ELEMENTARY

Chapter 1 Introduction to Bio-StatisticsChapter 1

Introduction to Statistics

DATA:::DISCRETE OSERVATIONS OF ATTRIBUTES OR EVENTS THAT CARRY LITTLE MEANING WHEN CONSIDER ALONE

REDUCE,SUMMERISE ADJUSTING FOR VARIATIONINFORMATION

TRANSFORMATION OF INFORMATION THROUGH INTEGRATION AND PROCESSING WITH EXPERIENCE AND PERCEPTION BASED ON SOCIAL AND POLITICAL VALUEINTELLIGENCE

STATISTICS• S - Scientific method for

• T - tabulation

• A - analysis

• T - testing of hypothesis and

• I - inference

• S - study of

• T - time trend

• I - in

• C - community

• S - set up

Statistics

Two Meanings Specific numbers Method of analysis

Statistics

1-1 Overview

Specific numbernumerical measurement determined by a

set of data

Example: Twenty-three percent of people

Specific numbernumerical measurement determined by a

set of data

Example: Twenty-three percent of people

Statistics

Method of analysisa collection of methods for planning

experiments, obtaining data, and then

then organizing, summarizing, presenting,

analyzing, interpreting, and drawing

conclusions based on the data

Statistics

Biostatistics is the application of statistical methods to the problems ofbiology, including human biology, medicine and public health

Descriptive Biostatistics : It is the study of biostatistical procedures which deal with the collection, representation, calculation and processing. i.e., the summarization of data to make it more informative and comprehensible. It involves graphical and tabular to describe. Includes: Collecting Organizing Summerizing Presenting data

Inferential Biostatistics: It constitutes the procedures which serve to make generalizations or drawing conclusions on the basis of the studies of a sample. This is also known as sampling biostatistics. Includes: Making inferences Hypothesis testing Determining relationship Making predictions

• Statistical significance - whether the effect is due to by chance or realStatistical significance - whether the effect is due to by chance or real

Experimental →Intervention →Outcome Experimental →Intervention →Outcome

• Study Analysis → InferenceStudy Analysis → Inference Observational → Exposure →ObservationObservational → Exposure →Observation

IntroductionIntroduction

Population the complete collection of all

elements (scores, people, measurements, and so on) to be

studied. The collection is complete in the sense that it includes all subjects to be studied.

Definitions

Population the complete collection of all

elements (scores, people, measurements, and so on) to be studied. The collection is complete in the sense that it includes all subjects to be studied.

Definitions

Censusthe collection of data from every

element in a population

Sample

a subcollection of elements drawn from a population

Parameter

a numerical measurement describing some characteristic of a population

Definitions

Parameter

a numerical measurement describing some characteristic of a population

population

parameter

Definitions

Definitions

Statistic

a numerical measurement describing some characteristic of a sample

Definitions

Statistic

a numerical measurement describing some characteristic of a sample

sample

statistic

Definitions

Quantitative data

numbers representing counts or measurements

Definitions

Quantitative data

numbers representing counts or measurements

Qualitative (or categorical or

attribute) datacan be separated into different categories that are distinguished by some nonnumeric

characteristics

Definitions

Quantitative data

the incomes of college graduates

Definitions

Quantitative data

the incomes of college graduates

Qualitative (or categorical or

attribute) datathe genders (male/female) of college graduates

Discrete data result when the number of possible values is

either a finite number or a ‘countable’ number of possible values

0, 1, 2, 3, . . .

Definitions

Discrete data result when the number of possible values is

either a finite number or a ‘countable’ number of possible values

0, 1, 2, 3, . . .

Continuous (numerical) data result from infinitely many possible

values that correspond to some continuous scale that covers a range of values without gaps.

Definitions

2 3

Discrete

The number of eggs that hens lay; for

example, 3 eggs a day.

Definitions

Discrete The number of eggs that hens lay; for example, 3 eggs a day.

ContinuousThe amounts of milk that cows produce; for example,

2.343115 gallons a day.

