Medical Statistics.pptx
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Statistics is the study of collecting, organizing, summarizing, and interpreting data. Medical statistics applies statistical methods to medical data and research. Biostatistics specifically applies statistical methods to biological data. Statistics is essential for medical research, updating medical knowledge, data management, describing research findings, and evaluating health programs. It allows comparison of populations, risks, treatments, and more.
Medical Statistics.pptx
- 1. By. Dr S.B Chougala
- 2. Definition of Statistics Statistics is a branch of mathematics dealing with data collection, organization, analysis, interpretation and presentation of data. Definition of Medical statistics Medical statistics deals with applications of statistics to medicine and the health sciences, including epidemiology, public health, forensic medicine, and clinical research. ( In simple - statistics is applied in the field of medicine is called as medical statistics)
- 3. Definition of Biostatistics Biostatistics is a branch of science in which application of different statistical methods like, collection, classification, presentation, analysis, interpretation of biological variations. (In simple - when knowledge of statistics is applied to biological variables is called as Biostatistics)
- 4. Three reasons: Basic requirement of medical research. To Update your medical knowledge. For Data management and treatment. To describe research.
- 5. Descriptive information for any population To decide the relative importance of problems Prove association between variables Prove relation between risk and disease Compare new phenomena with old ones Compare results of different researches. Evaluate health programs & services
- 6. Population In statistics, population refers to the total set of observations, items or units that can be taken for study. From this sample is drawn for the research. For example, if we are studying the weight of adult women, the population is the set of weights of all the women in the world.
- 7. Sample A sample refers to a smaller, manageable version or unit of a larger group from the population. It is a subset containing the characteristics of a larger population. Samples are used in statistical testing when population sizes are too large for the test to include all possible members or observations. A sample should represent the population as a whole and not reflect any bias toward a specific attribute.
- 8. Data Data are individual pieces of factual information recorded and used for the purpose of analysis. Set of information collected during the process of any study or research. It is the raw information from which statistics are created.
- 9. Variable A variable is a characteristic of a unit being observed that may assume more than one of a set of values to which a numerical measure or a category from a classification can be assigned (e.g. age, weight, etc., “disease”, etc. A variable is any characteristics, number, or quantity that can be measured or counted. A variable may also be called a data item. Age, sex, business income and expenses, country of birth, capital expenditure, class grades, eye colour and vehicle type are examples of variables.
- 10. Normal Distribution The normal distribution is a probability function that describes how the values of a variable are distributed. It is a symmetric distribution where most of the observations cluster around the central peak and the probabilities for values further away from the mean taper off equally in both directions.
- 11. Data Collection The collection, organization, and presentation of data are basic background material for learning descriptive and inferential statistics and their applications Method of Collecting Data On the basis of the source of collection data may be classified as, Primary data Secondary data
- 12. Data which are originally collected for the first time by investigator himself for the purpose of the study are called primary data. There are several methods for collecting primary data. Some of them are: Direct personal investigation Indirect investigations Through correspondent By mailed questionnaire Through schedules
- 13. When we use the data, which have already been collected by others, the data are called secondary data. This data is said to be primary for the agency which collects it first, and it becomes secondary for all the other users. Method of Collecting Secondary Data are, Published reports of newspapers, RBI and periodicals Publication from trade associations Financial data reported in annual reports Information from official publications Publication of international bodies such as UNO, World Bank etc. Internal reports of the government departments Records maintained by the institutions Research reports prepared by students in the universities
- 14. Categorical Data Categorical data represent characteristics such as a person’s gender, marital status, hometown, or the types of movies they like. Categorical data can take on numerical values (such as “1” indicating male and “2” indicating female), but those numbers don’t have mathematical meaning. You couldn’t add them together, for example. (Other names for categorical data are qualitative data, or Yes/No data.)
- 15. These data have meaning as a measurement, such as a person’s height, weight, IQ, or blood pressure; or they’re a count, such as the number of stock shares a person owns, how many teeth a dog has, or how many pages you can read of your favorite book before you fall asleep. (Statisticians also call numerical data quantitative data.) Numerical data can be divided into two groups Discrete (Counted Items such as- number of children, defects per hour etc.) Continuous (Measured Characteristics such as- weight, voltage etc)
- 16. Data collected in the form of schedules and questionnaires are not self explanatory. These are in the form of raw data. In order to make them meaningful, these are to be made presentable.
