HYPOTHESES
- Created by: Shumaira Ahmed
- Created on: 18-05-22 09:50
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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...'
- Any
results or trends found are due to error or statistical chance.
- 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.
- One-tailed Hypothesis: Directional-Predicts the exact direction of which the independent variable will
affect the dependent variable.
- 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)
- 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.
- Clearly identify the IV and DV in a measurable way
- 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.
- Saying results show a significant relationship (IV did affect DV) when this was incorrect.
- 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
- Thinking the results were not significant when in fact they were significant (IV DID affect DV).
- Null Hypothesis: A hypothesis that predicts that the IV has no effect on the dependent variable.
- Correlational hypothesis: Predicts there will be a relationship between the two variables
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