probability and significance

• Null hypothesis suggests no causal relationship exists between the independent variable and the dependent variable
• Alternative hypothesis suggests a causal relationship between IV and DV
• IV is changed
• DV is measured
• P=<0.05: Psychologists accept a 1 in 20 chance that their results are due to chance variation
• P=<0.05 means there is less than a 5% probability the results gained are due to chance
• P=<0.01: Is occasionally used by psychologists, this level of significance is usually required of studies attempting to support a particularly controversial theory or if the psychologist is conducting a replication
• Using the P=<0.01 level reduces the probability of accepting the alternate hypothesis in error to less than 1 in 100
• Type I (1) error

  • When researchers accept the alternate hypothesis (reject null) in error
  • Data collected has passed the level of significance, but really the findings were due to chance variation
  • Using P=<0.05 means this will happen in around 1 in 20 studies
• Type II (2) error

  • when researchers reject the alternate hypothesis (accept null) in error
  • data collected has not passed the level of significance
  • but really the participants not acting as expected is due to chance variation hiding the causal relationship between IV & DV
• To reduce the chance of a Type 1 error, a researcher can decide to use a P=<0.01 level of significance, however, this then increases the likelihood of a Type 2 error
• Using P=<0.05 reduces the chance of a Type 2 error but increases the possibility of a Type 1 error