Biostatics
General Description of the Course
This is a basic introductory course in fundamentals of biostatistics and medical statistics designed to meet the needs of medical graduates with emphasis on numerical problems on clinical practice and community health. It attempts to provide a broad perspective view of the application of statistical methods in biomedical and health problems including simple theories of sample surveys and probability and main focus on techniques of collecting reliable information of health problems and health services in the community and statistical presentation and interpretation of the findings of collected data. It will also try to introduce the computer skills in statistical analysis and data presentation.
Students will be able to
Specific and Behavioral Objectives:
Students will be able to
- define statistics and explain its scope, functions, limitations and usefulness
- state and explain the role of Biostatistics in the community medicine and health sciences;
- explain the significance and use of different branches of statistics in the investigation of community health and biomedical problems in public health and medical research;
- collect and record statistical information on medical and related fields from primary and secondary sources viz census, vital registration, ad-hoc surveys, population registers, hospitals records, medical journals and bulletins;
- process data including the determination of frequency distribution, presentation of statistical data diagrammatic and graphic forms as simple, multiple, subdivided bar diagrams, pie diagram, cartograms, pictogram, histogram frequency curve, frequency polygon, cumulative frequency curve, scattered diagram and give an elementary interpretation of the data including simple analyses of tables, charts and graphs;
- compute different rates and ratios of mortality, morbidity and fertility measures
- state and compute different measures of central tendencies — mean, mode, median and identify the requisites of an ideal average and its merits and demerits;
- state and compute different measures of location — quartiles, deciles and percentiles
- state and compute different measures of dispersions like range, standard deviation, variance, co-efficient of variation and identify the requisites of an ideal dispersions
- explain the concept of probability and chance in regard to biomedical applications such as diagnosis of cases, recovery from diseases ( efficacy of treatments): enunciate the simple additive and multiplicative laws of probability;
- define and state the properties ‘of Binomial, Poisson and Normal probability distributions and identify the parameters of these distribution and solve numerical examples;
- define concept of correlation and state the properties of correlation coefficients and compute the Pearson correlation coefficient and Spearman rank correlation coefficient and explain its meaning and solve numerical examples
- explain concept of regression analysis for two variables and compute the regression coefficients for simple linear regression equations and explain the cause and effect relationship between two variables;
- describe hypothesis and perform tests of significance in terms of defining hypothesis
- formulating a statistical hypothesis,
- differentiating null hypothesis from alternative hypothesis,
- defining Type I and Type II errors in testing of hypothesis/level of significance
- conducting statistical tests of significance, Z-tests and t-test for one sample and two
- samples, chi square — test for proportion, goodness fit and independence or association,
- test of correlation coefficient and draw inferences and solve numerical examples;
- explain sampling theory in terms of
- defining population, sample, sampling unit, sampling frame
- describing sample survey and census, and state the relative merits and demerits of
- sample versus census,
- criteria for selecting appropriate sampling design
- differentiating between probability and non-probabiiity sampling
- describing accidental sampling or convenience sampling, purposive sampling or judgmental
- sampling quota sampling and snow balling sampling as non- probabiiity sampling
- describing simple random sampling, stratified random sampling, systematic sampling,
- cluster sampling and multi-stage sample as probability sampling
- explaining the meaning of sampling errors and the sample size
- describing non-sampling errors that may occur in observational data
- describe research and its use in medicine
- types of research
- describing the steps necessary for conducting a research
- writing a research protocol
- framing research tools — questionnaire, checklist, guideline
- conducting a simple scientific research
- interpretation of results
- familiar with bioinformatics in terms of
- writing and presenting reports using MS Office
- retrieving subject matter from CD Rom, internet, websites
- applying computer skills in data processing and analysis : EPI- INFO and SPSS
