Biostatistics

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By: DR:NAJEEB MEMON Assistant Professor Faculty of Community Medicine & Public Health Sciences LUMHS, Jamshoro, Pakistan BIOSTATISTICS

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B I O S T A T I S T BIOSTATISTICS BIOSTATISTICS

STATISTICSIt is the science of collection, summarizing , analyzing , interpreting and presentation of data. BIOSTATISTICS-Branch of statistics-Deals with the application of statistical methodsto the information related to Health sciences. : 

STATISTICSIt is the science of collection, summarizing , analyzing , interpreting and presentation of data. BIOSTATISTICS-Branch of statistics-Deals with the application of statistical methodsto the information related to Health sciences.

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TYPES: 1, DESCRIPTIVE BIOSTATISTICS deal with the enumeration, organization And graphical representation of data.

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2. INFERENTIAL BIOSTATISTICS. are concerned with reaching conclusions from incomplete information, that is, generalizing from the specific sample.

VARIABLE :It is the characteristic of the person,object or phenomenon that can take on any value. : 

VARIABLE :It is the characteristic of the person,object or phenomenon that can take on any value.

DATA: It is the set of values of one or more variables recorded on one or more individuals.Primary Data:Census is an example of collecting primary data from populationSecondary Data:Already existing data about problem / populationexample from hospital record, to use the census data. : 

DATA: It is the set of values of one or more variables recorded on one or more individuals.Primary Data:Census is an example of collecting primary data from populationSecondary Data:Already existing data about problem / populationexample from hospital record, to use the census data.

TYPES OF DATA 1. QUALITATIVE DATA : It is the data which shows individual values falling into separate classes,these classes may have no numerical relationship with one another. Example: hair color , severity of disease. : 

TYPES OF DATA 1. QUALITATIVE DATA : It is the data which shows individual values falling into separate classes,these classes may have no numerical relationship with one another. Example: hair color , severity of disease.

QUALITATIVE DATA : 

QUALITATIVE DATA A. NOMINAL DATA OR CATEGORICAL It is the data that one can name, it is unordered, either-on type of data. Example: Sex (Male, Female) hair color. B. ORDINAL DATA ORDERED OR CATEGORICAL It is the data in which there is natural ordering of the categories. Example: severity of disease (Mild, Moderate, severe), occupational groups

2. QUANTITATIVE DATA : It is the data which shows some numerical value. Example:Family size , height , weight. : 

2. QUANTITATIVE DATA : It is the data which shows some numerical value. Example:Family size , height , weight.

QUANTITATIVE DATA : 

QUANTITATIVE DATA A. DISCRETE QUANTITATIVE DATA It is the quantitative data that takes only integral (whole number) of values. Example: Number of children in family, Number of deaths. B. CONTINUOUS QUANTITATIVE DATA It is the quantitative data that can be recorded on continuous scale i,e it can take decimal value, too. Example: Height, weight ,hemoglobin level.

Sources of data on community health Data may come from different sources: Surveillance systems (e.g., NIH) Planned surveys (Government, Universities, NGOs) Experiments (Pharmaceutical Companies)Health Organizations (Administrative Data sets)Private sector (Banks, Companies, etc) Government (All government agencies) : 

Sources of data on community health Data may come from different sources: Surveillance systems (e.g., NIH) Planned surveys (Government, Universities, NGOs) Experiments (Pharmaceutical Companies)Health Organizations (Administrative Data sets)Private sector (Banks, Companies, etc) Government (All government agencies) Census: (periodic count, after every 10 ys:) There are 2 principal methods for Enumeration of population. De facto: Which allocates persons according to their location at the time of enumeration. De jure; this assigns them according to their usual place of residence

Organizing Data : 

Organizing Data Frequency Table Frequency Histogram Relative Frequency Histogram Frequency polygon Relative Frequency polygon Bar chart Pie chart stem-and-leaf display Box Plot

PRESENTATION OF DATA : 

PRESENTATION OF DATA RATES,RATIOS AND PROPORTIONS. FREQUENCY DISTRIBUTION TABLES: - Simple Tables. - Complex Tables. - 2 x 2 Tables. CHARTS AND GRAPHS.

