Help
Options
Didn't know it?
click below
click below
Knew it?
click below
click below
Don't Know
Remaining cards (0)
Know
retry
shuffle
restart
0:00
Embed Code - If you would like this activity on your web page, copy the script below and paste it into your web page.
Normal Size Small Size show me how
Normal Size Small Size show me how
Research methods
| Question | Answer |
|---|---|
| Qualitative data | Analysis that focuses more on words than numbers |
| Quantitative data | Analysis that uses numerical data |
| Mean | The statistical average, calculated by adding up all the scores in a set of data and then dividing by the number of scores. |
| Median | The central value of the data set, calculated by putting the data in order and finding the middle score. If there is an even number of scores, the median is the middle value between the two central values. |
| Mode | The most frequently occurring score, calculated by a frequency count. |
| What do experimental methods seek to do? | Establish a cause and effect using a hypothesis. |
| What are the three factors of a true experiment? | 1. Random allocation of participants to conditions 2. Manipulation of variables 3. Control of other variables |
| What is one way of controlling other variables in an experiment? | Using a control group as well as an experimental group. |
| What are the three key features of a laboratory experiment? | 1. Carried out in a controlled setting 2. Participants know they are taking part 3. All features of the true experiment are met |
| What are three advantages of laboratory experiments? | 1. High control over variables increases validity. 2. High control also gives high replicability which increases reliability. 3. We can conclude a cause and effect. |
| What are three disadvantages of laboratory experiments? | 1. The tasks and settings are unrealistic - they lack mundane/experimental realism. 2. The setting is unlike real life so ecological validity is low. 3. There is a high chance of investigator-participant effects. |
| What are the three key features of a field experiment? | 1. The independent variable is controlled. 2. No other variables are controlled. 3. Participants are not randomly allocated to conditions. |
| What are three advantages of field experiments? | 1. Ecological validity is higher as the experiment often takes place in a real life setting. 2. Less chance of demand characteristics 3. We can still conclude cause and effect. |
| What are two disadvantages of field experiments? | 1. There is no control of extraneous variables 2. Random allocation of participants is difficult as participants usually don't know they're taking part. |
| What are the three key features of natural experiments? | 1. There is no random allocation of conditions 2. IV is naturally occurring 3. Therefore this is a quasi-experiment: not really an experiment at all |
| What are two advantages of natural experiments? | 1. Useful when it is unethical to manipulate the IV 2. Very high ecological validity |
| What are two disadvantages of natural experiments? | 1. There is no control of extraneous variables so internal validity is reduced. 2. As a result we can't conclude cause and effect. |
| On what 2 diagrams is a correlation shown? | Scatter diagrams and correlation coefficients |
| How does a correlation coefficient work? | It ranges between -1.0 (negative) and 1.0 (positive). The closer to either of these two, the stronger the relationship between the two variables . 0 means there is no relationship. |
| 2 strengths of using correlations. | 1. Can establish a relationship between two variables. 2. Researchers can analyse situations which would be unethical to experiment. |
| 3 weaknesses of using correlations. | 1. Doesn't establish cause and effect, only a relationship. 2. Doesn't consider 3rd variables 3. Only shows linear relationships - doesn't work for curvi-linear relationships, for example temperature and aggression |
| What are the two types of observation? | Natural and controlled observations |
| What is a natural observation? | It is carried out in a familiar environment and no variables are manipulated eg a parent keeps a diary of their child's behaviour |
| What is a controlled observation? | It is carried out in a a laboratory by a researcher, eg the child is watched through a one way mirror (Strange Situation) |
| 2 strengths of observations | 1. Naturalistic observations have high ecological validity. 2. Controlled observations have high control over different variables |
| 3 weaknesses of observations | 1. High chance of observer bias 2. Unethical to observe people without their consent, but with this ecological validity would be low 3. Controlled observations have low ecological validity |
| How can we overcome observer bias in observations? | The double blind technique - neither the participant nor the observer knows the hypothesis so they don't make biased judgements. |
| Apart from the double blind technique, what other ways can we improve reliability of observations? | 1. Operationalise (clearly define) ambiguous terms such as aggression 2. Conduct a pilot study which allows all observers to practice their schedule and determine if all categories are clear |
| Describe open questions, and give 1 strength and weakness of them. | Open questions enable the participant to answer in their own words. A strength of this is that rich, detailed qualitative data is produced, but a weakness is that this is difficult to analyse. |
