Aim: a general statement conclusion idea( statement, conclusion, idea ) of what the researcher intends to investigate- the purpose outcome conclusion( purpose, outcome, conclusion ) of the study. Hypothesis: a testable untestable( testable, untestable ) statement that states the relationship between the variables beliefs data( variables, beliefs, data ) being investigated.
A directional hypothesis: states what kind of difference there will be between the variables outcomes researchers conclusions( variables, outcomes, researchers, conclusions ). They often include words like 'more' or 'less' e.g. People who drink caffeine will be more intelligent than people who don't. A non-directional hypothesis: simply states that there will be a difference, but not the type outcome conclusion( type, outcome, conclusion ) e.g. People who drink more caffeine will differ in terms of intelligence when compared to people who don't drink caffeine.
Researchers usually use directional hypotheses when previous research suggests no particular outcome. When previous research suggests a particular outcome, they'd use a non-directional hypothesis.
In an experiment, the researcher manipulates the variable and records the effect of this change on the variable.
Levels of the IV: the ❌ condition (e.g. No caffeine/ drink of water), the ❌ condition (caffeine). An effective directional hypothesis should distinguish between the IV and DV e.g. The group who drink caffeine will be more intelligent than the group who drink water. The only issue with this hypothesis is that it doesn't include the ❌ of the variables (explained in other question)
Operationalisation of variables includes ensuring the variables being investigated are measurable immeasurable subjective confounding( measurable, immeasurable, subjective, confounding ) and therefore unfuzzy, e.g. Participants who drink 200ml of coffee in one hour can answer 5 more questions in a 20 minute period than participants who drink 200ml of water in one hour.
Extraneous variables: any variable other than the IV DV CV( IV, DV, CV ) which may have an effect on the DV IV CV( DV, IV, CV ). They do not vary vary( do not vary, vary ) systematically with the IV. Confounding variables: any variable other than the IV EV DV( IV, EV, DV ) which may have affected the DV IV EV( DV, IV, EV ) so we are unsure of the true source of the changes to the DV. They vary do not vary( vary, do not vary ) systematically with the IV.
Demand characteristics: in which the participant guesses the aim outcome conclusion( aim, outcome, conclusion ) of a study, and then acts accordingly e.g. As they believe they are expected not expected( expected, not expected ) to behave, or try to over-perform to please irritate obey( please, irritate, obey ) the researcher.
Investigator effects: how the researcher participant general public expected( researcher, participant, general public, expected )'s behaviour influences a participant's behaviour e.g. Smiling at certain participants but not others. It can also refer to the actions beliefs opinions( actions, beliefs, opinions ) of the researcher related to the study design e.g. Selection of participants, the materials, the instructions etc. Leading Open Closed( Leading, Open, Closed ) questions are also an example of investigator effects
Which technique is used to minimise the effects of extraneous/confounding variables on an outcome?
Operationalisation
Randomisation
Demand characteristics
Leading questions
Randomisation Operationalisation( Randomisation, Operationalisation ) refers to the use of chance objectivity rigid structure researcher involvement participant involvement( chance, objectivity, rigid structure, researcher involvement, participant involvement ) wherever possible during an experiment to reduce investigator effects. For example, if participants must recall word from a list, the list should be randomly generated- the position is not chosen by the experimenter.
Standardisation: all participants must have the same a different a similar( the same, a different, a similar ) environment, information and experience. This includes standardised instructions beliefs ideas outcomes( instructions, beliefs, ideas, outcomes ).
Experimental Design: 1. Independent Repeated Matched( Independent, Repeated, Matched ) groups: two three( two, three ) separate groups, one group does control condition, other does experimental condition. Results are compared. 2. Repeated Independent Matched( Repeated, Independent, Matched ) measures: one group two groups( one group, two groups ), does both the control condition and the experimental condition. Results are compared. 3. Matched pairs: choosing one group, then choosing another to match contrast compete against( match, contrast, compete against ) participants in the first group (e.g. Based on IQ, culture etc.) One group does control condition, other does experimental condition. Results are compared.
