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BASIC BIOSTATISTICS

   Diane Flynn, LTC, MC
   Colin Greene, LTC, MC
Objectives


Overview of Biostatistical
Terms and Concepts
Application of Statistical Tests
Why Use Statistics?
Descriptive Statistics
• identify patterns
• leads to hypothesis generating
Inferential Statistics
• distinguish true differences from
  random variation
• allows hypothesis testing
Why Use Statistics?
          Cardiovascular Mortality in Males


    1.2
      1
    0.8
SMR 0.6                                        Bangor
    0.4                                        Roseto
    0.2
      0
       '35-   '45-    '55-     '65-    '75-
        '44    '54     '64      '74     '84
                                              AJPH 1992
Types of Data
Numerical
       • Continuous
       • Discrete
Categorical
       • Ordinal
       • Nominal
Descriptive Statistics

Identifies patterns in the data
Identifies outliers
Guides choice of statistical test
Percentage of Specimens Testing
         Positive for RSV

       Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun

South 2    2   5   7   20   30   15   20   15   8    4    3

North- 2   3   5   3   12   28   22   28   22   20   10   9
east
West 2     2   3   3   5    8    25   27   25   22   15   12

Mid-   2   2   3   2   4    12   12   12   10   19   15   8
west
Descriptive Statistics
           Percentage of Specimens Testing Postive for
                          RSV 1998-99
35
30
25                                                 South
20                                                 Northeast
15                                                 West
10                                                 Midwest
 5
 0
     Jul     Sep    Nov   Jan   Mar   May    Jul
Describing the Data
        with Numbers

Measures of Central Tendency
  • MEAN -- average
  • MEDIAN -- middle value
  • MODE -- most frequently observed
             value(s)
Distribution of Course Grades
            14
            12
            10
Number of   8
 Students   6
            4
            2
            0
                 A   A- B+ B   B- C+ C   C- D+ D   D-   F
                                 Grade
Describing the Data
       with Numbers

Measures of Dispersion
  • RANGE
  • STANDARD DEVIATION
  • SKEWNESS
Measures of Dispersion
• RANGE
   • highest to lowest values
• STANDARD DEVIATION
   • how closely do values cluster around the
     mean value
• SKEWNESS
   • refers to symmetry of curve
Measures of Dispersion
• RANGE
   • highest to lowest values
• STANDARD DEVIATION
   • how closely do values cluster around the
     mean value
• SKEWNESS
   • refers to symmetry of curve
Standard Deviation
Curve A



           Curve B




          σB
   σA
Measures of Dispersion
• RANGE
   • highest to lowest values
• STANDARD DEVIATION
   • how closely do values cluster around the
     mean value
• SKEWNESS
   • refers to symmetry of curve
Skewness
       Curve A             Curve B
Mode
       Median




                               negative
                               skew
                Mean
The Normal Distribution
                     .

Mean = median =
mode




                         Mean, Median, Mode
Skew is zero
68% of values fall
between 1 SD
95% of values fall
between 2 SDs
                                              1   2σ
                                              σ
Inferential Statistics

Used to determine the likelihood that a
conclusion based on data from a
sample is true
Terms

p value: the probability that an observed
  difference could have occurred by
  chance
Hypertension Trial

DRUG Baseline mean SBP F/u mean SBP


 A          150            130


 B          150            125
Terms

confidence interval:
The range of values we can be
 reasonably certain includes the true
 value.
30 Day % Mortality
Study      IC STK Control    p     N

Khaja       5.0     10.0    0.55   40

Anderson    4.2     15.4    0.19   50

Kennedy     3.7     11.2    0.02 250
95% Confidence Intervals

    Khaja
    (n=40)

Anderson
 (n=50)


                 Kennedy
                  (n=250)


-.40 -.35 -.30 -.25 -.20 -.15 -.10 -.05 .00   .05   .10   .15   .20
Types of Errors

                                Truth

                          No            Difference
                          difference
Conclusion   No                          TYPE II
             difference                 ERROR (β )
             Difference    TYPE I
                          ERROR (α)
                          Power = 1-β
What Test Do I Use?
1. What type of data?

