EXPERIMENTS

EXPERIMENTS

1. an experiment is a way of conducting research

   • where one variable is changed - independant variable - IV
   • and the other variable is measured - dependant variable- DV

2. HYPOTHESESES

   • IS A STATEMENT OF WHAT YOU BELIEVE TO BE TRUE
   • THE AIM IS STATEMENT OF WHAT YOU ARE INTENDING TO INVESTIGATE
   • different kinds of hypothesis:
     • DIRECTIONAL HYPOTHESIS: states the kind of difference between two conditions or two groups of participants - higher or lower, faster or slower etc.
       • two tailed hypothesis: uncertain which way the investigation will go in
     • NON DIRECTIONAL HYPOTHESIS: simply states that there is a difference between two conditions of two groups of participants
       • one tailed hypothesis: predicting the direction the result will go in
     • EXPERIMENTAL HYPOTHESIS: this is the hypothesis for an experiment
     • RESEARCH HYPOTHESIS: this is the hypothesis written for any other kind of study. It's a general prediction meaning does not give enough information on the investigation suggesting another hypothesis is needed.
     • ALTERNATIVE HYPOTHESIS: states how the research hypothesis can be carried out, so it must identify what variables are being measured and changed.
     • NULL HYPOTHESIS: is a statement of no difference (no correlation) between variables being measures (dependant)

3. ETHICS

   • ethical issues occur when there is a conflict between the rights of participants and the needs of researchers
   • INFORMED CONSENT: participants should be briefed with as much information as possible about the study to enable them to make an informed judgement as to whether to take part or not
     • not everyone is capable of giving consent as studying people who are vunarable they may not know the implications of taking part - if the vunerable people don't have careers or parents they seek consent from a ethical committee
   • DECEPTION: deception should only be used if there is no alternative. We should seek apporval from ethical committee. DEBRIEFING DOESN'T JUSTIFY DECEPTION
   • RIGHT TO WITHDRAW: we must make participants aware that they are free to leave a study at anytime, even if we have paid them!! They can also refuse permission for their data to be used.
   • PROTECTION FROM HARM: participants psychological and pysiological safety must be ensured. We cannot expose them to greater to risk than their normal life experience.
   • CONFIDENTIALITY: information about our participants is protected by the data protection act. They must not be identifiable in published researcher. Participants are given numbers or referred to by a code or initals.
   • PRIVACY: often tricky if we are conducting observations when people are unaware they are being watched, but we must maintain their right to privacy. We should only observe people where they would expect to be observed by others in public places.
   • how to improve a study with ethical issues
     • do a PILOT STUDY
       • a pilot study is a small-scale trial run of a research design before doing the real thing. Its done in order to find out if certain things don't work so you can correct them before spending time on the real thing.
   • confederates
     • individuals in an experiment who are not real participants and have been instructed how to behave by the experimenter.

