Medical Statistics.pptx

Definition of Statistics
 Statistics is a branch of mathematics dealing with data
collection, organization, analysis, interpretation and
presentation of data.
Definition of Medical statistics
 Medical statistics deals with applications
of statistics to medicine and the health sciences,
including epidemiology, public health, forensic
medicine, and clinical research.
 ( In simple - statistics is applied in the field of medicine
is called as medical statistics)

 Definition of Biostatistics
Biostatistics is a branch of science in
which application of different statistical
methods like, collection, classification,
presentation, analysis, interpretation of
biological variations.
 (In simple - when knowledge of statistics is
applied to biological variables is called as
Biostatistics)

Three reasons:
 Basic requirement of medical research.
 To Update your medical knowledge.
 For Data management and treatment.
 To describe research.

 Descriptive information for any population
 To decide the relative importance of
problems
 Prove association between variables
 Prove relation between risk and disease
 Compare new phenomena with old ones
 Compare results of different researches.
 Evaluate health programs & services

Population
 In statistics, population refers to the total set of
observations, items or units that can be taken
for study.
 From this sample is drawn for the research.
For example, if we are studying the weight of
adult women, the population is the set of
weights of all the women in the world.

Sample
 A sample refers to a smaller, manageable
version or unit of a larger group from the
population.
 It is a subset containing the characteristics of
a larger population.
 Samples are used in statistical testing when
population sizes are too large for the test to
include all possible members or observations.
 A sample should represent the population as
a whole and not reflect any bias toward a
specific attribute.

Data
 Data are individual pieces of factual
information recorded and used for the
purpose of analysis.
 Set of information collected during the process
of any study or research.
 It is the raw information from
which statistics are created.

Variable
 A variable is a characteristic of a unit being
observed that may assume more than one of
a set of values to which a numerical measure
or a category from a classification can be
assigned
(e.g. age, weight, etc., “disease”, etc.
 A variable is any characteristics, number, or
quantity that can be measured or counted.
 A variable may also be called a data item.
 Age, sex, business income and expenses,
country of birth, capital expenditure, class
grades, eye colour and vehicle type are
examples of variables.

Normal Distribution
 The normal distribution is a probability function
that describes how the values of a variable are
distributed.
 It is a symmetric distribution where most of the
observations cluster around the central peak and
the probabilities for values further away from
the mean taper off equally in both directions.

 Data Collection
The collection, organization, and presentation
of data are basic background material for
learning descriptive and inferential statistics
and their applications Method of Collecting
Data On the basis of the source of collection
data may be classified as,
 Primary data
 Secondary data

 Data which are originally collected for the first
time by investigator himself for the purpose of
the study are called primary data.
There are several methods for collecting primary
data. Some of them are:
 Direct personal investigation
 Indirect investigations
 Through correspondent
 By mailed questionnaire
 Through schedules

 When we use the data, which have already been
collected by others, the data are called secondary data.
This data is said to be primary for the agency which
collects it first, and it becomes secondary for all the
other users.
Method of Collecting Secondary Data are,
 Published reports of newspapers, RBI and periodicals
 Publication from trade associations
 Financial data reported in annual reports
 Information from official publications
 Publication of international bodies such as UNO, World
Bank etc.
 Internal reports of the government departments
 Records maintained by the institutions
 Research reports prepared by students in the
universities

Categorical Data
 Categorical data represent characteristics such
as a person’s gender, marital status,
hometown, or the types of movies they like.
 Categorical data can take on numerical values
(such as “1” indicating male and “2” indicating
female),
 but those numbers don’t have mathematical
meaning. You couldn’t add them together,
 for example. (Other names for categorical data
are qualitative data, or Yes/No data.)

 These data have meaning as a measurement,
such as a person’s height, weight, IQ, or blood
pressure; or they’re a count,
 such as the number of stock shares a person
owns, how many teeth a dog has, or how many
pages you can read of your favorite book before
you fall asleep. (Statisticians also call numerical
data quantitative data.)
 Numerical data can be divided into two groups
 Discrete (Counted Items such as- number of children,
defects per hour etc.)
 Continuous (Measured Characteristics such as- weight,
voltage etc)

 Data collected in the form of schedules and
questionnaires are not self explanatory. These
are in the form of raw data. In order to make
them meaningful, these are to be made
presentable.