| Describe closed questions and give 1 strength and weakness of them. | In a closed question the participant answers from a range of fixed responses. A strength of this is that the data produced is easy to analyse, but a weakness is that the participant may not be able to give their true opinion. |
| What are 3 strengths of questionnaires? | 1. They allow you to question lots of people quickly. 2. Lots of information about what people think and do can be collected. 3. The researcher doesn't have to be there, so there is less risk of interpersonal factors such as investigator effects. |
| What are 3 weaknesses of questionnaires? | 1. There is a risk of social desirability, particularly in sensitive areas. 2. Postal response is low so only a certain kind of person will take part. 3. It's difficult to make sure every participant has the same understanding of each question. |
| Describe a structured interview. | The procedure is standardised with the same questions which are asked in the exact same order with the exact same wording. The questions are usually closed with a number of fixed possible responses. |
| Why might a researcher prefer a structured interview? | If they will need to report results in a quantitative format, and also if they already know a lot about the topic and possible answers in question. |
| Describe a semi structured interview. | The interviewer may use some of the same questions for each interviewee, but the order may vary and they are able to ask follow up questions. Questions are usually open. |
| Describe an unstructured interview. | An interview where questions are not prearranged, allowing the interviewer to be spontaneous and develop questions during the course of an interview. |
| 4 strengths of interviews. | 1. Detailed qualitative information can be obtained 2. The interviewer can clarify themselves or the participant 3. New lines of enquiry can be opened in unstructured interviews 4. The casualness of some interviews encourages participants to be honest |
| 3 weaknesses of interviews. | 1. Qualitative data can be hard to analyse. 2. More time consuming than other methods. 3. Risk of interpersonal factors or investigator effects. |
| Describe a case study. | Case studies gather detailed information about a specific individual or group and their case. |
| 3 strengths of case studies. | 1. Rich, qualitative data 2. High ecological validity 3. Can challenge established thinking and open new lines of inquiry. |
| 3 weaknesses of case studies. | 1. Idiographic - so population validity is low. 2. Low replicability so unreliable. 3. High chance of observer bias |
| 2 main features of a directional hypothesis. | 1. Specifically states the predicted outcome. 2. Can be called a one tailed hypothesis because it predicts the nature of the results. |
| 2 main features of a non directional hypothesis. | 1. Predicts a relationship between the IV and DV but doesn't say what it will be. 2. Can be called a two tailed hypothesis because the results could go in either way. |
| 2 main features of a null hypothesis | 1. Predicts there will be no relationship between variables. 2. Might be used to prove or disprove another hypothesis. |
| Why do studies have an aim? | To give them a clear focus. |
| 3 types of experimental design. | Repeated measures, independent measures, matched pairs. |
| Describe a repeated measures design and 1 strength and weakness of it. | The same participants are used for both conditions. It is useful when only a small number of participants is available, but there is a risk of demand characteristics and order effects (fatigue, practice). |
| How can some of the difficulties of repeated measures design be overcome? | With the single blind technique (only the researcher knows the hypothesis) and counterbalancing (conditions are repeated in different orders). |
| Describe an independent measures design and 1 strength and weakness of it. | Participants are randomly allocated to conditions and remain separate. There is less risk of demand characteristics so the same stimuli can be used, but more people are needed than a repeated measures design. |
| Describe a matched pairs design and 1 strength and weakness of it. | Participants are put into pairs based on similarity (eg age, IQ), put in separate conditions and their results are compared. This can be a good way of tackling participant variables, but it is hard to match participants exactly, and many would be needed. |
| Define operationalising variables and why it is important. | This means giving the variables clear definitions of what they are and how they will be measured. This is important to making sure the results are both reliable and valid. |
| Define the independent variable (IV) | The variable which is manipulated by the researcher and is expected to affect the dependent variable. |
| Define the dependent variable (DV) | The variable which is supposed to change according to the independent variable. |
| Define extraneous variables (EV) | Variables other than the independent variable which could affect the dependent variable. They are called confounding variables if they can provide alternative explanations for the results. |
