Significance

• Probability= A measure of the likelihood that a particular event will occur where 0 indicates statistical impossibility and 1 indicates statistical certainty.
• Significance= A statistical term that tells us how sure we are that a difference or correlation exists. A significant result means that the researcher can reject the null hypothesis.
• Critical value= When testing a hypothesis the numerical boundary or cut-off point between acceptance or rejection of the null hypothesis.
• Type 1 error= The incorrect rejection of a true null hypothesis.
• Type 2 error= The failure to reject a false null hypothesis.
• The null hypothesis:

  • The null hypothesis states there is no difference between the conditions whereas the alternate hypothesis states that there is a difference.
  • The statistical test determines which one is true.
• Level of significance:

  • Usually 5% or 0.05 in psychology.
  • This is the point at which the researcher can claim to have found a large enough difference.
  • This is when they can reject the null hypothesis.
• Calculated and critical values:

  • Each statistical test has a table of critical values.
  • To check for significance the calculated value must be compared with the critical value.
• • One-tailed test: If the hypothesis is directional.
  • Two-tailed test: if the hypothesis is non-directional.
• The number of participants in the study is referred to as N.