Statistics is useful in medicine for decision making, acquiring new knowledge, and conducting surveys. It is used in areas like diagnosis, treatment, and research studies. Variables found in the human body include height, weight, and blood pressure. Descriptive statistics are used to describe data through measures of central tendency like mean, mode, and median, and measures of variation like standard deviation and histograms. Inferential statistics are used to make conclusions from data through hypothesis testing.

1. STATISTICS IN
MEDICINE

2. What is statistics ?
`
Statistics involves
data or information
eg.
Information regarding a country
Information about weather
Information on health status
Information about a patient
Information on normal subjects
WHO
Unesco
CDC

3. What is statistics ?
Statistics is the science dealing with
analysis, presentationcollection,
& interpretation of data

4. When is statistics useful in
day-to-day life
weather report
in a shop
in an examination
in match making
in lottery

5. Weather report
rain will be
expected in the
central area
rest of the
country most
likely will be dry
Likelihood, chance
Colombo
Weather

6. In a shop
what will you
buy?
how to select?
which one is
good?
how much is
worth?
Previous knowledge
Banana

7. In an examination
what is the pass
mark?
who has sound
knowledge &
who has poor
knowledge?
half knowledge,
should you
pass?
performance, cut off point

8. In match making
in matching two
people
previous known
details
details of the
family
based on these a
prediction is
made
does it always
work ???
prediction

9. In lottery
choice between
number to win
and number to
lose
previous
experience
guesswork
prediction
prediction

10. Summary
Likelihood
Chance
Previous knowledge
Cut off point
Guesswork
Prediction
Probability
Statistics

11. When is statistics useful in
medicine ?
decision making on diagnosis
eg. a patient with headache
• does all signs and symptoms fit into
already known diseases
• previous knowledge, experience from
previous patients
• guesswork
• does it work ???

12. When is statistics useful in
medicine ?
decision making on treatment
eg. a patient with headache
• which drug to be given among A,B,C
analgesics
• previous knowledge, experience of
using them
• guesswork
• does it work ???

13. When is statistics useful in
medicine ?
acquiring new knowledge
eg. how does blood flow against
gravity
• planning a study
• doing the study
• arriving at conclusions

14. When is statistics useful in
medicine ?
surveys of diseases in a
population
eg. how far malaria has spread
• planning a study
• doing the study
• arriving at conclusions

15. Summary
Statistics is useful in medicine
in different areas
Research studies use statistics
in data analysis

16. Variables
Task: write 3 variables and 1 constant
found in the human body
eg. Height as a variable
almost all biological features show
variation
it is extremely difficult to find a
feature which does not vary???

17. Variables
What is basis of this ‘variation’ ?
fundamentally genetical
but environmental factors are
always important

18. Variables
height
weight
blood pressure
pulse rate
body temperature
size of a swelling
social status: income

19. Variables
response to a question
Do you like to treat a patient with
AIDS? Y / N / undecided
Do you agree with what I say in
this lecture? Y/N/?
Attitudes - Opinions - What we feel

20. Types of variables
a) nominal
b) ordinal
c) interval
d) ratio

21. Nominal variables
Qualitative classification
Distinct categories
No ranking
eg: gender, race, color, city
males
females

22. Ordinal variables
Qualitative classification
Categories have order or rank
eg. Socioeconomic status
• Upper
• Middle (upper & lower)
• Lower

23. Interval & ratio variables
Quantitative classification
Interval variable has no absolute
zero
eg. T°C
Ratio variable has absolute zero
eg. Kelvin temp, time, space

24. Methods of collecting data
questionnaire
interview
measurement using special
instrument
BHT studies (Bed Head Ticket)
Postal surveys

25. Different types of sampling
Simple random sample
Systematic sampling
Stratified sampling
Cluster sampling
Population Sample

26. Simple random sample
each subject in the population has an equal chance
of getting selected to the sample
each subject is given a number
subjects selected using random
numbers
use random tables or computer
generated random numbers
random table
20 17 42 28 31 17 59 66 38 61 03 51 10 55 92 52 44 25 88
74 49 04 03 08 33 53 70 11 54 48 94 60 49 57 38 65 15 40

27. Non-random sample
this is a biased sample
certain subjects have more
probability of getting selected to
the sample
certain situations randomisation is
not possible either due to practical
difficulties or difficulty in finding
subjects

28. Statistical concepts
In order to arrive at conclusions
data are analysed
Conclusions are based on
concepts just like geometric
theorems

29. Descriptive statistics
Background information
Inferential statistics
Hypothesis testing

30. Central TendencyCentral Tendency
 A single value representing a datasetA single value representing a dataset
 eg. pulse rateeg. pulse rate

31. Measures of CentralMeasures of Central
TendencyTendency
 MeanMean (x)(x)
 averageaverage
x =x = ΣΣ xx
nn
 ModeMode
 commonest value or the most frequentcommonest value or the most frequent
valuevalue
 MedianMedian
 central valuecentral value
-
-

