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Medical Statistics & Demography Made Easy by Devashish Sharma

By Devashish Sharma

The e-book explains the themes of important statistics, statistical equipment in epidemiology, and healthiness information
The ebook offers solved examples on quite a few scientific difficulties essential to comprehend the computational aspect in learn works. It emphasizes common options and diverse statistical equipment and formulae important in computation. It comprises approximately 50 unsolved questions and approximately three hundred MCQs. An accompanying CD-ROM illustrates a bunch of concepts in clinical facts.

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X+a ~ N (μ + a, σ2) STANDARD NORMAL VARIATE If x ~ N (μ, σ2), then is a standard normal variate with mean 0 and variance 1. 2 The above curve of normal distribution showing the scales of the original variable which differ from μ by +σ, + 2σ Theoretical Discrete and Continuous Distribution 53 and + 3σ. From the above Figure it is clear that a relatively small proportion of the area under the curve lies outside the pair of values x = μ + 2σ and x = μ – 2σ. 05. In X and Y are two independent standard normal variate then U = X + Y and V = X – Y are also independently distributed as a normal variate with mean 0 and variance 2.

Examples for Calculating Standard Deviation; Quartile, Coefficient of Dispersion and Coefficient of Variation: In case of Discrete Data: Simple Method 36 Medical Statistics and Demography Made Easy Variable xi 18 45 34 22 35 39 17 Total –12 15 4 –8 5 9 –13 210 724 No. 8  Mean  Measure of Dispersion 37 Short-cut Method: Variable xi ui2 ui = (xi – A) 18 45 34 22 35 39 17 Total –17 10 –1 –13 0 4 –18 289 100 1 169 0 16 324 – 35 899 No. of cases = 7; Let A = 35 Mean u = – 35 7 = – 5; therefore Mean (In this case we simply change the origin and SD is independent of Origin) In case of continuous frequency distribution: Age group fi Cumm.

05. In X and Y are two independent standard normal variate then U = X + Y and V = X – Y are also independently distributed as a normal variate with mean 0 and variance 2. The following tables gives the area under the normal probability curve for some important values of normal variate x. 7% Importance of Normal Distribution 1. e. Binomial, Poisson can be approximated by Normal distribution. 2. Many distribution of sample statistic tend to normal for large samples and as such they can be studied with the help of normal distribution.

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