled by not allowing either the participants or the researcher to know the aim of the research, this is a double-blind experiment. Therefore, either consciously or unconsciously, the investigator is unable to influence the participants.
What Are Ethical Issues?
Ethical issues or considerations that researchers need to consider before, during and after the research is conducted.
Ethical issues take into consideration the welfare of the participants, the integrity of the research and the use of the data.
The British Psychological Society?
The BPS has a code of ethics that researchers need to consider when undertaking psychological research.
Six of the main ethical guidelines include:
- deception,
- right to withdraw,
- informed consent,
- privacy and confidentiality,
- protection from harm.
‘DRIPP’ - hahahahahah.
Ethical Guideline: Deception?
Deception is when information is deliberately withheld from participants were they on knowingly misled.
Why is it unethical?
It is an ethical if broken because it prevents participants from giving fully informed consent which means that they might be taking part in research that goes against their views or beliefs.
How to deal with deception if it’s broken?
At the end of the study, the participants should be fully debriefed and told the true aim and nature of the research. The participant then should be given the right to withdraw the publication of their results. The contact details of the experimenter should be given if participants have any further questions or queries.
Ethical Guideline: Right To Withdraw?
The right to withdraw is the right Of participants to remove themselves or their data from the study at any stage. This includes after the research has been conducted, in which case the researcher must destroy any data or information collected.
Why is it unethical if broken?
Participants who are not given the right to withdraw may feel unnecessary or undue stress and are therefore not protected from harm.
What to do if it is broken?
At the end of the study, the participants should be fully debriefed until the true aim and nature of the research. The participant should be given the right to withdraw. The contact details of the experimenter should be given if participants have any further questions.
Ethical Guideline: Informed Consent?
When someone consents to participate in research, their consent must be fully informed which means the aims of the research should be made clear before they agreed to participate.
Why is it unethical if broken?
Lack of informed consent may mean that the participant is taking part in research that goes against their wishes or beliefs. It is possible that the participant may have felt obliged to take part or even forced into it, especially if they are not fully informed.
What to do if it is broken? If informed consent is broken, the researcher may then have to gain consent through one of the following: - presumptive consent, - prior general consent, - retrospective consent, - children as participants.
Types Of Consent?
Presumptive consent - Involves taking a random sample of the population and introducing them to the research, including any deception which may result. If they agree to take part in the research, it can be presumed that other future participants would do the same so the content is generalised.
Prior general consent - Involves participants agreeing to take part beforehand in numerous psychological investigations, which may or may not involve deception. This means that they will have given consent for being deceived.
Retrospective consent - Involves participants giving consent for their participation after already taking part. For instance, if they were not aware that they were the subject of an investigation.
Children as participants - Involves gaining the consent of the parents inviting for children under the age of 16 to participate in any psychological research.
Ethical Guideline: Privacy?
Privacy is the right of individuals to decide how information about them will be communicated to others.
Why is it unethical?
If broken, a skilled researcher may obtain more information from a participant then they wish to give which could be an invasion of privacy in the participant me later feel ashamed or embarrassed.
What to do if it’s broken?
The participant should be provided with a fully informed consent and the right to withdraw at any stage. The researcher should explain to participants of the ways in which information will be protected and kept confidential, e.g. no names will be published in the final report and any written information or video information will be destroyed.
Ethical Guideline: Confidentiality?
Confidentiality is where are participants personal information is protected by law under the data protection act both during and after the experiment.
Why is it unethical?
Because a persons details or data may be used by other parties against the participants wishes.
What to do if it’s broken?
Participants are provided with a fake name, number or initials to protect their identity. They should not be identifiable by any person, institution or organisation.
Ethical Guideline: Protection From Harm?
Psychologists have the responsibility to protect their participants from physical or psychological harm, including stress. The risk of harm must be no greater than which they are exposed to in everyday life.
Why is it unethical?
Participants should leave the research in the same state as they entered it. If they are harmed, they may suffer from long-term effects that could impact their lives in the future.
What to do if it’s broken?
The researcher should remind participants of their right to withdraw throughout and after the research. The researcher should terminate the experiment of the level of psychological or physical harm is higher than expected. Participants should be debriefed at the end of the experiment and in some instances they may be referred to counselling.
The Role Of Peer Review?
Peer review is an independent assessment process that takes place before a research study is published. All psychologists must be prepared for their work to be scrutinised in this way which is conducted anonymously.
There are several aims of the peer review process (in brackets are ways to remember it):
PEER - To provide recommendations about whether the research should be published in the public domain or not.
VIEWS - To check the validity of the research to ensure it is of high quality.
ARE - To assess the appropriateness of the procedure and methodology.
SO - To judge the significance of the research in the wider context of human behaviour.
OVER-RATED - To assess the work for originality and ensure that other relevant research is sufficiently detailed.
(A extra one): To inform allocation of future research funding to where the investigative processes.
Purpose of peer review:
- to ensure quality and relevance of research,
- to ensure accuracy of findings,
- to evaluate proposed designs for research funding.
Peer Reviews Evaluation?
Weakness - there are drawbacks associated with the peer review process. Peer reviews are often anonymous, so there is a possibility that they will use this fact as a means to criticise rivals in their field of psychology. This happens because there tends to be limited funding for new research in psychology. As a result, and accurate or unfair criticism is may be received by following the peer review process which is not a valid reflection of the research quality.
Weakness - It is sometimes difficult to find a suitable Pierre. The consequence of this is that research which is not of high quality will be passed as suitable for publication. This may cause a positive publication bias.
Strength - This process helps to prevent any substandard research from entering the mainstream which serves to protect the reputation of the discipline. Experts within the field often actors peers, there is less opportunity for plagiarised work or duplications of research being published.
