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  • Hypothesis: A specific, testable production of how one variable in an experiment will affect another variable.
    • Null Hypothesis: A hypothesis that predicts that the IV has no effect on the dependent variable.
      • Any results or trends found are due to error or statistical chance.
        •  Accepted if statistical tests show no significance.
      • 'There will be no significant difference...'
    • Alternate Hypothesis: A hypothesis that states there is a significant relationship between the two variables being studied and that the results were not due to chance, therefore supporting the theory being investigated.  
      • One-tailed Hypothesis: Directional-Predicts the exact direction of which the independent variable will affect the dependent variable.
        • Eg. Girls will achieve higher scores in the exams than boys
      • Two-tailed Hypothesis: Nondirectional- Predicts that an effect will occur between the IV and DV, but not in a specified direction.
        • Eg. There will be a significant difference between girls and boys scores in the exams.
    • Operationalise
      • Clearly identify the IV and DV in a measurable way
        • Eg. Eating their favourite food will have a positive effect on the participants’ mood (measured on a scale of 1 - 10, 1 being extremely negative, 10 being extremely positive in response to “How do you feel?) compared to eating their least favourite food.
          • (This is alternate one-tailed)
    • Type 1 Error: False positive
      • Saying results show a significant relationship (IV did affect DV) when this was incorrect.
        • Acceptance of alternate when null should be accepted.
    • Type 2 Error: False negative
      • Thinking the results were not significant when in fact they were significant (IV DID affect DV).
        • Acceptance of null when alternate should be accepted
  • Correlational hypothesis: Predicts there will be a relationship between the two variables


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