32. exampleexample
 In a datasetIn a dataset
1 2 2 3 3 3 4 4 51 2 2 3 3 3 4 4 5
 mean = 3mean = 3
 mode = 3mode = 3
 median = 3median = 3

33. VariationVariation
 Central value gives only theCentral value gives only the
representative figurerepresentative figure
 variation of data set is not shownvariation of data set is not shown

34. Measures of VariationMeasures of Variation
 RangeRange
 from minimum to maximumfrom minimum to maximum
 Charts or graphsCharts or graphs
 bar chartbar chart
 histogramhistogram

35. Bar chartBar chart
0
5
10
15
20
25
30
35
frequency
males females
Patients with headache
generally used for categorical variables

36. Pie chartPie chart
Patients with headache
males
females

37. Multiple bar chartMultiple bar chart
0
50
100
150
200
250
average
income
1986 1987 1988
average income in 3 years
male
female

38. HistogramHistogram
Ageofemployee
38.0
37.0
36.0
35.0
34.0
33.0
32.0
31.0
30.0
29.0
28.0
27.0
26.0
25.0
24.0
23.0
50
40
30
20
10
0
Std.Dev=3.35
Mean=29.4
N=292.00
for continuous variables

39. Frequency distribution curveFrequency distribution curve

40. Standard deviation (SD)Standard deviation (SD)
 This is an accurate measure ofThis is an accurate measure of
variabilityvariability
 Calculated for continuous dataCalculated for continuous data
 Based on deviations of data from theBased on deviations of data from the
meanmean

41. Standard deviation (SD)Standard deviation (SD)
 If the data set isIf the data set is
1, 2, 2, 3, 3, 3, 4, 4, 51, 2, 2, 3, 3, 3, 4, 4, 5
 mean will be 3mean will be 3
 deviations are calculateddeviations are calculated
(3-1), (3-2), (3-2), (3-3), (3-3), (3-4),(3-1), (3-2), (3-2), (3-3), (3-3), (3-4),
(3-4), (3-5)(3-4), (3-5)
2, 1, 1, 0, 0, 0, -1, -1, -22, 1, 1, 0, 0, 0, -1, -1, -2
 deviations are squareddeviations are squared
4, 1, 1, 0, 0, 0, 1, 1, 44, 1, 1, 0, 0, 0, 1, 1, 4
 mean of squared deviation is calculated= 12/9mean of squared deviation is calculated= 12/9
 square root is taken= root of 12/9square root is taken= root of 12/9

42. Standard deviation (SD)Standard deviation (SD)
 datadata deviationsdeviations square of deviationssquare of deviations
 11 3-13-1 22 44
 22 3-23-2 11 11
 22 3-23-2 11 11
 33 3-33-3 00 00
 33 3-33-3 00 00
 33 3-33-3 00 00
 44 3-43-4 -1-1 11
 44 3-43-4 -1-1 11
 55 3-53-5 -2-2 44
12/9
variance = 12/9
SD = √12/9

43. Standard deviation (SD)Standard deviation (SD)
 In the previous example of 292 subjectsIn the previous example of 292 subjects
 meanmean = 29.41 yrs= 29.41 yrs
 SDSD = 3.35 yrs= 3.35 yrs
 minimum = 23.00 yrsminimum = 23.00 yrs
 maximum= 37.83 yrsmaximum= 37.83 yrs
 (n = 292)(n = 292)

44. Coefficient of variationCoefficient of variation
(COV)(COV)
SDSD
COV = ---------COV = --------- X 100 %X 100 %
meanmean
 COV has no unitsCOV has no units
 Variations between two variables could beVariations between two variables could be
compared using COV (eg. Blood pressure andcompared using COV (eg. Blood pressure and
pulse rate)pulse rate)

45. Normal distributionNormal distribution
 generally continuous variables in the humangenerally continuous variables in the human
body such as height and weight has a definitebody such as height and weight has a definite
patternpattern
 It is a symmetrical, an inverted bell shapedIt is a symmetrical, an inverted bell shaped
curvecurve
 mean, mode and median are similarmean, mode and median are similar
 this type of distribution is calledthis type of distribution is called “normal“normal
distribution”distribution”

46. Normal distributionNormal distribution
VAR00001
9.08.07.06.05.04.03.02.01.0
12
10
8
6
4
2
0
Std. Dev = 2.02
Mean = 5.0
N = 50.00

47. Normal distributionNormal distribution
VAR00001
9.08.07.06.05.04.03.02.01.0
12
10
8
6
4
2
0
Std. Dev = 2.02
Mean = 5.0
N = 50.00
•symmetrical
•bell-shaped
•mean, mode,
median
similar
•also called a
Gaussian
curve

48. Normal distributionNormal distribution
mean
mode
median