Self-Report * Questionnaire: A method of self-report where respondents write/record their own answers to a list of pre-determined questions. * Unstructured- A method if self-report that features no pre-set questions. No questions are decided in advance so the researcher is free to explore the participants’ thoughts and ideas. * Rich source of qualitative data * Interviewee is relaxed and so answers the questions fully * Different data from each person so comparisons are difficult to make * Analysis is difficult * Low inter-rater reliability because of the disagreement over the interpretations * Demand characteristics * Semi-Structured- New questions are developed as the conversation develops. The interviewer may start off with some pre-determined questions then develop further questions. * Interviewer can be flexible and follow the line of thinking of every interviewee * Data collected can be on the same general topics so comparisons can be made * Non-standardised procedure means questions are worded differently therefore interpretations will be different * Low reliability- difficult to replicate * Fully structured- A list of pre-determined questions that re delivered by an interviewee in real time- face to face or over the phone. * Quick and easy to administer * Easy to replicate- high reliability * Data analysis is easier * Less chance of interpersonal bias to affect results * Loss of richness of the data gathered as there is no room for individual responses * Interviewee is limited in the answer they can give * Only quantitative data is collected * Interviews: This is a type of spoken questionnaire where the interview records the responses. There are two types of interviews. * Structured Interview- Where all the questions to be asked are decided beforehand. They may have limited range of answers (e.g. yes/no) * Unstructured Interview- They resemble conversations and the researcher will have a topic they wish to discuss but might develop questions as they go along and keep the interview along the right track * Open and Closed Questions * Open questions are those that allow the respondents to give a more detailed answer * -They can produce unexpected information * -Allow respondents to express what they actually think * More difficult to analyse because of the qualitative data that is produced thus making it more difficult to draw conclusions * Closed questions are those that give the respondents a limited choice of answers to give * Easier to analyse the data * May not permit people to express their precise feelings. * forced choice response may not reveal full extent of people’s beliefs

* Rating Scales: Example Likert scale. A statement is used and the participant decides how strongly they agree or disagree with the statements. * They can give us an idea about how strongly a participant feels about something. This therefore gives more detail than a simple yes no answer. * Ability to quantify responses and compare across different individuals and analyse statistically. * Tendency with Likert scales for people to respond towards the middle of the scale perhaps to make them look less extreme. * Participants may provide the answers that they feel they should- Demand charecteristics * Quantitative data – lacks in depth replies

* Fixed choice questions: Fixed choice questions are phrased so that the respondent has to make a fixed choice answer usually “yes” or “no” * This type of questionnaire is easy to measure and quantify. It also forces a participant to not choose a middle option. * However respondents may not feel that their desired response is available and of course the answers are not in-depth.

* Reliability: Reliability refers to consistent a measuring device is. A measurement is said to be reliable or consistent if the measurement can produce similar results if used again in similar circumstances
A way to improve reliability is to clarify ambiguous questions. In the case of interviews, interviewers could be given training.

* Validity: This is when a study measure or examines what it’s meant to measure; how much the questions test the aim. To check if a study is valid, you compare the results of the self-report with another self-report on the same topic. This is called “concurrent validity”.
A way to improve validity is to avoid leading questions, add open questions to expand responses and give confidentiality to allow participants to give more truthful answers.

