Introduction to Statistics and Biostatistics and Definitions by C0SD5p


									Introduction to Statistics and
Biostatistics and Definitions
1. WA 900 D184 1991
   Daniel, Wayne W.
   Biostatistics: A Foundation for Analysis in the Health Sciences

2. WA 950 D272 2004
   Dawson, Beth Trapp, Robert G.
   Basic & Clinical Biostatistics
   Lange Medical Books/ McGrow-Hill NewYork 2004

3. WA 950 G545 2002
   Glantz, Stanton A.
   Primer of Biostatistics
   McGrow-Hill NewYork 2002

4. WA 950 A733 2002
   Armitage, P.
   Statistical Methods in Medical Research
   Blackwell Science Oxford 2002
This course teaches the basic skills needed to critique the
medical literature by providing a fundamental
understanding of biostatistics.

Course Description
The primary purpose of this course is to teach you basic
skills to critique the medical literature and need for
statistical consultancy when designing, conducting and
reporting a research. As future physicians you have an
obligation to remain current in your field of practice and to
treat patients according to generally accepted standards
of care. To do this well you will need to read those
journals that are considered the most important sources
of new information impacting on your field of medicine.
For example, internal medicine physicians generally read
the New England Journal of Medicine (NEJM) which is
published by the Massachusetts Medical Society.
Perhaps the most influential medical journal, its articles
are widely reviewed by the media. Most surgeons read
the Annals of Surgery. In short, each field of medicine
has its own specialty journals.
As your patients hear media reports about the latest
research results, they will most certainly ask for your
Should adult patients take antioxidants to help
prevent heart disease?
Do the potential benefits of hormonal replacement
in postmenopausal women outweigh the potential
Statistics is the art and science of data. It deals
       •Planning Research
       •Collecting Data
       •Describing Data
       •Summarizing- Presenting Data
       •Analyzing Data
       •Interpreting Results
       • Reaching decisions or
        discovering new knowledge
Biostatisitcs is the application of statistical
methods to health sciences.

Basic tasks of statistics
•To describe

•To draw inferences concerning the underlying
Descriptive statistics:
These are devices for organizing data and may be:
(i) tabular (ii) graphical (iii) numerical
Inferential statistics:
Much of the statistical investigations are carried
on samples. Conclusions about the population are
thus drawn from the observations carried out on
these samples. Statistical methods which are used
for making inferences about the population are
based on probability theory and are called
inferential statistics.
Data : Set of values of one or more variables recorded
on one or more observational units.
Observation (case): Individual source of data.
Variable: This is a quantity which varies such that it
may take any one of a specified set of values. It may
be measurable or non-measurable.
Population: A collection, or set, of individuals,
objects, or measurements whose properties are to be
Sample: A subset of the population, selected in such a
way that it is representative of the larger population.
Parameter : A summary value which in some
way characterizes the nature of the population in
the variable under study.
Statistic : A summary value calculated from a
sample of observation.

Sources of data
1. Routinely kept records
2. Published data sources
3. Data on electronic media
4. Surveys and Experimental research
5. Census
6. Generated or artificial data
                Types of Data

1. Qualitative Data
   Results from a variable that asks for a quality
   type of description of the subject.

2. Quantitative Data
   Results from obtaining quantities-counts or
                        Scale of measurement
                                              (Categorical) Data

                          Nominal                                        Ordinal

                                                                   Severity of disease
              Two                     More than two                Income level
           categories                  categories

                                        Marital Status
 Binary                 Dichotomous

Disease – or +          Gender(M;F)
             Quantitative Data

 Discrete                             Continuous

# of birth
# of death
                           Interval                 Ratio

                           Temperature             Age
                           IQ                      Weight
  Why should medical students learn biostatistics?
1. Medicine is becoming increasingly QUANTITATIVE.
   • The aim is to improve the Health Status of the
   • We have to clarify the relationships between certain
     factors and diseases.
   • Enumarate the occurances of diseases
   • Explain the etiology of diseases (which factors
     cause which diseases)
   • Predict the number of disease occurence
   • Read, understand and criticize the medical
Why should medical students learn biostatistics?

 2. The planning, conduct and interpretation of
    much of medical research are becoming
    increasingly reliant on statistical methods.
  How many patients must be treated?
  How do we have to allocate the subjects to treatments?
  What are the other factors which may influence the
  response variable?
  Under which conditions must the study be conducted?
  Is matching necessary?
  Is blinding (single blinding or double blinding) necessary?
  Is there a need for a control group?
  Shoud the placebo effect be considered?
  Which experimental design technique is more appropriate?
Example 1

 Distribution of Women with a Diagnosis of    Distribution of Healthy Women Among
   Tromboembolism Among Blood Groups                       Blood Groups
Blood Group    Frequency           %         Blood Group   Frequency       %
    A              32             58.2           A            75          51.7
    AB             4               7.3           AB           8            5.5
    B              8              14.5           B            19          13.1
    O              11             20.0           O            43          29.7
   Total           55             100.0         Total        145          100.0
Example 2
    In a follow up study 609 males between ages of 40 to
    76 free of coronary heart disease (CHD) were
    examined from 1990 to 1999. At the end of the period
    71 new cases of CHD were identified. The primary
    goal of this study was to evaluate the association
    between obesity and the incidence of CHD. The
    results were as follows:
                              Risk Ratio= R
             Obesity              27 / 122
  Disease   Yes No     Total   R=
                                  44 / 487
  CHD+       27 44      71
  CHD-       95 443    538
                               The risk of CHD is 2.45
  Total     122 487    609
                               times higher among obese

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