2. How many samples?

3. Are the data normally distributed?

4. What is the sample size?

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Stats7.0

  • 1. BASIC BIOSTATISTICS Diane Flynn, LTC, MC Colin Greene, LTC, MC
  • 2. Objectives Overview of Biostatistical Terms and Concepts Application of Statistical Tests
  • 3. Why Use Statistics? Descriptive Statistics • identify patterns • leads to hypothesis generating Inferential Statistics • distinguish true differences from random variation • allows hypothesis testing
  • 4. Why Use Statistics? Cardiovascular Mortality in Males 1.2 1 0.8 SMR 0.6 Bangor 0.4 Roseto 0.2 0 '35- '45- '55- '65- '75- '44 '54 '64 '74 '84 AJPH 1992
  • 5. Types of Data Numerical • Continuous • Discrete Categorical • Ordinal • Nominal
  • 6. Descriptive Statistics Identifies patterns in the data Identifies outliers Guides choice of statistical test
  • 7. Percentage of Specimens Testing Positive for RSV Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun South 2 2 5 7 20 30 15 20 15 8 4 3 North- 2 3 5 3 12 28 22 28 22 20 10 9 east West 2 2 3 3 5 8 25 27 25 22 15 12 Mid- 2 2 3 2 4 12 12 12 10 19 15 8 west
  • 8. Descriptive Statistics Percentage of Specimens Testing Postive for RSV 1998-99 35 30 25 South 20 Northeast 15 West 10 Midwest 5 0 Jul Sep Nov Jan Mar May Jul
  • 9. Describing the Data with Numbers Measures of Central Tendency • MEAN -- average • MEDIAN -- middle value • MODE -- most frequently observed value(s)
  • 10. Distribution of Course Grades 14 12 10 Number of 8 Students 6 4 2 0 A A- B+ B B- C+ C C- D+ D D- F Grade
  • 11. Describing the Data with Numbers Measures of Dispersion • RANGE • STANDARD DEVIATION • SKEWNESS
  • 12. Measures of Dispersion • RANGE • highest to lowest values • STANDARD DEVIATION • how closely do values cluster around the mean value • SKEWNESS • refers to symmetry of curve
  • 13. Measures of Dispersion • RANGE • highest to lowest values • STANDARD DEVIATION • how closely do values cluster around the mean value • SKEWNESS • refers to symmetry of curve
  • 14. Standard Deviation Curve A Curve B σB σA
  • 15. Measures of Dispersion • RANGE • highest to lowest values • STANDARD DEVIATION • how closely do values cluster around the mean value • SKEWNESS • refers to symmetry of curve
  • 16. Skewness Curve A Curve B Mode Median negative skew Mean
  • 17. The Normal Distribution . Mean = median = mode Mean, Median, Mode Skew is zero 68% of values fall between 1 SD 95% of values fall between 2 SDs 1 2σ σ
  • 18. Inferential Statistics Used to determine the likelihood that a conclusion based on data from a sample is true
  • 19. Terms p value: the probability that an observed difference could have occurred by chance
  • 20. Hypertension Trial DRUG Baseline mean SBP F/u mean SBP A 150 130 B 150 125
  • 21. Terms confidence interval: The range of values we can be reasonably certain includes the true value.
  • 22. 30 Day % Mortality Study IC STK Control p N Khaja 5.0 10.0 0.55 40 Anderson 4.2 15.4 0.19 50 Kennedy 3.7 11.2 0.02 250
  • 23. 95% Confidence Intervals Khaja (n=40) Anderson (n=50) Kennedy (n=250) -.40 -.35 -.30 -.25 -.20 -.15 -.10 -.05 .00 .05 .10 .15 .20
  • 24. Types of Errors Truth No Difference difference Conclusion No TYPE II difference ERROR (β ) Difference TYPE I ERROR (α) Power = 1-β
  • 25. What Test Do I Use? 1. What type of data? 2. How many samples? 3. Are the data normally distributed? 4. What is the sample size?