Biostatistics Dr. Amjad El-Shanti MD, PMH,Dr PH University of Palestine 2016

What is statistics? Statistic is the science which deals with development and application of the most appropriate methods for: 1) Collection of data 2) organizing, summarizing of data 3) analyzing of data 4) interpretation of results of data 5) and presentation of information that can be stated numerically so that can be used in testing hypothesis or making decision. It is used in medicine, Public Health, sociology, economics, etc

Why is statistics? It is about understanding our world.

Why is statistics? It is important in: 1. Evaluation 2. Planning 3. Problem Solution 4. Quality Control 5. Researching 6. Developing 7. Life Management

Sources of data: A) From historical Records: (old census, annual vital statistical records, textbooks and journals, annual and monthly reports of different companies, hospital records, annual epidemiological and statistical reports of WHO) B) Survey Methods: 1. Comprehensive Survey: collection of data about every individual in the society (New census). 2. Sample Survey: collection of data about a certain portion of the population named the sample. It is the most commonly method for collection of data since it requires less time, effort and money. It should be: a) representative of the population b) unbiased C)Experiments: It may be carried out in the laboratory or in the field.

Statistical Procedures: Statistical procedures can be separated into two overlapping areas: 1- Descriptive Statistics: merely describe, organize or summarize data, they refer only to the actual data available. 2-Inferential Statistics: Involve making inference that go beyond the actual data. They typically involve inductive reasoning

Population and Sample: A population is the universe about which an investigator wishes to draw calculations; it need not consist of people. The point is that a population can range from relatively small set of numbers, which is easily collected to an infinity large set of numbers, which can never be completely collected.

Population and Sample: Unfortunality the populations in which we are interested are usually quite large. In this case we are forced to draw a sample of observations from a population and to use that sample to infer something about the characteristics of the population.

Kind of samples: There are four basic kinds of samples: 1- Simple Random Samples: It is the simplest sample. It is a sample drawn so that every element in the population has an equal probability of being included. 2- Stratified Random Sample: In this type of sampling, at first the population is divided into relatively internally homogenous strata or groups (males, females, refugees, Citizens, ………..).

Kind of samples: 3-Cluster samples: It maybe used when it is too expensive to draw a simple random or stratified random sample. The clusters are sampled randomly and all the members of cluster are sampled. 4-Systematic Samples: A systematic Sample involves choosing elements in a systematic way such as selecting every third patient admitted to a hospital.

Selection : Statistical procedures: There is an important distinction between descriptive and inferential statistics. In any study you must start your analysis by descriptive statistics to describe a set of data before you can use it to draw inferences (descriptive statistics like: frequencies, graphs, measures of central tendency, measures of variations, ……..).

Selection :Statistical procedures: when you come to inferential statistics, you need to make several additional distinctions to help you focus the choice of an appropriate statistical technique. The choice of an appropriate statistical technique depends on the type of variables in questions.

Type of data A. Constant data: These are observations which do not vary from time to time or from person to person. e.g. number of eyes, number of ears, number of fingers such data are not important statistically. B. Variables: These are observations which vary from time to time and from person to person e.g. age, weight, marital status

Type of variables: A variable is any measured characteristic or attribute that differs for different subjects. Variables can be quantitative or qualitative A) Quantitative variables. B) Qualitative variables

A) Quantitative Variables : These are variables which can be expressed in the form of quantities or numbers. They are classified into: 1. Quantitative Continuous Variables: this type has three characteristics: a) It may take integer or fractional values. b) It is obtained by measurement. c) It can take any value between two fixed limits namely, the upper and lower limits. e.g. Age, Weight, Height, vital capacity, distance, Blood Pressure, Blood Volume, Intelligence quotient..etc 2. Quantitative Discrete Variables : this type has two characteristics: a) It is obtained by enumerating or counting. b) It always take integer e.g. pulse rate, respiratory rate, number of cigarettes smoked per day, family size, number of players..etc

B ) Qualitative Variables: These are variables which can not be expressed in the form of quantities or numbers but take the form of qualities. 1. Qualitative Ordinal Variables: these are qualitative variables whose categories can be put in a definite order. e.g. educational level, Social level, general health condition, result of medical treatment. –Any quantitative variable can be transformed to qualitative ordinal variable. e.g. Blood pressure (hypotension, Normal, Hypertension) Blood Sugar (Hypoglycemia, Normal, Hyperglycemia) Smoking (Mild, Moderate, Heavy) Weight (Obese, Normal, Underweight) 2. Qualitative Nominal Variables: these are qualitative variables whose categories can not be arranged in a definite order. e.g. Blood group, sex, smoking (yes, no).

N.B. We are able to change the type of variable which we are dealing with: e.g. Smoking could be quantitative discrete (Number of cigarettes smoked per day). Also it can be transformed to qualitative ordinal (Heavy, Moderate, Mild) or transformed to qualitative nominal (yes or no)

Types of Data: 1.Constant 2.Variables Types of Variables: 1.Quantitative Variables 2.Qualitative variables Types of Quantitative Variables: 1.Continuous (integer or fractional ) obtained by measurement 2.Discrete (integer or fractional ) obtained by enumeration or counting Type of Qualitative Variables: 1. Ordinal (arranged in definite order) 2.Nominal (not arranged in definite order)

Data, Variable, Information Data: Recorded facts and figures about the sample elements. (variables, subjects) Variable: any measured characteristic or attribute that differs for different subjects. Information: the meaningful fact about the sample data after statistical processing. Data Information Statistical processing