Probability and Statistics: Biomedical Course Outline (BS-322)

Descriptive Statistics: Basic definitions, Measures of central tendency and variation, Chebychev‟s theorem, z-scores, Frequency distribution, Graphical representation of data stem & Leaf and Box Plots, Symmetry and skewness, Quintiles (Percentiles, Deciles & Quartiles)

Probability Theory: Basic definition and rules of probability, Conditional probability & Bayes‟s Theorem, Counting techniques.

Random Variable: Concept of random variable, Discrete & Continuous random variable and its random variable and variance of random variable and their properties.

Discrete & Continuous Probability Distributions: Uniform, Binomial, Multinomial, Hyper geometric, Negative binomial, Geometric, Poisson, Normal & Exponential distributions and their applications.

Sampling Theory: Sampling distribution of mean, t-distribution, and Sampling procedures.

Regression & Correlation: Linear, Exponential and Multiple Regression Models and Multiple Correlation Coefficient, ANOVA.

Statistical Inference: Estimation of parameters such as mean and variance, Classical and Bayesian method of estimation.

Hypothesis Testing: Z-test, t-test, and Goodness of fit test.