| What are the two main types of extraneous variable, what kind of things are they and how can they be controlled? | 1. Situational variables like temperature or instructions given. Can be controlled by standardisation (everything is the same for all participants) 2. Participant variables like age, background. Can be controlled by random allocation. |
| How can demand characteristics and investigator effects be dealt with? | Single or double blind technique, where either the participant or both the participant and researcher are unaware of the hypothesis and conditions. |
| Define realibility | Reliability is the consistency of a measure: it should be the same every time it is repeated. |
| Define validity | Validity is whether we are actually measuring what we are supposed to be. |
| Define inter-rater reliability | In an observation two different observers should record the same findings. This can be assessed with correlational methods. |
| Define internal validity | The extent to which the IV causes the DV. |
| Define external validity | The extent to which results can be generalised. |
| Define face validity | The extent to which the test and materials appear authentic. |
| Define concurrent validity | The extent to which the results of a study agree with another study which has good validity. |
| Define predictive validity. | The extent to which the results of a study are good predictive measures of the results of future studies. |
| What is deception, why is it important to avoid and how can it be maintained? | Refers to deception of participants. Some is usually necessary but too much prevents informed consent and could make participants distrustful of researchers. After a debrief, participants can give retrospective informed consent or remove their data. |
| What is informed consent, why is it important and how can it be maintained? | Participants must agree to take part in the study with full knowledge about its details. Without it they may take part in something against their wishes. They have to sign a standardised form - parents do this for participants under 16. |
| What right do participants always have in research? | They always have the right to withdraw at any time. |
| What is protection, why is it important and how can it be maintained? | Participants have a right to be protected from psychological or physiological harm - they must leave as they arrived. A study with poor protection was Milgram (1963) - many participants were traumatised. |
| When is a sample said to be biased? | If it doesn't accurately represent the target population. |
| What is random sampling and one strength and weakness of it? | Every member of the population has an equal chance of being selected. This is the best method as it has the least chance of bias but it is often difficult and impractical to do. |
| What is opportunity sampling and one strength and weakness of it? | The sample consists of those available to the researcher. This is the easiest method, but is highly likely to be biased. |
| What is volunteer sampling and one strength and weakness of it? | The sample consists of volunteers who have responded to some kind of advert. Relatively easy and likely to have low participant attrition, but there is a high chance of bias as a certain type of person is likely to respond. |
| What is the mean and one strength and weakness of it? | The mean is the statistical average of a set of data. It represents all the data, but is very sensitive and can be easily distorted by extreme, anomalous values and become unrepresentative. |
| What is the median and one strength and weakness of it? | The middle score in a set of data when it is ordered. It is less sensitive than the mean so may be more appropriate, but it only represents one value whereas the mean represents all data. |
| What is the mode and one strength and weakness of it? | The most frequently occurring score in a set of data. Like the median it is unaffected by extreme scores, but like the mean it is sensitive and only one small change can make it unrepresentative. |
| What is the range and what does it tell us? | The range is the difference between the highest and lowest values in a set of data. It is a simple measure of dispersion and tells us simply how much variation there is in the set of data. |
| 1 strength and 1 weakness of the range as a measure of dispersion. | It is very easy to calculate, but also easily manipulated by extreme scores. |
| What is standard deviation and what does it tell us? | A figure which tells us about the spread of data around the mean. A high figure means there is a wide spread, a low figure means the data is close to the mean. |
| 1 strength and 1 weakness of the range as a measure of dispersion. | It takes all scores into account as well as the mean, which the range doesn't, therefore giving us more information. However it is very difficult to calculate. |
| What are the two types of qualitative analysis? | Content analysis and pure qualitative analysis. |
| What is the process of content analysis and 1 strength and weakness of it? | Categories are established and counted when they occur in a text. This makes quantitative data which is easy to analyse. However there is a risk of investigator effects, eg interpretation of definition of violent behaviour. |
| What is the process of pure qualitative analysis? | Coding is rejected - data is transcribed and simply read through for recurrent themes. |
Created by:
strawberrydream96
Popular Psychology sets