 This refers to the organization of data into
tables, graphs or charts, so that logical and
statistical conclusions can be derived from
the collected measurements.
Data may be presented in(3 Methods)
1. Textual
2. Tabular
3. Diagrammatic
4. Graphical

 In the textual presentation the data gathered
are presented in paragraph form.
 Data are written and read.
 It is a combination of texts and figures.
Ex-Of the 150 sample interviewed, the following
complaints were noted: 27 for lack of books in
the library, 25 for a dirty playground, 20 for
lack of laboratory equipment, 17 for a not well
maintained university buildings

 It is one of the method of presenting data
using the statistical table.
 A systematic organization of data in columns
and rows.
 Depending upon the number of rows and
columns and its divisions the tables are
divided in to two types
1. Simple tables
2. Complex Tables / Manifold tables

 Table heading –consists of table number and
title
 Stubs – classifications or categories which are
found at the left side of the body of the table
 Box head – the top of the column
 Body – main part of the table
 Footnotes – any statement or note inserted
 Source Note – source of the statistics

KINDS OF GRAPHS OR DIAGRAMS
1. BAR GRAPH – used to show relationships/
comparison between groups
2. PIE OR CIRCLE GRAPH- shows percentages
effectively
3. LINE GRAPH – most useful in displaying data
that changes continuously over time.
4. PICTOGRAPH – or pictogram. It uses small
identical or figures of objects called isotopes
in making comparisons .Each picture
represents a definite quantity.

Average
 An average is a single number taken as
representative of a list of numbers.
 Different concepts of average are used in
different contexts.
 Often "average" refers to the arithmetic mean,
the sum of the numbers divided by how many
numbers are being averaged.
 In statistics, mean, median, and mode are all
known as measures of central tendency, and in
colloquial usage any of these might be called
an average value.

Percentile
 A percentile (or a centile) is a measure used
in statistics indicating the value below which
a given percentage of observations in a group
of observations falls.
 For example, the 20th percentile is the value
(or score) below which 20% of the
observations may be found.

 Range
 Standard Deviation
 Standard Error

 The Range is the difference between the
lowest and highest values. (Measure of
spread)
 Easiest measure of variability to calculate
 Simply the difference between the highest
and lowest scores
SET OF SCORES:
7, 2, 7, 6, 5, 6, 2
RANGE = HIGHEST SCORE - LOWESTSCORE
R = 7 - 2 = 5

 Indicates the amount that all scores differ or
deviate from the mean
 When the values in a dataset are grouped
closer together, you have a smaller standard
deviation. On the other hand, when the values
are spread out more, the standard deviation
is larger because the standard distance is
greater.

 The standard error is a measure of the
variability of a statistic. It is an estimate of
the standard deviation of a sampling
distribution. The standard error depends on
three factors:
 N: The number of observations in the
population.
 n: The number of observations in the sample.
 The way that the random sample is chosen.

 Probability is the measure of the relative chance
of occurrence of an event will occur in a
Random Experiment.
 For example, the probability of PROBABILITY
having a disease is the disease prevalence.
 The value of probability ranges between 0 to 1
 0 indicates impossibility and 1 indicates
certainty.

 Additional law of probability
 Multiple law of probability
 Binomial law of probability

 Test of significance is a formal procedure for
comparing observed data with a claim (also
called a hypothesis) whose truth we want to
assess.
 Test of significance is used to test a claim
about an unknown population parameter.
 A significance test uses data to evaluate a
hypothesis by comparing sample point
estimates of parameters to values predicted
by the hypothesis.

 The methods of inference used to support or
reject claims based on sample data are
known as tests of significance.

 in statistical hypothesis testing, the p-
value or probability value is the probability of
obtaining test results at least as extreme as
the results actually observed during the test,
assuming that the null hypothesis is correct.

 The p-value is used as an alternative to
rejection points to provide the smallest level
of significance at which the null
hypothesis would be rejected. A smaller p-
value means that there is stronger evidence
in favor of the alternative hypothesis.

AYUSH research portal
 Department of AYUSH has launched the online
AYUSH Research portal on 18-04-2011 to serve
the scientific community for disseminating the
research findings in the domain of Ayurveda, Yoga
& Naturopathy, Unani, Siddha, Sowa Rigpa and
Homoeopathy researchers and allied faculties.
Main aim of this portal is to show-case the
research findings in an organized fashion and to
prevent duplication of work; to encourage
interdisciplinary research and generate evidence
for wide acceptance of these systems worldwide.

DHARA
 DHARA is the acronym for Digital Helpline for
Ayurveda Research Articles. It is the first
comprehensive online indexing service
exclusively for research articles published in
the field of Ayurveda. DHARA is accessible
online at www.dharaonline.org.

PubMed
 PubMed is a free search engine accessing
primarily the MEDLINE database of references
and abstracts on life sciences and biomedical
topics. The United States National Library of
Medicine (NLM) at the National Institutes of
Health maintain the database as part of
the Entrez system of information retrieval

It provides access to:
 older references from the print version of Index
Medicus, back to 1951 and earlier
 references to some journals before they were
indexed in Index Medicus and MEDLINE, for
instance Science, BMJ, and Annals of Surgery
 very recent entries to records for an article before it
is indexed with Medical Subject Headings (MeSH)
and added to MEDLINE
 a collection of books available full-text and other
subsets of NLM records
 PMC citations
 NCBI Bookshelf

Medical Statistics.pptx

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Medical Statistics.pptx