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T - test

BIOCHEMISTRY

mprasadnaidu
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T - test

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  1. t-test M.Prasad Naidu MSc Medical Biochemistry, Ph.D,.

  2. 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 < 60 • Certainly if n < 30

  3. Is there a difference? between you…means, who is meaner?

  4. Statistical Analysis control group mean treatment group mean Is there a difference? Slide downloaded from the Internet

  5. What doesdifferencemean? The mean difference is the same for all three cases medium variability high variability low variability Slide downloaded from the Internet

  6. What doesdifferencemean? medium variability high variability Which one shows the greatest difference? low variability Slide downloaded from the Internet

  7. What doesdifferencemean? • a statistical difference is a function of the difference between meansrelative 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

  8. 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

  9. Probability - p • With t we check the probability • Reject or do not reject Null hypothesis • You reject if p < 0.05 or still less • Difference between means (groups) is more & more significant if p is less & less

  10. Types • One sample compare with population • Unpaired compare with control • Paired same subjects: pre-post • Z-test large samples >60

  11. Test direction • One tailed t test • Two tailed test

  12. Mean systolic BP in nephritis is significantly higher than of normal person 0.05 100 110 120 130 140

  13. 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

  14. Assumptions • Normal distribution • Equal variance • Random sampling

  15. Otherwise prop-up data

  16. Solutions • Normalize the data – log conversion • Use other tests - Welch test - Cochrane’s modified t test • Use non-parametric test

  17. Limitations - general • Fails to gauge magnitude of difference between two means (solution- do CI) • Only compares 2 groups (solution- if> than 2 groups – ANOVA)

  18. Limitations – paired t test • Doesn’t 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

  19. Hope! now your view on statistics should have changed…It is nothing but Truth1 – Truth2 SE (T1 – T2)

  20. THANK YOU

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