Name two advantages of the independent group design
Order effects are not a problem
Participants less likely to guess aims
Cost- effective
Lack of participant variables
Name two disadvantages of the independent groups design
Quite expensive
Participant variables
Order effects
Easy to guess aims
Name two advantages of the repeated measures design
Fewer participant variables
Cheaper
Fewer order effects
No demand characteristics
Name two disadvantages of the repeated measures design
Expensive
Name two advantages of the matched pairs design
No order effects
Fewer demand characteristics
Cheaper and faster
No participant variables
Name two disadvantages of the matched pairs design
Some participant variables
More expensive and time consuming
allocation: allocating participants randomly to the conditions. This should evenly distribute participant characteristics (e.g. Names in a hat). -balancing: half participants take part in condition A then B, the other half do B then A. This helps control effect, although it doesn't remove them entirely.
Lab experiment: takes place in a ❌ environment in which the ❌ manipulates the ❌, while maintaining ❌of the extraneous variables.
Field experiment: takes place in a ❌ setting in which the ❌ manipulates the IV.
Natural experiment: takes place in a ❌ setting in which the change in the IV ❌ brought about by the ❌, but would occurred anyway.
Quasi experiment: there is ❌of the IV, it exists anyway (e.g. Age or gender)
Name three advantages of lab experiments
Control over variables
Easily replicable
High internal validity
Easy to generalise
High external validity
Name four disadvantages of lab experiments
Low external validity
Low internal validity
Too artificial
Difficult to generalise
Participant variables more likely
Lack of control
Difficult to replicate
Name two advantages of field experiments
More natural environment
More controlled environment
Name two disadvantages of field experiments
Ethical issues- no consent
Name two advantages of natural experiments
Provide opportunities that are normally impossible
Name two disadvantages of natural experiments
Can't randomly allocate
Name an advantage of quasi experiments
Carried out in controlled conditions
Carried out in natural environment
Easy to identify cause and effect
Few confounding variables
Name a disadvantage of quasi experiments
Cannot randomly allocate
The target population: a subset type sample( subset, type, sample ) of general population e.g. Male students for Idaho. The sample: a small group that is ideally representative of the target general( target, general ) population.
Random sampling: all most some half of the( all, most, some, half of the ) members of target population have equal haven't got an equal( have equal, haven't got an equal ) chance of being selected. Each person is added to a list and then given a number, and the sample is generated via a computer researcher( computer, researcher ) (e.g. Computer-based randomiser)
Systematic sampling: every nth single other( nth, single, other ) person is selected e.g. Every 5th pupil on a school register. A sampling frame (alphabetised list of target population) is produced and every nth person is selected.
Stratified sampling: the sample reflects the proportions of people in particular sub-groups (strata omega gamma stratifiers( strata, omega, gamma, stratifiers )). The researcher calculates what percentage each strata is of the general population world target population( general population, world, target population ) (e.g. 40% female) and then participants are randomly systematically( randomly, systematically ) sampled accordingly. With reference to the example above, if you were to have 20 participants, 8 would need to be female in order to be representative.
Opportunity sampling: selecting anyone who is willing unwilling randomly sampled( willing, unwilling, randomly sampled ) and able to participate.
