Validity

Nota:

• are you  measuring what you are supposed to be measuring if any extraneous variables you cannot be 100% sure and cannot infer cause and effect

1. ecological validity
   1. strengths of low eco val research
      1. high control

         Nota:

         • manipulate and isolate the IV to measure the effect on the DV = infer cause and effect
         1. example

            Nota:

            • loftus and palmer changing the verb in the sentance manipulates the iv and allows to see the cause of the different speed estimations
      2. more reliable

         Nota:

         • standardised procedure making it easy to replicate 
         1. example

            Nota:

            • bruce conducted an experiment into recognising faces had standadised images and composite images and had to match composties to original = repeated in the same way
      3. high scientific equipment used

         Nota:

         • this is not something we come across every day = objective measurments to be made can collect quantitaive data allowing easy comparisons. 
         1. example

            Nota:

            • dement and kleitman when conducting a study on dreaming attatched elctrode to scalp and eye lids, this is not how people normally sleep but gives us indepth information that wouldn't be accsessiable without 
   2. weaknesses low of eco val research
      1. reductionist

         Nota:

         • as the situation is very controlled it simplifies complex behavouir by isolating the IV does not look for a combo of factors 
      2. generalisability

         Nota:

         • harder to generalise the results as often effected by social desirability and demand characterisitcs due to high levels of control
         1. example

            Nota:

            • dement and kleitman and dreaming - not being allowed caffine and nicotine and being woken up during the night = not generalised to a normal nights sleep
      3. lack of qual data

         Nota:

         • as scientfic methods collect objective quantitaive data and this lacks reason and insight 
2. internal

   Nota:

   • does the study measure what its supposed to within the study itself
3. external

   Nota:

   • does the study measure what it claims to outside the study
4. concurrent

   Nota:

   • comparing the measure with an already existing established measure of the same variable to check for concurrent validity 
5. face

   Nota:

   • are you measuring what you say you want to measure
6. population

   Nota:

   • the extent to which the results of a study can be generalised to the target population
7. strengths
   1. highly reliable
   2. controlled
   3. useful
   4. generalisable
8. weaknesses
   1. ethics