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Introduction to biostatistics

Introduction to biostatistics. Marek Majdan. Definitions.

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Introduction to biostatistics

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  1. Introduction to biostatistics Marek Majdan Training in essential biostatistics for Public Health Professionals in BiH, Marek Majdan, PhD; marekmajdan@gmail.com

  2. Definitions • A statistic is a quantity that is calculated from a sample of data. It is used to give information about unknown values in the corresponding population. For example, the average of the data in a sample is used to give information about the overall average in the population from which that sample was drawn. (Easton, VJ, McColl, JH, Statistcs Glossary, http://www.stats.gla.ac.uk/steps/glossary/basic_definitions.html#stat) Training in essential biostatistics for Public Health Professionals in BiH, Marek Majdan, PhD; marekmajdan@gmail.com

  3. Definitions A population is any entire collection of people, animals, plants or things from which we may collect data. It is the entire group we are interested in, which we wish to describe or draw conclusions about. In order to make any generalizations about a population, a sample, that is meant to be representative of the population, is often studied. For each population there are many possible samples. A sample statistic gives information about a corresponding population parameter. For example, the sample mean for a set of data would give information about the overall population mean. It is important that the investigator carefully and completely defines the population before collecting the sample, including a description of the members to be included. ExampleThe population for a study of infant health might be all children born in the UK in the 1980's. The sample might be all babies born on 7th May in any of the years. (Easton, VJ, McColl, JH, Statistcs Glossary, http://www.stats.gla.ac.uk/steps/glossary/basic_definitions.html#stat) Training in essential biostatistics for Public Health Professionals in BiH, Marek Majdan, PhD; marekmajdan@gmail.com

  4. Definitions A sample is a group of units selected from a larger group (the population). By studying the sample it is hoped to draw valid conclusions about the larger group. A sample is generally selected for study because the population is too large to study in its entirety. The sample should be representative of the general population. This is often best achieved by random sampling. Also, before collecting the sample, it is important that the researcher carefully and completely defines the population, including a description of the members to be included. ExampleThe population for a study of infant health might be all children born in the UK in the 1980's. The sample might be all babies born on 7th May in any of the years. (Easton, VJ, McColl, JH, Statistcs Glossary, http://www.stats.gla.ac.uk/steps/glossary/basic_definitions.html#stat) Training in essential biostatistics for Public Health Professionals in BiH, Marek Majdan, PhD; marekmajdan@gmail.com

  5. Definitions • Statistical Inference makes use of information from a sample to draw conclusions (inferences) about the population from which the sample was taken. (Easton, VJ, McColl, JH, Statistcs Glossary, ttp://www.stats.gla.ac.uk/steps/glossary/basic_definitions.html#stat) Training in essential biostatistics for Public Health Professionals in BiH, Marek Majdan, PhD; marekmajdan@gmail.com

  6. Definitions • Biostatisticsis the application of statistics to a wide range of topics in biology. The science of biostatistics encompasses: • the design of biological experiments, especially in medicine and agriculture; • the collection, summarization, and analysis of data from those experiments; • and the interpretation of, and inference from, the results. (Easton, VJ, McColl, JH, Statistcs Glossary, http://www.stats.gla.ac.uk/steps/glossary/basic_definitions.html#stat) Training in essential biostatistics for Public Health Professionals in BiH, Marek Majdan, PhD; marekmajdan@gmail.com

  7. Definitions An experiment is any process or study which results in the collection of data, the outcome of which is unknown. In statistics, the term is usually restricted to situations in which the researcher has control over some of the conditions under which the experiment takes place. ExampleBefore introducing a new drug treatment to reduce high blood pressure, the manufacturer carries out an experiment to compare the effectiveness of the new drug with that of one currently prescribed. Newly diagnosed subjects are recruited from a group of local general practices. Half of them are chosen at random to receive the new drug, the remainder receiving the present one. So, the researcher has control over the type of subject recruited and the way in which they are allocated to treatment. (Easton, VJ, McColl, JH, Statistcs Glossary, http://www.stats.gla.ac.uk/steps/glossary/basic_definitions.html#stat) Training in essential biostatistics for Public Health Professionals in BiH, Marek Majdan, PhD; marekmajdan@gmail.com

  8. Definitions • Epidemiologyis the study of the distribution and size of disease problems in human populations, in particular to identify aetiological factors in the pathogenesis of disease and to provide the data essential for the management, evaluation and planning of services for the prevention, control and treatment of disease. Everitt, B: Medical statistics from A to Z. Cambridge Uni. Press, 2006 Training in essential biostatistics for Public Health Professionals in BiH, Marek Majdan, PhD; marekmajdan@gmail.com

  9. Epidemiological studies Experimental (intervention studies) Studies preventions and treatments for diseases; investigator actively manipulates which groups receive the agent under study. Observational Studies causes, preventions, and treatments for diseases; investigator passively observes as nature takes its course. Cohort - Typically examines multiple health effects of an exposure; subjects are defined according to their exposure levels and followed for disease occurrence. Case–control-Typically examines multiple exposures in relation to a disease; subjects are defined as cases and controls, and exposure histories are compared. Cross-sectional Examines relationship between exposure and disease prevalence in a defined population at a single point in time. Ecological Examines relationship between exposure and disease with population-level rather than individual-level data. Ann Aschengrau , George R. Seage: Essentials of Epidemiology in Public Health. Jones & Bartlett Publishers 2007. Training in essential biostatistics for Public Health Professionals in BiH, Marek Majdan, PhD; marekmajdan@gmail.com

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