Volunteer sampling: involves the researcher advertising the study, and participants selecting themselves others the researcher( themselves, others, the researcher ) to take part (volunteer)z
Name and advantage of random sampling
Free from researcher bias
Quick and easy to do
Very representative
Name three disadvantages of random sampling
Difficult and time consuming
Sample can still be unrepresentative
Participants can refuse to take part
Researcher bias can affect sample
Name two advantages of systematic sampling
Avoids researcher bias
Quite representative
Entirely representative
Name two advantages of stratified sampling
Representative sample
Strata identifies all ways people are different
Name a disadvantage of stratified sampling
Complete representation impossible
Not representative
Researcher bias
Name an advantage of opportunity sampling
Convenient
Representative
Name two disadvantages of opportunity sampling
Unrepresentative
Inconvenient
Expensive+ time consuming
Name an advantage of volunteer sampling
Easy+ quick
Name a disadvantage of volunteer sampling
Volunteer bias
Time consuming
Informed consent: making participants aware of the aims beliefs researcher's name( aims, beliefs, researcher's name ), procedures, their rights lack of rights( rights, lack of rights ) and the use of the data. It can make a study seem unnatural more natural( unnatural, more natural ) if the participant knows the aims.
Deception: deliberately accidentally( deliberately, accidentally ) misleading or withholding information. This means participants can't give informed consent behave naturally interact adequately( give informed consent, behave naturally, interact adequately ). It can be justified if it means participants' behaviour is more natural artificial( natural, artificial ) and they are not suffering.
Protection from harm help researcher public( harm, help, researcher, public ): participants should not suffer any form of harm during the experiment. The harm can be psychological e.g. Feeling embarrassed, guilty or inadequate.
Privacy: participants researchers the general public( participants, researchers, the general public ) control information about themselves. Confidentiality: this involves the right to have our personal medical educational public( personal, medical, educational, public ) data protected.
To deal with informed consent, researchers should send a consent letter demand order( letter, demand, order ), and only go ahead when this is signed.
Dealing with protection from harm and deception: debriefing standardisation operationalisation sampling( debriefing, standardisation, operationalisation, sampling ) can be used to ensure the participants know the aims and details problems( details, problems ) of the study. It should also reassure participants that they have the right to withhold enclose all( withhold, enclose all ) information, and that they can be provided counselling if necessary.
Dealing with confidentiality: this often done by referring to participants by numbers first names last names( numbers, first names, last names ) or initials code names( initials, code names ). They are also reminded during debriefing that their data will be protected throughout.
A pilot study is a small-scale version of the actual investigation.
Pilot studies often use fewer more male female( fewer, more, male, female ) participants, and are utilised to test if the investigation aim hypothesis( investigation, aim, hypothesis ) runs smoothly. This also involves identifying any issues positives participants( issues, positives, participants ) so they can be modified in order to save time and money in the future.
Single blind trial: only researcher participant( researcher, participant ) knows aim, controls demand characteristics participant variables order effects researcher bias( demand characteristics, participant variables, order effects, researcher bias ). Double blind trial: both researcher and participant don't know know( don't know, know )aim, preventing demand characteristics and investigator effects participant variables order effects( investigator effects, participant variables, order effects ).
Control group: group of participants whose purpose is for comparison proof results highlighting change in DV( comparison, proof, results, highlighting change in DV ). The experiment group tests the effects of changing the IV, and this is compared to results from the control group.
Naturalistic observation: watching and recording behaviour in the setting in which it would normally not normally never( normally, not normally, never ) be performed. Controlled observation: watching and recording behaviour within a structured natural( structured, natural ) environment e.g. In which some variables are managed
Covert observation: participants' behaviour is recorded and watched without with( without, with ) their knowledge or consent. Overt observation: participants' behaviour is recorded and watched with without( with, without ) their knowledge and consent
Participant observation: researcher becomes doesn't become( becomes, doesn't become ) member of group whose behaviour he/she is recording. Non-participant observation: researcher doesn't become becomes( doesn't become, becomes )a member of group whose behaviour he/she is recording.
Naturalistic observations have high external internal( external, internal ) validity as findings can can't( can, can't ) be generalised to everyday life. Lack of control decreases replicability generalisability( replicability, generalisability ) and extraneous variables could also be present. Controlled observations can't can( can't, can ) be easily generalised, but extraneous variables are less more( less, more ) common so replication is easier harder( easier, harder )
