This document discusses collecting and handling data in clinical practice and research. It explains that effective diagnosis requires a good quality patient history and physical examination. It also discusses the importance of variables and different types of data, including categorical and quantitative variables. Qualitative variables can be nominal, ordinal, or dichotomous. Quantitative variables can be discrete or continuous. The document stresses the importance of collecting data carefully and using appropriate statistical analysis to gain meaningful knowledge and information from the data.

1. COLLECTING AND HANDLING DATA
Dr. Zahraa Mohammed Mustafa
Public health and community medicine Lecturer
Faculty of Medicine, Beni Suef University

2. “I never guess. It is a capital
mistake to theorize before one has
data. Insensibly one begins to twist
facts and theories, instead of
theories to suit facts.
”
-- Sir Arthur Conan Doyle

3. DECISION-
MAKING IN
CLINICAL
PRACTICE

4. Much decision- making in clinical practice is based upon the interpretation of
history, examination, and investigations. Effective diagnosis requires a good
quality history (asking the right questions) and examination (being skilled in
eliciting clinical signs), and for this reason there is a big focus in undergraduate
and postgraduate clinical training on these skills. If a doctor ‘cuts corners’ with
their history taking, or has a sloppy examination technique, then key symptoms
and signs may be missed, leading to incorrect diagnosis and inappropriate
clinical management.

8. The science of
STATISTICS
deals with DATA

9. • Data comes from the Latin word “datum” which means “something
given”
• It refers to individual pieces of information
• It is measures without meaningful knowledge
• We use data to reach information and gain knowledge
DATA ‫المعطيات‬
/
‫البيانات‬

10. “A variable is any quantity that varies. Any attribute, phenomenon or
event that can have different values”
 notated by capital letters such as X and Y, is a characteristic of
interest for each person or thing in a population.
 Variables may be numerical or categorical.
 Numerical variables take on values with equal units such as weight
in pounds and time in hours.
 Categorical variables place the person or thing into a category.
Variable
‫المتغير‬

11. QUALITATIVE OR CATEGORICAL VARIABLES:
Where the answer to the question is a category from many legitimate mutually exclusive categories
appropriate to be an answer.
Example:
When asked about the Blood group, there are 4 possible appropriate mutually exclusive answers A, B, AB
and O and the individual will choose the one that applies to him.
(Mutually exclusive = cannot occur together, i.e., you cannot have more than one of these Blood groups).

12. Categorical variables may be one of three types:
The categories you
choose from have no
meaningful order.
Examples includes Blood
groups, residence,
nationality
There are only two categories
you choose from. Examples
include Sex (male-female),
Disease status (healthy-
disease), and Current
smoking status (smoker-
nonsmoker).
The categories you choose
from have a meaningful order.
Examples include Educational
level (illiterate, Primary,
Secondary and University),
Cancer stage (A1, A2, B1, B2,
C1 …etc.)

13. QUANTITATIVE VARIABLES:
Where the answer to the question is a number that may be one of two types
a) Discrete quantitative variables
b) Continuous quantitative variables

14. Integers without fractions
= Enumerated observation.
Examples include the number
of children per family, number of
molar teeth in the mouth,
number of beds in a hospital,
and RBCs count.
= Numbers with fractions
= Measurements.
Examples include
systolic blood pressure,
age, height, and fasting
blood sugar.
If there is a true zero (height, age and
weight), the variable is called
If the zero is relative (zero Degree
Centigrade or Zero IQ score)

17. Paper forms

18. Electronic data
capture

23. DR. ZAHRAA MOHAMMED MUSTAFA