AICE Psychology Questions with 100% Complete Solutions| Graded A+

lab experiment - These take place in a situation or environment that is artificial to the participants in the study. There are two main types of variable that need to be considered when running any experiment. strengths of lab study - have high levels of standardisation and so can be replicated to test for reliability. As laboratory experiments have high levels of control, researchers can be more confident it is the IV directly affecting the DV. weaknesses of lab study - As laboratory experiments take place in an artificial setting, it is said that they can lack ecological validity. Many laboratory experiments make participants take part in tasks that are nothing like real-life ones, so the tasks lack mundane realism. Participants usually know they are taking part in an experiment and they may respond to demand characteristics as something about the set-up indicates the aim of the experiment. field experiment - These are experiments that take place in the participants' own natural environment rather than in an artificial laboratory. The researcher still tries to manipulate or change an IV while measuring the DV in an attempt to see how the IV affects the DV. There is an attempt to control other variables that could affect the DV. One type of these is called situational variables. These are variables from the setting that might affect the DV (e.g. the weather or time of day). strengths of field study - take place in a realistic setting, it is said that they have ecological validity. As participants will not know they are taking part in a study, there will be little or no demand characteristics so behaviour is more likely to be natural and valid. weaknesses of field study - Situational variables can be difficult to control, so sometimes it is difficult to know whether it is IV affecting the DV. It could be an uncontrolled variable causing the DV to change. As participants will not know they are taking part in a study, there are issues with breaking ethical guidelines. These include the issues of informed consent and deception. natural experiment - This is when researchers use a pre-existing or naturally occurring IV. There are certain instances where the experimenter cannot directly manipulate the IV under investigation. These usually take place in a real-life situation (e.g. the workplace or a hospital). strengths of natural study - As the experiment is located in a natural setting exploiting a naturally occurring IV, the study should be high in ecological validity. As participants are usually unaware that a study is taking place, their behaviour is more likely to be natural and a valid representation of each person's behavioural repertoire. weaknesses of natural study - It can be difficult to know whether the IV has caused an effect on the DV due to the lack of controls. Therefore, it is difficult to establish a cause-effect relationship. As the event is naturally occurring, it can be very difficult to replicate the experiment to test for reliability. aim - is written before a study is run. It is a statement that tells people what the purpose of a study is. It does not predict the outcome of the study (a hypothesis does this) but merely states what the study is about. It can be written as a question. independent variable (IV) - the variable that the psychologist chooses to manipulate or change. This represents the different conditions that are being compared in any study. These usually form the experimental condition and the control condition. To make sure that only one factor is being changed in an experiment, it is divided into two groups. One group, called the control, is exposed to all of the experiment but does not get whatever is being tested or changed in the experiment. Essentially, it is used as a comparison group. At the same time, the experimental conditions gets all of the experiment plus the one variable being tested by the experiment. dependent variable (DV) - is the variable that the psychologist chooses to measure. hypothesis - predicts the findings of a study. It is also written before the study is run. An experimental one always contains the IV and DV (fully operationalised). A correlational one will always have both measured variables operationalised. directional (one-tailed) hypothesis - predicts a significant difference or correlation and also the direction of results. non-directional (two-tailed) hypothesis - predicts a difference or correlation but not the expected direction of results. null hypothesis - is necessary if we are going to use inferential statistical tests to examine whether we have found a significant difference or a significant correlation. These tests calculate how far the actual findings have deviated from chance. experimental design - Researchers who choose to use an experiment have to decide on this. This refers to how they allocate participants to the varying conditions of their experiment. independent measures design - This is when a participant only takes part in one level of the IV. If the IV is naturally occurring (e.g. gender, age) then a researcher must use this type of design. In a true one, participants are randomly allocated to one level of the IV (so they get an equal chance of being placed in any level of the IV). strengths of independent measures design - As participants only take part in one condition they are less likely to guess the aim of the study, therefore reducing the potential effects of demand characteristics. As participants only take part in one condition there are no order effects that can reduce the validity of findings. weaknesses of independent measures design - There may be a problem with participant variables affecting the DV rather than the IV-- even by chance, all people of a certain personality might form one condition and all people with a different personality might form the other condition-- so it could be personality affecting the DV rather than the IV. More participants are required for this type of design compared to repeated measures. repeated measures design - This is when a participant takes part in all of the levels of the IV. This cannot be used if the IV is naturally occurring (e.g. a participant cannot be a male and a female at the same time). strengths of repeated measures design - Using repeated measures eliminates any effect of participant variables as all participants take part in all conditions, therefore they are controlled. Fewer participants are needed for this type of design than the number needed for independent measures design. weaknesses of repeated measures design - As all participants take part in all conditions, there is a chance of demand characteristics affecting the study-- participants might work out of the aim of the study and behave in a way to fulfill that rather than showing their true behaviour. Order effects can affect the findings of the study and reduce its validity. matched pairs design - An experimental design in which participants are arranged into pairs. Each pair is similar in ways that are important to the study and one member of each pair performs in a different level of the IV. extraneous variable - There are variables that can influence the relationship between the IV and DV. They can affect the outcome of an experiment but they are not the variables of interest. Therefore, they add error to the experiment.