Psych1

• Strengths of natural experiments

  1. Natural Experiment, high ecological validity

  2. No demand characteristics, don't know they're being measured. Therefore sure they're acting how they normally would
• What is an aim?

  A general statement outlining what the researcher is investigating e.g to investigate the capacity of STM
• What is an Independent Variable?


  The variable in the experiment that the researcher is manipulating to see what influence/effect it has on the DV e.g knife and pen (Johnson and Scott)
• What is a Dependent Variable?

  The variable that is measured in an experiment and is affected by the manipulation of the IV e.g accuracy of recall of perpetrator (Johnson and Scott)
• Operationalisation of Variables


  -Ensuring variables are in a form that CAN BE TESTED
• What is an Extraneous variable?

  Any variable other than the IV which affects the DV, affecting all conditions e.g participant characteristics, IQ, age, class etc.
• What is a Confounding variable?

  Any variable other than the IV which affects the DV, only affecting one condition (usually situational) e.g noise, temperature
• What are demand characteristics?


  CUES from the researcher that lead to participants GUESSING the experiment objective & changing their behaviour
• What are investigator effects?


  Where the investigator's behaviour has an effect on the research outcome
• Difference between Quantitative & Qualitative data

  QUANT= Numerical Data

  QUAL= Recordable info, but worded
• Hypothesis writing


  Definition: a testable statement in which the researcher predicts the outcome. *Exam tip: can be asked to identify the difference between aim and hypothesis.

  Use the template: There will be a significant increase/decrease/difference in the DV when IV1 compared to IV2. Examples:

  - There will be a significant increase in the maths test outcomes when jazz music is played compared to when pop music is played

  - There will be a significant increase in the participants estimated speed when a more impactful verb is used compared to when a less impactful verb is used
• Operationalisation of variables


  Operationalisation: clearly defining variables so it can be measured numerically/specifically

  Why do we operationalise the DV?

  - to make findings more objective

  - helps researcher replicate studies
• Null and Alternate hypothesis

  Null- a statement suggesting there's no effect

  Alternate- a statement suggesting there is an effect

  Examples of Null:

  - (directional): there will be no specific decrease in the GCSE maths test outcomes when jazz music is played compared to pop music

  - (non-directional): there will be no specific difference when...

  Examples of alternate: *generally write alternate unless specified otherwise

  - (non-directional): there will be a significant difference when jazz music is played compared to pop music

  - (directional): there will be a significant increase/decrease when...
• Directional Hypothesis


  Directional- specific about whether the change will be an increase or decrease (there's prior research)

  Examples of directional:

  - there will be a significant increase in maths test outcomes when jazz music is played compared to pop music
• Non-Directional Hypothesis


  Non-directional- certain about difference but no the direction of the difference between the DV and two conditions (used when there is no prior research)

  
  

  Examples of non-directional:

  - there will be a significant difference between the test scores when jazz music is played compared to pop music
• Null hypothesis


  States there is NO RELATIONSHIP between the variables being studied
• Falsifiability


  Suggests that for a theory to be considered scientific, it must be abler to be tested & proven as true
• Sample


  The participants you select from a TARGET population to make generalisations to the rest of the population about
• Representative


  The extent to which a sample mirrors the researcher's target population
• Generalisability


  The extent to which the findings can be applied to the larger population
• What is an experiment?

  A research method where the IV is manipulated in order to measure its effect on the operationalised DV.

  Four types:

  1. Lab experiments

  2. Natural experiment

  3. Field experiment

  4. Quasi experiment
• Laboratory experiments


  - high levels of control

  - conducted in an artificial environment

  - IV created by the researcher

  - IV manipulated to measure its effect on the DV
• Strengths of Lab experiments

  1. Control Extraneous Variables, creating a standardised procedure

  >Increases reliability.

  2. Allows objective measurements to be used, quantitative data more measurable
• Weaknesses of Lab experiments

  1. Low ecological validity, can't be generalised to everyday life

  2. Participants are generally aware that their behaviour is being measured/assessed (LEADS TO DEMAND CHARACTERISTICS)
• Field experiments


  - Manipulated independent variable, but in a real life setting

  - limited level of control

  - IV is still manipulated to observe effects on DV

  *Exam tip: must evaluate in comparison to another type of experiment
• Strengths of field experiments

  1. HIGHER ECOLOGICAL VALIDITY than a lab study (real life)

  2. Less demand characteristics (don't know they're being studied)
• Weaknesses of field experiments

  1. Not controlling variables, can't create standardised procedure, decreasing reliability

  2. Can't ensure DV changes are causal relationship to the IV because of extraneous varibles
• Natural experiments


  - IV occurs naturally and is out of control of the researcher

  - Everyday environment

  - limited control

  - conducted in a natural environment
• Weaknesses of natural experiments

  1. Can't establish standardised procedure, lack of control of extraneous varibales

  2. Cause & Effect relationship weakened as extraneous variables exist, don't know if DV changes are due to IV

  3. Random allocation cannot take place, we have no control over which condition participants are placed in.

  >Decreases validity.
• Quasi experiments


  - Naturally occurring IV that the researcher investigates (such as: people with Anorexia)

  -the IV is based on existing differences between participants,

  -The researcher didn't cause the depression, it already existed and was a difference between participants.
• Strengths of quasi experiments

  1.Researcher can investigate ethically things that would generally be unethical to create in someone

  (Causing depression is highly unethical)

  >Can investigate effect of behaviours & variables without causing harm

  
  

  2. High Internal Validity (confident that the causal explanation investigated isnt affected by extraneous variables)
• Weaknesses of quasi experiments

  1. Causal effect weakened, ppts have further different characteristics that can't be controlled

  (eg; differing in socio-economic level)
• What is reliability?


  How consistent findings of an experiment are, whether they occur in a similar way repeatedly. If results are consistent they're said to be reliable.
• How do you test reliability?


  Test-Restest method:

  1) Participant completes experimental task *what task-apply

  2) After a period of time, the same participant completes the same experimental task again

  3) the researcher runs a Spearmans Rho correlational analysis with variable 1 as the participant's test score (changeable) from the 1st test and variable 2 as the same participant's test scores from the 2nd test. A strong positive correlation (with a correlational coefficient of 0.8 or higher) indicates a high reliability.
• How do you improve reliability?

  Standardised procedure and high control- researcher can repeat experiment to check for consistency
• What is validity?


  How well an experiment measures what it intends to measure.

  Internal validity- extent to which the experiment measures what it intends to measure.
• What is external validity?

  The extent to which findings can be applied to wider population e.g settings, people.

  1. Ecological- extent to which findings can be applied to other environments (usually real life)

  2. Population- extent to which findings can be applied to individuals from the target population

  3. Temporal- extent to which findings can be applied to to other time period/eras
• What are the 3 experimental designs

  1. Independent groups

  2. Repeated Measures

  3. Matched pairs design
• Independent groups design


  - Participants are divided into two groups (the number of groups are dependent on the number of conditions)

  - Each group participates in one condition of the experiment
• Strengths of independent groups

  -Participants only partake in ONE condition, no order effects

  >Performance in the condition won't be worse as there is no boredom or fatigue

  >Therefore order effects won't impact participants performance or affect results so they will be due to IV manipulation (NO NEED TO COUNTER BALANCE)

  
  

  -Participants only take part in ONE condition, won't realise the aim of the experiment.

  -Won't lead to demand characteristics

  >Participants have less opportunity to change their behaviour to suit/refute the aim of the experiment.

  -Won't lead to participants displaying unnatural behaviour

  >Will lead to accurate data

  >Findings are more likely (due to IV manipulation)

  >Increases validity.