Biostatistics

Introduction to Bio-Statistics, types of data and graphical representation.

Descriptive statistics: Measures of Central tendency- Mean ,

median, mode.
 Measures of dispersion-Range, Standard deviation, coefficient of Variation.

Calculating Measures from an Ungrouped Frequency Tables.
Basic probability. Conditional probability, concept of independence, sensitivity, specificity. Bayes Theorem for predictive probabilities.
Some discrete probability distributions: cumulative probability .
Binomial, and Poisson -their mean and variance.
Continuous probability distributions: Normal distribution,  Standard normal distribution and t distribution.
Sampling with and without replacement, sampling distribution of one and two sample means and one and two proportions.

Statistical inference: Point and interval estimation, Type of errors,

Concept of P-value.
Testing hypothesis about one and two samples means and proportions including paired data – different cases under normality.