Week 2 Hypothesis Structuring (Textbooks) Flashcards
To supplement our understanding of hypothesis structuring covered in the first part of lecture 2
How does Andy Field define a hypothesis?
*A hypothesis is a prediction about the state of the world
How does Andy Field define the Experimental Hypothesis?
- a synonym for the alternative hypothesis
How does Andy Field define the Alternative Hypothesis?
- The prediction that there will be an effect
- i.e. that my experimental manipulation will have some effect or
- that certain variables will be related to each other
How does Andy Field define the Null Hypothesis?
- the reverse of the experimental hypothesis
* that my prediction is wrong and the predicted effect does not exist
Why do we need a null hypothesis?
- we need a null hypothesis because we cannot prove the experimental hypothesis using statistics, but we can reject the null hypothesis
- If our data gives us confidence to reject the null hypothesis, then this provides support for our experimental hypothesis
What does Andy Field tell me about directional hypothesis?
- Hypothesis can be directional or non-directional
* A directional hypothesis states that an effect will occur, but it also states the direct of the effect
What do inferential statistics tell me according to Andy Field?
- Inferential statistics helps to confirm or reject my predictions,
- telling me whether the experimental hypothesis is likely to be true
Why does Fisher recommend 95% as a useful confidence threshold?
- only when I am 95% certain that a result is genuine (i.e. not chance) should I accept it to be true
- therefore, if there is only a 5% probability (.05) of something occurring by chance, then we can accept this as a genuine effect
How does including effect sizes with significance levels of 0.05 help interpretation of results?
The use of effect sizes strikes a balance between using arbitrary cut-offs (.01, .05) for significance and assessing whether an effect is meaningful within the research context
