Inferential stats intro part 1
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Transcript of Inferential stats intro part 1
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Inferential Statistics
Learning Objectives:
•Understand the nature of probability• Understand the role of probability in statistical testing• Describe and choose the level of significance• Explain the difference between type 1 + type 2 errors.
Key words you need definitions for:
• Probability• Level of significance• Type 1 error•Type 2 error
Outcomes:ALL – Complete own MEMORABLE notes using mnemonics / mindmaps on each objective.
MOST – Complete activities set
SOME – Complete Tea Test problem by end of the lesson
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Inferential Statistics Tests
Make inferences about the populations from which the samples
are drawn
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Descriptive Statistics vs. Inferential Statistics
Allows us to draw conclusions
Through use of graphs
Allow us to say whetherdifference is significant
This differenceIs significant
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Inferential Stats
Watch the clip – the tea test.
Task:
Why are inferential statistical tests needed?
(Also see Pg 286)
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ProbabilityHow likely is it that something will happen?
A number between 0 and 10 = something DEFINITELY will NOT happen1 = something DEFINITELY will happen
PROBABILITY = NUMBER OF PARTICULAR OUTCOMES
NUMBER OF POSSIBLE OUTCOMES
Task:What is the probability of a coin landing heads up?How would you express this as a decimal?
Probability is expressed as “p”
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Probability
Inferential tests use probability to ascertain the likelihood that a pattern of results could have arisen by chance.
If the probability of the results occurring by chance is below a certain level we assume these results to be significant
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Chance
Real difference
We can state how certain we are the results are not
due to chance
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Key questions for Psychologists…
•How far does what we have found in our sample reflect the general population?
•Could differences shown in our test have occurred by chance?
E.g. In a study of 10 yr old boys a positive correlation is found between time spent playing aggressive computer games and observed levels of aggression?
Is this the case for all 10 yr old boys?Inferential tests will tell us how probable it is that the correlation could have occurred by chance.
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Watch the clip – P Values
Task:
Also referring to “Chance” pg 286
What does a p value of p ≤ 0.05 mean? Explain this both as a % but also what it tells us about the results of the study / correlation.
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P-levels/Significance Levels
CHANCE
P ≤0.10P ≤0.05P ≤0.01P ≤0.001
We can also write these as 10%, 5%, 1%, 0.1%
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Significant?
If our test is significant we canReject our null hypothesis and accept our alternative/experimental hypothesis
If our test is not significant we canAccept our null hypothesis and reject our alternative/experimental hyp
“If P is low…null must go.”
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Type 1 and Type 2 Errors
Rejecting a null hypothesis when we should notP level too tight
Accepting a null hypothesis when we should notP level too loose
Type 1 error
Type 2 error
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Errors
Throwing a coin 10 times there is a 17% probability of getting a head
If we set our p level too low it looks like there is phenomena there is not
Throwing a coin 100 times there is a 0.005% chance of getting a head
If we set it too high we may miss phenomena
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Why do we make errors?
Type 1 – if we allow ourselves a p=.05 sig level then we allow yourself a 1 in 20 chance ofmaking an error
Type 2 – too stringent a p level means we may miss something
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Watch the Type 1+2 errors video
Task
In your own terms explain the difference between a type 1 and type 2 error
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Refer to Pg 287 Type 1+2 errors
Task:Why might researchers choose to use p≤0.01 in preference to p≤0.05?
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Finished?•Check in with Mr Beech.
•Re-vsit any clips you are less certain on.
•Re-visit and test yourself on your schizophrenia cue cards.