Introduction to Biostatistics, Study Guides, Projects, Research of Sports Law

Download Introduction to Biostatistics and more Study Guides, Projects, Research Sports Law in PDF only on Docsity!

Introduction to Biostatistics

Department of Epidemiology and Biostaistics

Alemakef Wagnew M.(Bsc. in statistics and MPH)

September 25, 2019

introduction to Biostatistics

Course objective:

I (^) Definition and classification of Statistics I (^) Stages in statistical investigation I (^) Definition of Some Basic terms I (^) Applications, uses and limitations of Statistics I (^) Types of variables and measurement scales

Introduction

concern of Biostatistics

Applied Statistics: the application of statistical methods to solve real problems involving randomly generated data and the development of new statistical methodology motivated by real problems. Biostatistics is the branch of applied statistics directed toward applications in the health sciences and biology. Biostatistics: The tools of statistics are employed in many fields - business, education, psychology, agriculture, and economics, to mention only few. When the data being analyzed are derived from the public health data, biological sciences and medicine, we use the term biostatistics to distinguish this particular application of statistical tools and concepts.

Introduction

classification of Biostatistics

Descriptive statistics: A statistical method that is concerned with the collection, organization, summarization, and analysis of data from a sample of population. Inferential statistics A statistical method that is concerned with the drawing conclusions/infering about a particular population by selecting and measuring a random sample from the population.

descriptive statistics

 Some statistical summaries which are especially common in descriptive analyses are: I (^) Measures of central tendency I (^) Measures of dispersion I (^) Measures of association I (^) Cross-tabulation, contingency table I (^) Histogram I (^) Quantile, Q-Q plot I (^) Scatter plot I (^) Box plot

Inferential Statistics

 This branch of statistics deals with techniques of making conclusions about the population  Inferential statistics builds upon descriptive statistics  The inferences are drawn from particular properties of sample to particular properties of population  Inferential statistics are used to make generalizations from a sample to a population.  They encompasses a variety of procedures to ensure that the inferences are sound and rational, even though they may not always be correct

Statistical Methods

1.2 Stages in statistical investigation

There are five stages or steps in any statistical investigation

1. Collection of data I (^) The process of obtaining measurements or counts.
2. Organization of data I (^) Includes editing, classifying, and tabulating the data collected
3. Presentation of data I (^) overall view of what the data actually looks like I (^) facilitate further statistical analysis I (^) Can be done in the form of tables and graphs or diagrams
4. Analysis of data I (^) To dig out useful information for decision making I (^) It involves extracting relevant information from the data (like mean, median, mode, range, variance... )
5. Interpretation of data I (^) Concerned with drawing conclusions from the data collected and analyzed; and giving meaning to analysis results I (^) A difficult task and requires a high degree of skill and experience

1.3 Definition of Some basic terms

Population:is the complete set of possible measurements for which inferences are to be made.

Census:a complete enumeration of the population. But in most real problems it cannot be realized, hence we take sample.

Sample: A sample from a population is the set of measurements that are actually collected in the course of an investigation.

Parameter:Characteristic or measure obtained from a population.

Statistic:A statistic refers to a numerical quantity computed from sample data (e.g. the mean, the median, the maximum...).

Data:Refers to a collection of facts, values, observations, or measurements that the variables can assume.

1.3 Definitions of Some basic terms

Statistics: is a branch of mathematics dealing with data collection, organization, analysis, interpretation and presentation.

Sampling:The process or method of sample selection from the population.

Sample Size:The number of elements or observation to be included in the sample.

Variable:It is an item of interest that can take on many different numerical values.  Some examples of variables include: I (^) Diastolic blood pressure, I (^) heart rate, heights, I (^) The weights, I (^) Stage of bladder cancer patients,

Uses of Statistics

The main function of statistics is to enlarge our knowledge of complex phenomena. The following are some uses of statistics: i It presents facts in a definite and precise form. ii Data reduction. iii Measuring the magnitude of variations in data. iv Furnishes a technique of comparison. v Estimating unknown population characteristics. vi Testing and formulating of hypothesis. vii Studying the relationship between two or more variable. viii Forecasting future events

Limitations of statistics

As a science statistics has its own limitations. The following are some of the limitations: I Deals with only quantitative information.

II Deals with only aggregate of facts and not with individual data items.

III Statistical data are only approximately and not mathematical correct.

IV Statistics can be easily misused and therefore should be used be experts

Types of Variables 2

A. Depending on the characteristic of the measurement,

variable can be:

1. Qualitative(Categorical) variable I (^) A variable or characteristic which cannot be measured in quantitative form but can only be identified by name or categories, I (^) for instance place of birth, ethnic group, type of drug, stages of breast cancer (I, II, III, or IV), degree of pain (minimal, moderate, sever or unbearable). I (^) The categories should be clear cut, not overlapping, and cover all the possibilities. For example, sex (male or female), vital status (alive or dead), disease stage (depends on disease), ever smoked (yes or no).

Types of Variables 3

A. Depending on the characteristic of the measurement,

variable can be:

2. Quantitative(Numerical) variable: I (^) is one that can be measured and expressed numerically. Example: I (^) survival time I (^) systolic blood pressure I (^) number of children in a family I (^) height, age, body mass index.