4. EXPERIMENTAL DESIGN

   • REPEATED MEASURES
     • A repeated measures design consists of testing the same individuals on two or more conditions..
       • weaknesses
         • one condition differs from the second condition because of the two different levels of the IV.
           • so it might be that particiapants do better in condition 2 becuase the test was easier rather than becuase the noise was less loud.
             • in this case the changes in the DV (performance of concentration) would be due to a EXTRANEOUS VARIABLES rather than the IV.
               • EXTRANEOUS VARIABLE: variables the influence the outcome of an experiment, though they are not the variables that are actually of interest.
         • it is not always possible to test the same participants twice.
         • There is also a potential disadvantage resulting from order effects, although these order effects can be minimised. Order effects occur when people behave differently because of the order in which the conditions are performed.
           • For example, the participant?s performance may be enhanced because of a practice effect, or performance may be reduced because of a boredom or fatigue effect.
           • SOLUTION: Order effects act as a confounding variable but can be reduced by using counterbalancing. If there are two conditions in an experiment the first participant can do the first condition first and the second condition second. The second participant can do the second condition first and the first condition second and so on. Therefore any order effects should be randomised.
       • advantages
         • The key advantage of the repeated measures design is that individual differences between participants are removed as a potential confounding variable. Also the repeated measures design requires fewer participants, since data for all conditions derive from the same group of participants.
   • MATCHED PAIRS
     • A matched pairs design consists of using different participants for each condition of the experiment but participant variables are controlled by matching pairs of variables on a key variable like IQ, gender.
       • In order to get the pairing precise enough, it is common to get one group of participants together and then look round for partners for everyone. Participants can be matched on variables which are considered to be relevant to the experiment in question. For example, pairs of participants might be matched for their scores from intelligence or personality tests.
       • advantage
         • order effects do not occur
         • reduce the impact of individual differrences
       • disadvantages
         • hard to conduct as it is time consuming
           • NO SOLUTION
   • INDEPENDENT MEASURES
     • An independent measures design consists of using different participants for each condition of the experiment. If two groups in an experiment consist of different individuals then this is an independent measures design.
       • advantage
         • This type of design has an advantage resulting from the different participants used in each condition - order effects do not occur
       • weakness
         • independent measures designs is the potential for error resulting from individual differences between the groups of participants taking part in the different conditions - eg gender, age, IQ
           • SOLUTION: matched pairs so they are related to the DV
         • Also an independent groups design may represent an uneconomic use of those participants, since twice as many participants are needed to obtain the same amount of data as would be required in a two-condition repeated measures design - in other words time consuming

5. SAMPLING

   • in any study a researcher will need to select people to take part. The people who are selected are referred to as the sample. This sample is selected from a larger group - the target population
     • a good sample should NOT be biased and should represent the target population. This then means that later on we can GENERALISE the results of the study to the target population
       • when generalising we need to consider
         • size
         • gender
         • age group
         • make sure it covers whole sample
         • area participants are from
         • culture
   • Volunteer sampling
     • the participants select themselves. E.G. through an advertisment
     • advantages
       • participants are more willing to co operate
     • disadvantages
       • may not be representative of target population
       • only certain people will volunteer - bias
   • random sampling
     • everyone has an equal chance of being selected. E.G. random number generator
     • advantages
       • unbiased becuase everybody in the target population has an equal chance of being selected.
     • disadvantages
       • doesn't take into account the proportions of different groups in the sample
   • oppotunity sampling
     • choosing people who are readily available to the researcher
     • advantages
       • easy and quick to do
     • disadvantages
       • may not be representative - bias

6. types of experiments

   • lab
     • A laboratory experiment is an experiment conducted under highly controlled conditions.
     • strengths
       • EXTRANOUS VARIBALES are minimised therefore higher in internal validity
       • easily replicated which demonstrates EXTRENAL VALIDITY
     • weaknesses
       • participants may not behave naturally
         • Therefore, it should be difficult to generalise findings from experiments because they are not usually ecologically valid (true to real life).
       • investigator effecrs and participants effects may reduce INTERNAL VALIDITY
   • field
     • an experiment where it is conducted in a field/natural environment (real life situations). Participants are not usually aware that experiments are taking place
     • strengths
       • less artificial
       • higher ecological validity
       • avoids participants effects and this may increase internal validity
     • weaknesses
       • less control over extranous variables - reduces internal validty
       • more time consuming and expensive
   • quasi
     • not classed as a 'true experiment' - the IV can't be manipulated it natturally occurs
     • strengths
       • A strength of some quasi experiments is that participants are often unaware that they are taking part in an investigation and they may not be as artificial as laboratory experiments.
         • real/true behaviour is shown
     • weaknesses
       • cannot demonstrate casual relationships because IV is not manipulated
       • less control over IV
     • It is worth noting that quasi experiments are very common in psychology because ethically and practically they are the only design that can be used.

7. descriptive statistics

   • mean
     • strength
       • it makes the use of the values of all the data.
         • note: that the word 'values' all measures of central tendacy use of all the data and value
     • weaknesses
       • it can be unrepresentative of all the numbers if there is any extreme values
   • mode
     • strength
       • useful when data is in categories
     • weakness
       • not a useful way of describing data when there is several modes
   • median
     • strength
       • not affected by extreme values
     • weaknesses
       • not as 'senstive' as the mean becasue not all values are used
   • percentages