A Critique of the Proposed National Education Policy Reform
Inferential stats intro part 1
1. 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 Statistics
Outcomes:
ALL – Complete own MEMORABLE notes
using mnemonics / mindmaps on each
objective. Key words you need definitions for:
MOST – Complete activities set • Probability
• Level of significance
SOME – Complete Tea Test problem by • Type 1 error
end of the lesson •Type 2 error
3. 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
4. Inferential Stats
Watch the clip – the tea test.
Task:
Why are inferential statistical tests
needed?
(Also see Pg 286)
5. Probability
How likely is it that something will happen?
A number between 0 and 1
0 = something DEFINITELY will NOT happen
1 = something DEFINITELY will happen
NUMBER OF PARTICULAR OUTCOMES Probability is
PROBABILITY = 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?
6. 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
7. Chance
We can state how certain
we are the results are not Real
due to chance difference
8. 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.
9. 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.
10. 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%
11. Significant?
If our test is significant we can
Reject our null hypothesis and accept our
alternative/experimental hypothesis
If our test is not significant we can
Accept our null hypothesis and reject our
alternative/experimental hyp
“If P is low…null must go.”
12. Type 1 and Type 2 Errors
Type 1 error
Rejecting 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
13. 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
14. 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 of
making an error
Type 2 – too stringent a p level means we may
miss something
15. Watch the Type 1+2 errors video
Task
In your own terms explain the
difference between a type 1 and type 2
error
16. Refer to Pg 287 Type 1+2 errors
Task:
Why might researchers choose to use p≤0.01 in preference to p≤0.05?
17. 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.