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Statistical Fridays

Statistical Fridays. J C Horrow, MD, MS STAT Clinical Professor, Anesthesiology Drexel University College of Medicine. Session Review. New concepts: Observations vary Observational vs. experimental data Graphing your data Example: 50 patients induced with TPL or PPF Homework:

june
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Statistical Fridays

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  1. Statistical Fridays J C Horrow, MD, MSSTAT Clinical Professor, Anesthesiology Drexel University College of Medicine

  2. Session Review • New concepts: • Observations vary • Observational vs. experimental data • Graphing your data • Example: • 50 patients induced with TPL or PPF • Homework: • 20 patients given spinals for C-section

  3. Session Summary • A statistic is a function of the data. • Useful statistics have known distributions. • Statistical tests are based on a “null” hypothesis to be disproved. • The “Normal” distribution is the most common and useful distribution.

  4. Statistic: function of data • Average of all observations (mean) • Average of the smallest and largest • The middle observation (median) • The largest observation • The first observation USES: for estimation and testing

  5. ESTIMATION HYPOTHESIS TESTING Point Estimators Interval Estimators Statistical Inference mean, variance 95% Conf. Int.

  6. Useful Statistics • Are unbiased (on average, hit the mark) • Have minimal variance • Have known distributions Sample average ~ Normal (m, s2/N) Sample average ~ t (m, s2/N) Sample standard deviation = s (N-1)s2/ s2 ~ c2(n-1)

  7. TPL PPF 0 1 2 3 4 5 6 7 8 910 12 14 16 18 20 Useful Statistics Suggest several useful statistics for the induction data and state the assumptions for each.

  8. TPL PPF 0 1 2 3 4 5 6 7 8 910 12 14 16 18 20 Concept #3: Null Hypothesis Statistical tests are based on a “null” hypothesis to be disproved. EXAMPLES: • mTPL = mPPL for DSBP • MEDIANTPL < MEDIANPPL • s2TPL = s2PPL

  9. Concept #3: Statistical Tests Statistical tests utilize “test statistics” (duh?) • To test equality of means:mTPL – mPPL and compare it to zero • To test equality of medians:Sum of RanksTPL - Sum of RanksPPL • To compare sample variances: s2TPL / s2PPL and compare it to one

  10. The Normal Distribution Most common way numbers distribute • Occurs when measurement results from sum of individual parts • Sums and averages • “Bell”-shaped curve; symmetric • Observations clustered in center; fewer occur farther from center. • No “cut-off” at either end

  11. The Normal Distribution

  12. Session Review • New concepts: • Statistics are functions of the data • Useful statistics have known distributions • Statistical inference = estimation; testing • Tests seek to disprove a “null” hypothesis • Example: • 50 patients induced with TPL or PPF • Homework: • 20 patients given spinals for C-section

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