* Sampling: This is the process of selecting participants to study from the target population. Since the results of the study will be generalised back to the target population, samples should be as representative of the target population * Opportunity sampling: It consists of taking the sample from people who are available at the time the study is carried out and fit the criteria you are looking for. * Easy in terms of time and money, quick and is often the most economical method of sampling. It’s also the most common type of sampling. * Can produce a biased sample as it is easy for the researcher to choose people from their own social and cultural group. This sample would therefore not be representative of your target population as your friends may have different qualities to people in general. * Self-selecting sample: consists of participants becoming part of a study because they volunteer when asked or in response to an advert. * Useful as it is quick and relatively easy to do. It can also reach a wide variety of participants. * May not be representative of the target population for a number of reasons. For example, they be more obedient, more motivated to take part in studies and so on * Random Sampling: a sample in which every member of the population has an equal chance of being chosen. This involves identifying everyone in the target population and then selecting the number of participants you need in a way that gives everyone in the population an equal chance of being picked. For example, you could put all of the names of the students at your college in a hat and pick out however many you need. * Provides an unbiased representative sample of a target population. * Random sampling can be very time consuming and is often impossible to carry out, particularly when you have a large target population, of say all students. For example if you do not have the names of all the people in your target population you would struggle to conduct a random sample. * If you ask people to volunteer for a study the sample is already not random as some people may be more or less likely to volunteer for things. Similarly if you decided to put out an advert for participants it would be almost impossible to guarantee that every member of your target population has an equal chance of viewing the advert. * Stratified sampling: involves classifying the population into categories and then choosing a sample which consists of participants from each category in the same proportions as they are in the population. * Representative of the population * Very time consuming as the categories have to be identified and calculated. If you do not have details of all the people in your target population you would struggle to conduct a stratified sample. * Snowball sampling: Asking the participant who fits your target population to tell their friends about the study and ask them to get in touch with the researcher and so on. * Easier to target participants * May not be representative. * Systematic sampling: Every nth person on the list is chosen

* Ethical issues with self-report. * It is expected that all participants will have informed consent to the questionnaire and where deception is necessary, all participants should have been debriefed. * Questions should not cause emotional or psychological harm * They should avoid the invasion of privacy. Participant’s names should not be recorded and their answer can only be stored with permission.

Experiments * Laboratory Experiments: A laboratory experiment is an experiment conducted under highly controlled conditions. The variable which is being manipulated by the researcher is called the independent variable and the dependent variable is the change in behaviour measured by the researcher. * Allow precise control of variables- extraneous variables avoided * Allow to make statements about cause and effect- involve deliberate manipulation of variable * Can be easily replicated and repeated because of the standardised procedure- high reliability * Easy to record and analyse * Lack ecological validity- cant generalise findings * Show demand characteristics as well as social desirability bias. * Ethical issues often arise to stop demand characteristics.

* Field Experiment: A field experiment is an experiment that is conducted in the field - in a real world situation. The independent variable is still manipulated by the researcher. * High in ecological validity- generalisable * Can avoid demand characteristics * Ethical issues- cannot receive informed consent/ debriefed * Harder to debrief * harder to control confounding variables- cannot assume cause and effect

* Quasi Experiment: Where the independent variable is not manipulated by the researcher but occurs naturally. The researcher takes advantage of pre-existing conditions such as age, sex or an event that the researcher has no control over such as participant’s occupation. * Participants are often unaware that they are taking part in an investigation and they may not be as artificial as laboratory experiments. * Ethically and practically they are the only design that can be used. * Harder to establish causal relationships because the independent variable is not being directly manipulated by the researcher. * Cannot be replicated

* Experimental designs- Set of procedures used to control the influence of participant variables so that we can investigate the possible effects of the independent variable on the dependent variable * Independent measures design – the sample is divided into group and each group does one condition * No problem with order effect as learning, fatigue or boredom don’t influence the second condition, as the participants only participate in one condition * Easily replace participants if they drop out * potential for error resulting from individual differences between the groups of participants taking part in the different conditions * more participants are needed as each one is only used once * doesn’t control all participant variables- could just be measuring individual differences rather than observing IV-DV * Repeated measures design: consists of testing the same individuals on all the conditions. * individual differences between participants are removed as a potential confounding variable * requires fewer participants as the same group of participants are used to gain more data * situational variables such as order effects such as learning, fatigue or boredom may become constant errors when one condition is done after another * This could be dealt with by using counter balancing- participant 1 does A then B, participant 2 does B then A. * More demand characteristics * Some experiments cannot be done as a repeated measures design- gender. * Matched pairs design: The sample is divided in groups of participants who have been matched for relevant characteristics. Each group does only one condition. * Participant variables are kept more constant between participants * No order effect as participants only take part in one condition * Time consuming and difficult * Cannot be matched on all variables * More participants required as each one is only used once

* Hypothesis: A hypothesis is a testable, predictive statement. The hypothesis will state what the researcher expects to find out. * One-tailed/ directional hypothesis: Predicts the direction of the results or predicts either a positive or negative correlation will occur * Two-tailed / non-directional Hypothesis: Predicts a difference between two variables but not the direction * Null hypothesis: a hypothesis stating there will be no significant difference or relation between two conditions or variables. * Alternate hypothesis/Experimental hypothesis: A statement to be tested, predicts there will be a difference between two conditions.

