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Inferential stats intro part 1
 

Inferential stats intro part 1

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For A2 Psychology AQA A

For A2 Psychology AQA A
Redruth School

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    Inferential stats intro part 1 Inferential stats intro part 1 Presentation Transcript

    • 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. Inferential StatisticsOutcomes:ALL – Complete own MEMORABLE notesusing mnemonics / mindmaps on eachobjective. Key words you need definitions for:MOST – Complete activities set • Probability • Level of significanceSOME – Complete Tea Test problem by • Type 1 errorend of the lesson •Type 2 error
    • Inferential Statistics Tests Make inferences about thepopulations from which the samples are drawn
    • Descriptive Statistics vs. Inferential Statistics Allow us to say whether Allows us to draw difference is significant conclusions Through use of graphs This difference Is significant
    • Inferential Stats Watch the clip – the tea test. Task: Why are inferential statistical tests needed? (Also see Pg 286)
    • Probability How likely is it that something will happen?A number between 0 and 10 = something DEFINITELY will NOT happen1 = something DEFINITELY will happen NUMBER OF PARTICULAR OUTCOMES Probability isPROBABILITY = expressed as NUMBER OF POSSIBLE OUTCOMES “p” Task: What is the probability of a coin landing heads up? How would you express this as a decimal?
    • ProbabilityInferential tests use probability to ascertain thelikelihood that a pattern of results could havearisen by chance.If the probability of the results occurring bychance is below a certain level we assume theseresults to be significant
    • ChanceWe can state how certainwe are the results are not Real due to chance difference
    • Key questions for Psychologists…•How far does what we have found in our sample reflect thegeneral 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 foundbetween time spent playing aggressive computer games andobserved levels of aggression?Is this the case for all 10 yr old boys?Inferential tests will tell us how probable it is that the correlationcould have occurred by chance.
    • Watch the clip – P ValuesTask:Also referring to “Chance” pg 286What 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.
    • P-levels/Significance Levels P ≤0.10 C H P ≤0.05 A N P ≤0.01 C E P ≤0.001 We can also write these as 10%, 5%, 1%, 0.1%
    • Significant?If our test is significant we canReject our null hypothesis and accept ouralternative/experimental hypothesisIf our test is not significant we canAccept our null hypothesis and reject ouralternative/experimental hyp “If P is low…null must go.”
    • Type 1 and Type 2 ErrorsType 1 errorRejecting a null hypothesis when we should not P level too tight Type 2 error Accepting a null hypothesis when we should not P level too loose
    • ErrorsThrowing a coin 10 times there is a 17%probability of getting a headIf we set our p level too low it looks like there isphenomena there is notThrowing a coin 100 times there is a 0.005%chance of getting a headIf we set it too high we may miss phenomena
    • Why do we make errors?Type 1 – if we allow ourselves a p=.05 sig levelthen we allow yourself a 1 in 20 chance ofmaking an errorType 2 – too stringent a p level means we maymiss something
    • Watch the Type 1+2 errors videoTaskIn your own terms explain thedifference between a type 1 and type 2error
    • Refer to Pg 287 Type 1+2 errorsTask:Why might researchers choose to use p≤0.01 in preference to p≤0.05?
    • 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.