1. INTRODUCTION AND DEFINITIONS
STATISTICS
INTRODUCTION AND DEFINITIONS

2. STATISTICS A field of study concerned with methods and procedures of:
Collection, Organization, Classification & Summarization of data.
(Descriptive Statistics)
Analysis, and Drawing of inferences about a body of data when only a part of data are observed. ( Analytic Statistics)

3. BIOSTATISTICS
When the data being analyzed are derived from biological and medical sciences, the term “ Biostatistics” is used.

4. ADVANTAGES 1. Carrying out a research
Statistical analysis should be considered in the planning phase of the study
2. Evaluating published articles
Statistical errors are common in clinical researches that may invalidate the conclusion.

5. ADVANTAGES 3. Ethical consideration
It is unethical to use erroneous statistics especially in scientific publications. Using harmful or ineffective treatment or avoidance of useful treatment can occur if the statistics is wrong.
4. Professional and personal satisfaction

6. PURPOSES 3. Sampling and generalization
1. Data reduction
By condensing data to manageable proportions thus facilitating interpretation
2. Evaluate role of chance
To see if the effect of a certain event is a real one
3. Sampling and generalization
What proportion of discharged patients required readmission? What are their characteristics? The answer required generalization of the sample's result.

7. APPLICATIONS Are the differences between groups significant?
Are these two measures related or associated?
Can one predict the value of one variable from knowledge of the values of other variables؟

8. Variables
A characteristic that takes on different values
things.eg.

9. Quantitative Variables Qualitative Variables
The variable
that can be measured in the usual sense
of measurement
as age , weight, height,…
It is the variable that can not be measured in the usual sense
but can be described or categorized ..Socio-economic

10. QUALITATIVE VARIABLE . eg.; - socio-economic groups.
ill person with medical diagnosis
In this case we count the number of individuals falling into each category as the socioeconomic status, diagnostic category,…

11. It is characterized by gaps or interruptions
Quantitative
Variables
DISCRETE VARIABLE
It is characterized by gaps or interruptions
CONTINOUS VARIABLE
It does not posses the gaps or interruption, It can assume any value within a
in the values
specified interval of values
that it can assume.
assumed by any variable
- The number of daily
admissions
-Weight,
-The number of decayed, missing or filled teeth
-Height,
-Mid-arm circumference
per child

12. VARIABLES SCALE 1. NOMINAL SCALE
It uses names, numbers or other symbols. Each measurement assigned to a limited number of unordered categories and fall in only one category.
eg. males & females
2. ORDINAL SCALE
to assigned Each measurement a
limited number of categories that are ranked in a graded order. ( 1st, 2nd, 3rd..) .

13. VARIABLES SCALE 3. INTERVAL SCALE
Each measurement is assigned to one of unlimited categories that are equally spaced with NO true zero point.
4. RATIO SCALE
Measurement begins at a true zero point and the scale has equal intervals

14. POPULATION POPULATION OF ENTITIES
Largest collection of entities that had common characteristics for which we have an interest at a particular time.
POPULATION OF VARIABLES
It is the largest collection of values of a random variable for which we have an interest at a particular time.

15. SAMPLE Sample of entities: Sample of variables:
It is part or subset of the population
Sample of entities:
which is a subset of population of entities
Sample of variables:
which is subset of population of variables

16. GROUPED DATA
To group a set of observations, we select a set of contiguous, non overlapping intervals, such that each value in the set of observation can be placed in one, and only one, of the interval, and no single observation should be missed.
The interval is called:
CLASS INTEVAL.

17. NUMBER OF CLASS INTERVALS
The number of class intervals :
Should not be too few because of the loss of important information. and
Not too many because of the loss of the needed summarization .
When there
is a priori classification
of that
particular observation we can follow that classification ( annual tabulations), but when there is no such classification we can follow the
Sturge's Rule

18. NUMBER OF CLASS INTERVALS
Sturge's Rule:
k= log n
k= number of class intervals
n= number of observations in the set
The result should not be regarded as final, modification is possible

19. WIDTH OF CLASS INTERVAL
The width of the class intervals should be the same, if possible.
R W = K
W= Width of the class interval
R= Range (largest value – smallest value) K= Number of class intervals

20. FREQUENCY DISTRIBUTION
It determines the number of observations falling into each class interval
Fasting blood glucoselevels
< 60
60-62
63-65
Frequency 10 23 33
66-68 22
69-71 34
72+ 33
155

21. Fasting blood glucoselevels
RELATIVE FREQUENCY
DISTRIBUTION
It determines the
Fasting blood glucoselevels
< 60
Frequency
Relative frequency %
6.45
14.84
proportion of observation in the particular class interval relative to 10 23
60-62
63-65 33
21.29
the
66-68 22
14.19
total observations
in the set.
69-71 34
21.94
72+ 33
21.29
155
100

22. CUMULATIVE FREQUENCY DISTRIBUTION < 60 60-62
Fasting blood glucose levels
< 60
60-62
Frequency
Cumulative frequency distribution 10 33
This is calculated by adding the number of observation in each class interval to the number of 10 23
63-65 33 66
observations in the
66-68 22 88
class interval above,
starting from the
69-71 34
122
second class interval
72+ 33
155
onward.
155

23. EXERCI E S The followings 76 86 70 85 66 are the weights 55 73 49 7956
(Kg) of 45 adult 62 65 77 78 71
male individuals
attending a 69 72 47
primary health 88 58 68 59
care centers: 90 99 64 41 63 54 52 48 83 80 S

24. 1 76 10 86 19 70 28 85 37 66 2 55 11 73 20 49 29 79 38 56 3 62 12 65 21 77 30 78 39 71 4 13 69 22 72 31 40 47 5 88 14 58 23 68 32 59 41 6 90 15 99 24 33 64 42 7 16 63 25 54 34 43 8 52 17 26 48 35 44 9 18 27 83 36 80 45

25. EXERCISE Construct a table showing: Frequency Relative frequency
Cumulative frequency
Cumulative relative frequency distribution.

26. Number of class intervals:
K= log n
= log45
= X 1.653
=6.4 =6
Width of class interval:
R 99-41
W= = = 9.7 = 10
K 6

27. CLASS INTERVAL (Kg)
40-49
FREQUENCY 4
RELATIVE FREQUENCY %
8.9
CUMULATIVE FREQUENCY
CUM.REL. FREQUENCY
50-59 7
15.6 11
24.5
60-69
24.4 22
48.9
70-79 13
28.9 35
77.8
80-89 42
93.4
90-99 3
6.7 45
100.1
Total

28. Thanks