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Statistical Testing: The Sign Test - Coggle Diagram
Statistical Testing: The Sign Test
The Concept of Significance:
Statistical testing must be used to see whether the difference found occurred by chance
Statistical Test
- determining whether hypotheses should be accepted or rejected - find out whether differences/relationships between variables are significant or are likely to have occurred by chance
The Sign Test:
used to analyse the difference in scores between related items
Test of difference
Repeated measures
Nominal data (frequency headcount)
The Concept of Probability:
P = 0.05 (5%)
The level at which a researcher decides that the findings are significant (accept alternative and reject null hypothesis)
P = 0.01 may be used, only when research involves a human cost (clinical trials), or cannot be repeated and researchers need to be more confident in their findings
In the absence of proof/certainty, psychologists have decided that 5% will suffice, as significant differences/associations can be found but never statistical certainties
Phrases such as 'this suggests' rather than 'this proves' are used
Probability (p) refers to the likelihood that certain events will occur - applied to understanding the findings of a study
The Critical Value:
Calculated value (S - the less frequent sign) needs to be compared with a critical value to decide whether the result is significant or not - the critical values for a sign test are given in a table of critical values
The significance level - P = 0.05
Number of ppts in the investigation (N)
Whether the hypothesis is directional (one-tailed) or non directional (two-tailed)
The calculated value (S) must be equal to or less than the critical value at the 0.05 level of significance