Definitions

nominal level of measurement

characterized by data that consist of names,

labels, or categories only. The data cannot be

arranged in an ordering scheme (such as low to

high)

Example: survey responses yes, no, undecided

Definitions

ordinal level of measurement

involves data that may be arranged in some

order, but differences between data values

either cannot be determined or are meaningless

Example: Course grades A, B, C, D, or F

Definitions

interval level of measurement like the ordinal level, with the additional property that the difference

between any two data values is meaningful. The distance is defined. But ratio is not defined. Not include the natural zero starting point (where zero indicates that none of the quantity is present).

Example: temp in centigrade, intelligence score

20-250c =30-350c………00c is not mean the absence of heat…200c is not twice as hot as 100c

Definitions

ratio level of measurementthe interval level modified to include the natural zero starting point (where zero indicates that none of the quantity is present). For values at this level, differences and ratios are meaningful. The distance and ratio defined.

Example: length, weight…100 cm is 50cm more than 50 cm or twice as long as 50 cm

Definitions

Levels of Measurement Nominal - categories only

Ordinal - categories with some order

Interval - differences but no absolute zero. The distance is defined. But ratio is not defined.

Ratio – differences…….. absolute zero. The distance and ratio are defined.

qualitative

quantitative

Bio - Statistics

Descriptive

(Summarize & Describe data)

Inferential

(draw conclusion)

Qualitative Quantitative Estimation Hypothesis Testing

Confidence Interval

P Value

Proportion, Percentage Rate, Ratio

Central tendency

(mean median, mode)

Dispersion

Standard deviation standard error mean variance

Common Statistical Notations & Symbols

Summery value Sample statistics Popln. parameter

• Mean X µ• Standard Deviation S σ• Variance S2 σ2

• Proportion p P• Component of proportion q Q

Other Commonly Used Symbols:

Z : No of SD from Mean or standard normal deviate/ variate d.f or f. : degree of freedom P value : : Probability value

DATAREDUCE,SUMMERISE ADJUSTING FOR VARIATION INFORMATION

COMPONENT OF HEALTH INFORMATION 2.Demography3.Environmental Health Statistics4.Health Status :Mortality, Morbidity, Disability, Qol5.Health Resources6.Utilization Non Utilization Health Services

USES OF HEALTH INFORMATION:::•Measure health status local national and international comparison•Quantify health problems•Planning and effective management of health care need•Assessing health service accomplishing their objectives or not

: : : :SOURCES OF HEALTH INFORMATION::: : :

3.CENSUS

5.REgISTRATION OF VITAL EVENTS:: BIRTH 14 DAyS, DEATH 7 DAyS.

7.SRS

9.NOTIFICATION OF DISEASE

11.HOSPITAL RECORDS

13.DISEASE REgISTERS

15.EPIDEMIOLOgICAL SURVEILLANCE

17.ENVIRONMENTAL HEALTH INFORMATION

19.HEALTH MANPOwER STATISTICS

21.POPULATION SURVEyS

Health Management Information System (HMIS)Health Management Information System (HMIS)

BEFORE

Summary of data was calculated by hand and therefore prone to errors

Long delay to produce reports

A c o m p u t e r is e d in f o r m a t io n s y s t e m ( H M IS ) h a s b e e n in s t a l le d in n e a r ly a l l d i s t r ic t s in In d ia .

D a t a f r o m S C , P H C , C H C a n d H o s p i t a ls i s a v a i la b le f o r r e p o r t in g , s u p e r v is io n , p la n n in g a n d a n a ly s is

Computerized HMISComputerized HMIS

Data Collection at Data Collection at Health Facilities Health Facilities Form 6, 7 and 8)Form 6, 7 and 8)

District Computer District Computer UnitUnit

Block Computer UnitBlock Computer Unit

Decision Decision Support SystemSupport System

State DirectorateState Directorate

Health Managers / Health Managers / Program OfficersProgram Officers

Through Through FloppyFloppy

Through FTP, using phone Through FTP, using phone lineslines