RATE : 

RATE A RATE IS DEFINED AS THE NUMBER OF EVENTS PER UNIT OF POP ; PARTICULAR TIME PERIOD. RATE= (A/A+B) x TO CALCULATE A RATE,WE NEED THE FOLLOWING: 1. NUMERATOR i.e. THE No: OF EVENTS OCCURINGIN A DEFINED PERIOD. 2. DENOMINATOR i.e. THE DEFINED POPULATION. 3. DEFINED PERIOD OF TIME 4. A MULTIPLIER.

A RATE MEASURES THE OCCURANCE OF SOME PARTICULAR EVENT IN A SPECIFIED POPULATION IN A DEFINED PERIOD OF TIME. THE VARIOUS CATEGORIES OF RATE ARE:1. CRUDE RATES2. SPECIFIED RATES3. STANDARDIZED RATES. : 

A RATE MEASURES THE OCCURANCE OF SOME PARTICULAR EVENT IN A SPECIFIED POPULATION IN A DEFINED PERIOD OF TIME. THE VARIOUS CATEGORIES OF RATE ARE:1. CRUDE RATES2. SPECIFIED RATES3. STANDARDIZED RATES.

RATIO : 

RATIO A RATIO IS THE EXPRESSION OF RELATIONSHIP BETWEEN TWO RANDOM QUANTITIES. IT IS OBTAINED BY DIVIDING ONE QUANTITY BY ANOTHER. EXAMPLE : Male : Female Ratio, Rural: Urban Ratio, Doctor : Patient Ratio, RBC : WBC Ratio.

PROPORTION : 

PROPORTION A PROPORTION IS THE NUMERICAL EXPRESSION OF A PART DIVIDED BY THE WHOLE. IN A PROPORTION, THE NUMERICAL IS THE PART OF THE DENOMINATOR. PROPORTION = A A + B WHEN A PROPORTION IS MULTIPLIED BY 100, IT IS CALLED A PERCENTAGE.

Organizing Data : 

Organizing Data Frequency Table Frequency Histogram Relative Frequency Histogram Frequency polygon Relative Frequency polygon Bar chart Pie chart stem-and-leaf display Box Plot

Presentation of statistical Data : 

Presentation of statistical Data 1.Tabulation Simple T Frequency distribution T 2. Charts & Diagrams 1. Bar charts a. simple bar chart b. Multiple bar chart c. component bar chart 3. Histogram Frequency polygon Line Diagram Scatter Diagram 3.Pie charts 4. Pictogram 5. statistical Maps

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Tabulation Are devices for presenting data May be simple or complex Some principles Table should be numbered (Tab:1 or 2 ) Title Headings of column & rows Data alphabetically or geographically Not too large Footnotes

Table 1Population of some cities of sind : 

Table 1Population of some cities of sind Source Census of sind 2004

Frequency distribution Table : 

Frequency distribution Table Data is first split up in to convenient group (class intervals) & no: of items ( frequency) are in adjacent columns E.g:- 2 3 5 8 2 3 5 7 8 9 7 4 2 4 6 7 3 2 4 6 7 9

Charts & Diagrams : 

Charts & Diagrams For simple statistical data Have a powerful impact on the imagination of the people Especially in newspapers & magazines. Diagrams are better retained in mind than statistical tables.

Bar charts : 

Bar charts Way of presenting a set of numbers by the length of a bar length of a bar is proportional to the magnitude to be represented. Easy to prepare Values to be compared

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A, simple bars Vertical or horizontal Are separated by spaces

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Multiple bar chart / compound bar chart 2 or more bars can be grouped together

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Component bar chart Divided in to 2 or more parts Each part representing a certain item & proportional to the magnitude of that particular item .

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Histogram Pictorial diagram of frequency distribution Class intervals given on horizontal axis & frequency along vertical axis

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Joining the mid points of histograms blocks Showing freq: distrib: of reading of fating sugar blood

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Line Diagram Show the trends of events with the passage of time 1970 80 2000 8 mil 6 4 2 Malaria cases in Africa

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Pie chart The areas of a circle are compared The area of each segment depends upon the angle Often % in the segments

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Pictogram Popular method of presenting data to the “man in the street” Small pictures or symbol are used to present the data.

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Dot Maps When refer to geographic or administrative areas.

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Shaded maps When refer to geographic or administrative areas, according to suitability. Presenting data of varying size Areas are shaded with different colors

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Scatter diagrams Shows relationship b/w 2 variables ( linear nature ) +ve correlation b/w stress & B.P

THE END : 

THE END GOOD BYE GOOD BYE G O O D B Y E

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