Implications Of Psychological Research For The Economy?
Economy - how many members of society produce, share and consume goods and services.
Implications - the ability to interpret findings in terms their value, strengths, and weaknesses for achieving success.
We review psychological knowledge in context of the economy to help portray a clear picture of how people’s behaviour is affected in the real world.
E.g. the psychosocial research into psychopathology (mental illness) helps the economy because less money can be spent through salary contributions (when people take time off work for mental health) and treatments.
Psychopathology Example For Implications For The Economy?
Topic: Psychopathology.
The biological approach to treating OCD.
Soomro et al conducted a review of research examining the effectiveness of SSRI’s and found they were significantly more effective than placebos in the treatment of OCD (across 17 trails). This supports the use of biological treatments for OCD.
Implications for the economy:
- The development of effective treatments will restore quality of life for the sufferer,
- This impacts their ability to work and have less time off work for being ill,
- Government spends less money on funding incapacity benefit,
- NHS saves money because there’s FEWER RELAPSES requiring medical attention.
Memory Example For Implications For The Economy?
Topic: Memory.
Factors affecting accuracy of eyewitness testimony.
Fisher et al examined effectiveness of the cognitive interview in police interviews. 16 detectives recorded a selection of their interviews. The defectives were split into 2 groups. One group - cognitive interview. Second - standard interview (control). 46% information was obtained using cognitive. 90% of this info was accurate.
Implications for the economy:
- There will be a greater chance the police prosecute the right criminal from the offset,
- These techniques can reduce wasted money on wrongful arrests, questioning and court hearings,
- The criminal justice system saves money.
Attachment Example For Implications For The Economy?
Topic: Attachment.
Role of the father.
Belsky et al found males who reported higher levels of marital intimacy also displayed father-infant attachment, which suggests that males can form a secure attachment with their children (if the relationship with the women in good).
Implications for the economy:
- Research shows both mothers and fathers are equally capable of child rearing to enable a healthy development outcomes for the infants.
- This allows mothers to return to work, free of guilt, and contribute to the economy,
- Modern parenting styles can therefore maximise the annual income enabling both parents to contribute most effectively to the economy.
How To Calculate The Mean, Median, Mode And Range?
Mean - add all the numbers together then divide by how many there are.
Median - put all numbers in ascending order than find the middle number (if there is two numbers, find the between).
Mode - most common number.
Range - biggest number - smallest number.
How To Calculate Standard Deviation?
- Work out the mean,
- Then for each number: subtract the mean and square the result,
- Then work out the mean of those squared differences,
- Take the square root of that and we are done!
What Is A Histogram?
Basically a bar chart but with ranges of numbers at the bottom of each bar instead of a single number.
E.g. ‘0-10’ ‘11-20’ ‘21-30’ ‘31-40’
TIME ALWAYS ON BOTTOM OF CHART, FREQUENCY ALWAYS UP SIDE.
Y and X Axis?
X = along the bottom,
Y = up the side.
Time is always X.
What Is The Difference Between A Normal And A Skewed Distribution?
Imagine a graph and the curve for the graph goes up and down, symmetrically.
This is normal.
Imagine now the curve for the graph goes up really really high on the first half of the graph and then shoots down rapidly. It is not symmetrical.
This is skewed.
How To Calculate Percentages? And How To Convert A Percentage To A Decimal And Fraction?
E.g. Find 11% of 27?
10% = 2.7 1% = 0.27 11% = 2.97
E.g. What is 45 out of 60 as a percentage?
100/60 = 1.666
45 x 1.666 = 74
74%
E.g. Convert 54% to a decimal?
5.4
What is a sign test?
A chart that shows a difference between two groups.
What to do:
1. Write a ‘+’ or a ‘-‘ depending on whether the data after the second condition has changed. If there is any ‘=‘ (don’t change between conditions), then remove them people from the data (cross them out). If this is done, remember to change the number of participants.
- Add up the pluses and minuses.
- Work out the observed value. You do this by finding the smallest number of pluses and minueses. E.g. if there are 10+’s and 2-‘s then the observed value is 2.
- Compare the observed value to the critical value where p=0.05. Remember to look at the hypothesis to find if it’s directional (one tailed) or non-directional (two-tailed).
Work out number of people using N-1 or N-2.
What are the types of central tendency and the types of dispersion?
Central tendency - mean, median, mode.
Dispersion - range and standard deviation.
What is random allocation?
This happens after you have made your sample (not the same as random sampling).
E.g. you randomly allocate your participants into condition 1 and condition 2.
This is important when talking about repeated measures especially, but can also apply to independent groups and maybe others.
What is a meta-analysis?
A process whereby investigators combine findings from multiple studies (secondary data) on a specific phenomenon to make an overall analysis of trends and patterns across research.
This can include a qualitative review of previous research or a statistical, quantitative analysis to test for significance of effect size.
Meta-analysis evaluation?
Advantage - results are combined from many studies and so the conclusions drawn are in a larger sample which provides a greater confidence for generalisation. This increases validity of patterns identified.
Disadvantage - issues of bias associated with meta-analysis. Since the researcher is selecting data from research which has already taken place, they may choose to omit certain findings from their investigation. This could mean the findings do not accurately represent the studies analysed.
Positively skewed and negatively skewed?
Negatively skewed - the mode is the highest point on the graph. The graph line moves up gradually toward the mean and then down rapidly after. More of the distribution is on the left side of the mode.
Positively skewed - the mode is the highest point on the graph. The graph line moves up rapidly toward the mean and then down gradually after. More of the distribution is on the right side of the mode.