- 17. This refers to the organization of data into tables, graphs or charts, so that logical and statistical conclusions can be derived from the collected measurements. Data may be presented in(3 Methods) 1. Textual 2. Tabular 3. Diagrammatic 4. Graphical
- 18. In the textual presentation the data gathered are presented in paragraph form. Data are written and read. It is a combination of texts and figures. Ex-Of the 150 sample interviewed, the following complaints were noted: 27 for lack of books in the library, 25 for a dirty playground, 20 for lack of laboratory equipment, 17 for a not well maintained university buildings
- 19. It is one of the method of presenting data using the statistical table. A systematic organization of data in columns and rows. Depending upon the number of rows and columns and its divisions the tables are divided in to two types 1. Simple tables 2. Complex Tables / Manifold tables
- 20. Table heading –consists of table number and title Stubs – classifications or categories which are found at the left side of the body of the table Box head – the top of the column Body – main part of the table Footnotes – any statement or note inserted Source Note – source of the statistics
- 23. KINDS OF GRAPHS OR DIAGRAMS 1. BAR GRAPH – used to show relationships/ comparison between groups 2. PIE OR CIRCLE GRAPH- shows percentages effectively 3. LINE GRAPH – most useful in displaying data that changes continuously over time. 4. PICTOGRAPH – or pictogram. It uses small identical or figures of objects called isotopes in making comparisons .Each picture represents a definite quantity.
- 32. Average An average is a single number taken as representative of a list of numbers. Different concepts of average are used in different contexts. Often "average" refers to the arithmetic mean, the sum of the numbers divided by how many numbers are being averaged. In statistics, mean, median, and mode are all known as measures of central tendency, and in colloquial usage any of these might be called an average value.
- 33. Percentile A percentile (or a centile) is a measure used in statistics indicating the value below which a given percentage of observations in a group of observations falls. For example, the 20th percentile is the value (or score) below which 20% of the observations may be found.
- 34. Range Standard Deviation Standard Error
- 35. The Range is the difference between the lowest and highest values. (Measure of spread) Easiest measure of variability to calculate Simply the difference between the highest and lowest scores SET OF SCORES: 7, 2, 7, 6, 5, 6, 2 RANGE = HIGHEST SCORE - LOWESTSCORE R = 7 - 2 = 5
- 36. Indicates the amount that all scores differ or deviate from the mean When the values in a dataset are grouped closer together, you have a smaller standard deviation. On the other hand, when the values are spread out more, the standard deviation is larger because the standard distance is greater.
- 37. The standard error is a measure of the variability of a statistic. It is an estimate of the standard deviation of a sampling distribution. The standard error depends on three factors: N: The number of observations in the population. n: The number of observations in the sample. The way that the random sample is chosen.
- 38. Probability is the measure of the relative chance of occurrence of an event will occur in a Random Experiment. For example, the probability of PROBABILITY having a disease is the disease prevalence. The value of probability ranges between 0 to 1 0 indicates impossibility and 1 indicates certainty.
- 39. Additional law of probability Multiple law of probability Binomial law of probability
- 40. Test of significance is a formal procedure for comparing observed data with a claim (also called a hypothesis) whose truth we want to assess. Test of significance is used to test a claim about an unknown population parameter. A significance test uses data to evaluate a hypothesis by comparing sample point estimates of parameters to values predicted by the hypothesis.
- 41. The methods of inference used to support or reject claims based on sample data are known as tests of significance.
- 42. in statistical hypothesis testing, the p- value or probability value is the probability of obtaining test results at least as extreme as the results actually observed during the test, assuming that the null hypothesis is correct.
- 43. The p-value is used as an alternative to rejection points to provide the smallest level of significance at which the null hypothesis would be rejected. A smaller p- value means that there is stronger evidence in favor of the alternative hypothesis.
- 48. AYUSH research portal Department of AYUSH has launched the online AYUSH Research portal on 18-04-2011 to serve the scientific community for disseminating the research findings in the domain of Ayurveda, Yoga & Naturopathy, Unani, Siddha, Sowa Rigpa and Homoeopathy researchers and allied faculties. Main aim of this portal is to show-case the research findings in an organized fashion and to prevent duplication of work; to encourage interdisciplinary research and generate evidence for wide acceptance of these systems worldwide.
- 49. DHARA DHARA is the acronym for Digital Helpline for Ayurveda Research Articles. It is the first comprehensive online indexing service exclusively for research articles published in the field of Ayurveda. DHARA is accessible online at www.dharaonline.org.
- 50. PubMed PubMed is a free search engine accessing primarily the MEDLINE database of references and abstracts on life sciences and biomedical topics. The United States National Library of Medicine (NLM) at the National Institutes of Health maintain the database as part of the Entrez system of information retrieval
- 51. It provides access to: older references from the print version of Index Medicus, back to 1951 and earlier references to some journals before they were indexed in Index Medicus and MEDLINE, for instance Science, BMJ, and Annals of Surgery very recent entries to records for an article before it is indexed with Medical Subject Headings (MeSH) and added to MEDLINE a collection of books available full-text and other subsets of NLM records PMC citations NCBI Bookshelf