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t test-origin

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Title: Null hypothesis Author: SIVAGNANAM Last modified by: Sleep Lab Created Date: 6/19/2003 11:22:50 AM Document presentation format: On-screen Show – PowerPoint PPT presentation

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Title: t test-origin


1
t test-origin
  • Founder WS Gosset
  • Wrote under the pseudonym Student
  • Mostly worked in tea (t) time
  • ? Hence known as Student's t test.
  • Preferable when the n lt 60
  • Certainly if n lt 30

2
Is there a difference?
between youmeans, who is meaner?
3
Statistical Analysis
control group mean
treatment group mean
Is there a difference?
Slide downloaded from the Internet
4
What does difference mean?
The mean difference is the same for all three
cases
medium variability
high variability
low variability
Slide downloaded from the Internet
5
What does difference mean?
medium variability
high variability
Which one shows the greatest difference?
low variability
Slide downloaded from the Internet
6
What does difference mean?
  • a statistical difference is a function of the
    difference between means relative to the
    variability
  • a small difference between means with large
    variability could be due to chance
  • like a signal-to-noise ratio

Which one shows the greatest difference?
low variability
Slide downloaded from the Internet
7
So we estimate
signal
difference between group means

noise
variability of groups
_
_
XT - XC
_
_

SE(XT - XC)

t-value
low variability
Slide downloaded from the Internet
8
Probability - p
  • With t we check the probability
  • Reject or do not reject Null hypothesis
  • You reject if p lt 0.05 or still less
  • Difference between means (groups) is more more
    significant if p is less less

9
Types
  • One sample
  • compare with population
  • Unpaired
  • compare with control
  • Paired
  • same subjects pre-post
  • Z-test
  • large samples gt60

10
Test direction
  • One tailed t test
  • Two tailed test

11
Mean systolic BP in nephritis is significantly
higher than of normal person
0.05
100 110 120 130 140
12
Mean systolic BP in nephritis is significantly
different from that of normal person
0.025
0.025
100 110 120 130 140
Slide downloaded from the Internet
13
Assumptions
  • Normal distribution
  • Equal variance
  • Random sampling

14
Otherwise prop-up data
15
Solutions
  • Normalize the data log conversion
  • Use other tests
  • - Welch test
  • - Cochranes modified t test
  • Use non-parametric test

16
Limitations - general
  • Fails to gauge magnitude of difference
  • between two means
  • (solution- do CI)
  • Only compares 2 groups
  • (solution- ifgt than 2 groups ANOVA)

17
Limitations paired t test
  • Doesnt control a No. of other variables in a
    simple pre-post design
  • In many studies pre-test not possible
  • - mortality studies
  • With-in subject variation is introduced twice
  • - e.g. in pain ratings

18
  • Hope! now your view on statistics
  • should have changed It is nothing but
  • Truth1 Truth2
  • SE (T1 T2)
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