* Measures of central tendency: * Mean- The arithmetic average that indicates the typical score in a data set and is calculated by adding all the scores together in each condition and then dividing by the number of scores * This is a useful statistic as it takes all of the scores into account * Can be misleading if there are extreme values. * Mode- the most common value in a set of values. * Unaffected by extreme or rogue vales in one direction. * Median- The median is calculated by placing all the values of one condition in order and finding the mid- point. * more useful measure than the mean when there are extreme values * Not all of the scores are taken into account.

Correlation

* Types of correlation:

Uncorrelated: If there is no correlation between two variables they are said to be uncorrelated.

Negative correlation: As one variable increases, the second variable decreases

Positive correlation: As one variable increases. So does the second variable

* Very good for showing possible relationships between variables and sometimes are the only practical or ethical way of carrying out an investigation. * may use correlational analysis as a starting point in their research and if a relationship between variables is found they can then investigate this further * Doesn’t allow researchers to draw conclusions about cause and effect relationships- doesn’t imply causation. * Difficult to control extraneous variable

Observations * Observations: Observational studies are investigations where the researcher observes a situation and records what happens but does not manipulate an independent variable. * High in ecological validity as there is no intervention avoids problems with demand characteristics and social desirability. * They get to see how participants actually behave rather than what they say they do. * They offer ways of studying behaviour when there are ethical problems with manipulating variables. * Observational studies are also useful as a starting point in research. * Difficult to replicate- low reliability * Observations do not provide information about what participants are thinking or feeling. * There is little or no control of extraneous variables in observational studies therefore we cannot make cause and effect statements. * Problem of observer bias with observational studies. This occurs if the observers ‘see’ what they expect to see. * Ethical issues can arise with observational studies including problems with a lack of informed consent and invasion of privacy. * missing key behaviours due to people obscuring view * Types of observational studies * Participant observation: Type of observational study where the observer is also a participant in the activity being studied. * useful because it provides more insights about behaviour * Observer may lose some objectivity. * Undisclosed observation/ covert: is a type of observational study whereby the participants are not fully aware that they are being studied. The researchers may use one-way mirrors. * Participants are unaware they are being studied- no demand characteristics * Structured observation is where the researchers design a type of coding scheme to record the participants' behaviour. Coding schemes are ways of categorising behaviour so that you can code what you observe in terms of how often a type of behaviour * Fairly simple to carry out and that they provide quantitative data which can be analysed statistically. * It gives a very restricted view of what is actually happening. The researcher may miss important behaviour and the data is not as in-depth as simply observing behaviour which is occurring. * Unstructured observation involves the researchers recording the behaviour they can see. * Rich quantitative data * Can be difficult without the use of recording equipment (such as a video camera) * can be difficult to analyse * Tendency for observers to record the most eye-catching or noticeable behaviours which might not be the most relevant or important behaviours to record. * Sampling observational data: Sometimes observations are made continuously where the observers record everything that happens in detail. Perhaps with a video camera. Sometimes researchers use a sampling technique as it may be difficult to record everything * Event sampling: Consists of the researcher recoding an event every time it happens * if too many observations happen at once it may be difficult to record everything * Time sampling: occurs when the researcher decides on a time say 5 seconds and then records what behaviour is occurring a at that time * Some behaviour will be missed and therefore the observation may not be representative. * Reliability: Refers to how consistent a measuring device is * A common way of assessing the reliability of observations is to use inter-rater reliability. This involves comparing the ratings of two or more observers and checking for agreement in their measurements. * A way of improving the reliability of an observational study is to ensure that the categories are clearer or that the observers are well trained in the use of the checklists. * Validity: refers to whether a study measures or examines what it claims to measure or examine. * Validity could be reduced in many ways in an observation: * If participants are aware they are being observed they may behave in the way they feel they should behave- demand characteristics * Validity could also be reduced by observer bias. That is the observer may be influenced by expectations and not record objectively what happened * Validity could be improved in a number of ways: * Perhaps some of the categories could have been coded in a different or clearer way. * Observers could be kept unaware of the aims of the observation * More observers could be employed. * Use a covert observation