Research Method 3

Research Method 3

1. Reliability

   • Test-retest reliability (experiment)
     • If the measure depends upon interpretation of behaviour, we can compare the results from two or more tests in different times/ groups
       • if the results in the two tests are similar, we can assume the test is reliable
         • to deal with this the tests must then be reformed ti ensure consistency
   • split half reliability (test)
     • splitting a test into two halves, and comparing the scores in both halves
       • if the results on the two halves are similar, we can assume the test is reliable
         • to deal with this the tests must then be reformed ti ensure consistency
   • Inter-Rater reliability (observation)
     • The measure (observation sheet) is administered to the same group of people twice using different raters (observers)
       • if there is high agreement between the raters, the measure is consistent
         • to deal with this strict criteria must be provide to enable consistent observation

2. Validity

   • Internal validity: the extent to which the outcome of the study is the direct result of the manipulated independent variable
   • External validity: the extent to which the findings apply to other people and situations
   • Construct validity: the extent to which the test measures what it claims to measure
   • Predictive Validity: the extent to which results from a test or a study can predict future behaviour.
   • Ecological validity: the extent to which the findings still explain the behaviour in different situations.
   • Population validity: the extent to which the findings can be applied to other people

3. Objectivity

   • being objective refers to the need to be impartial and judgement free.
   • it is important that the DV is measured objectively so that the opinions or judgements of the researcher do not affect how the DV is recorded.

4. Inferential statistics

   • a inferential test of significance will indicate whether we should retain or reject a hypothesis
   • we use a inferential test to decide whether or not to accept the null hypothesis because it tells us whether the results were likely due to chance or not

5. Nominal level of data

   • most basic form of data you can gather because it does not tell you very much information about the data set or results; the data gathered are categorical or grouped and the total number of values in each category or group is calculated.

6. Ordinal level of data

   • tells us a little bit more information about the values in the data set. Ranked into an order or position.