• Dr. Rajesh

This course is devoted to make foundation of mathematics especially for those learners who do not have mathematics background after school mathematics. Last six units of this course are devoted to discuss introductory part of descriptive statistics.

• Prof. Manish Trivedi

This course has been designed to make you familiar with some of the basic methods of analysis of both univariate and bivariate data. It describes some measures based on central tendency, dispersion, skewness and kurtosis which are used to explore the properties of a distribution. Such types of measures are also used to analyse the univariate distribution and to compare two or more distributions. The concept of statistical relationship between two variables is then introduced and quantitative measures of relationship between two variables for determining the strength of relationship are also discussed. Next, we elaborate the average relationship between two variables in terms of regression analysis and also discuss the multiple and partial correlation.

sample from the same population is classified with respect to two or more qualitative variables. The aim of this course is to make you aware of the quantitative and qualitative techniques of statistics and their applications.

• Dr. Rajesh

This course is devoted to explain descrete probability through lots of examples. The idea of random variable and its two types discrete and continuous also have been discussed in detail. Last two blocks of this course discussed some famous discrete and continuous probability distributions. This course explains the fitting of simple and multiple logistic regression models along with concepts of other generalised linear models. It also describes concepts and application of survival analysis, various survival functions, Kaplan and Meier survival curve, Log-rank tests along with Cox proportional hazard model.

• Dr. Prabhat Kumar Sangal

This course will help you understand some useful techniques of statistics to draw inferences about the population on the basis of sample(s). It consists of the basic concepts and methodologies of sampling distributions with their applications, estimation theory, parametric and non-parametric testing of hypothesis.

This course also explores the basic concepts and methods of point and interval estimation, the concepts and terminologies of Testing of Hypothesis and the methodologies and applications of non-parametric tests.

• Prof. Manish Trivedi

This course is designed to acquaint the learners with the statistical techniques used for Sample surveys and their analysis, ANOVA, design of experiments and some useful methods of generation of random numbers and applications of simulation techniques.

We discuss some frequently used methods of sampling methods with their characteristics and applications, methodologies and applications of one-way and two-way analysis of variance techniques, different kinds of designs with their layout and analysis, concepts of factorial experiments and various kinds of systems and methods of generation of the random numbers of discrete and continuous variables.

• Dr. Rajesh
• Dr. Prabhat Kumar Sangal

The course is designed to develop the skills of learner in applying the techniques and tools of statistics to industrial and business data. Block 1 describe the concepts of quality control and the methods of process control by using the different kinds of quality control charts for variables as well as for attributes. Block 2 discuss the various methods of product control such as acceptance sampling plans, rectifying sampling plans, single sampling plans, double sampling plans etc. Third block discusses some decision making criteria and fourth block is devoted to introduce game theory. In this block games with saddle point and two person zero sum games have been discussed in detail.

• Prof. Manish Trivedi

This course discusses the concepts and techniques of operational research, such as the linear programming problem, the simplex method of solving linear programming problems, transportation problem, assignment problem, queueing theory, sequential problems and inventory models.

You will also be studying the concepts of regression modelling and time series analysis and forecasting techniques. In Regression Modeling the methods of fitting the best suited regression models have been discussed for the one independent and multiple more that one independent variables data. In Time Series analysis the study of the analysis of the time series data has been incorporated and discussed in depth.

• Dr. Rajesh
• Dr. Neha Garg

This course is devoted to explain the concepts of demography, vital events, methods of obtaining the vital statistics as well as various measures of vital statistics and life tables in the first block of this course. The second block discusses the direct and indirect bioassay, dose-response relationship along with design and analysis of parallel line, slope ratio and quantal bioassays. Third block of this course discuss what is epidemiology. Distinction between descriptive and analytic epidemiology is also discussed. Three famaous epidemiological study designs namely: Cross Sectional, Cohort and Case Control have been explained in detail. Finally, this block discusses about screening programme. The fourth block of this course discusses about conduct of clinical trials. Different phases of clinical trial and some well known measure of clinical trials are also discussed in this block.

• Dr. Neha Garg

The course is designed to develop the skills of learners in applying the techniques and tools of statistics to medical and pharmacy-related data. This course discusses the concepts of categorical variable and its related statistical tests along with the various measures of diagnostic tests, measures of agreement and disagreement, relative risk, odds ratio and Mantel-Haenszel method. It also describes the fitting of simple and multiple regression models as well as its related statistical analysis.

• Dr. Neha Garg

This course is designed with the lab components based on the contents discussed in the core courses of the programme in Microsoft Excel. Lab exercises based on the core courses would be worth two credits and a compulsory core component for all the learners. The lab sessions of this course include: Introduction to MS Excel, Classification and Tabulation of Data, Diagrammatic Presentation of Data, Graphical Presentation of Data, Graphical Presentation of Time Series Data, Measures of Central Tendency, Measures of Dispersion Moments, Skewness and Kurtosis, Correlation Analysis, One Sample Tests, Two Sample Tests, Analysis of Variance, and Design of Experiments.

• Dr. Neha Garg

This lab course worth two credits is designed with exercises based on the theory courses in Industrial Statistics specialisation. The lab sessions of this course include: Control Charts for Mean, Control Charts for Mean using Range, Control Charts for Mean using Standard Deviation, Control Charts for Range, Control Charts for Standard Deviation, Control Charts for Fraction Defective, Control Charts for Fraction Defective with Variable Sample Size, Control Charts for Number of Defectives, Control Charts for Number of Defects, Control Charts for Number of Defects per Unit, Simple Linear Regression, Multiple Linear Regression, Regression with Dummy Variable, Variable Selection Methods, Estimation of Trend by Curve Fitting, Smoothing or Filtering the Time Series, and Seasonal Component Analysis.

• Dr. Neha Garg

This lab course worth two credits is designed with exercises based on the theory courses in Biostatistics specialisation. The lab sessions of this course include: Chi-square Test for Association, Chi-square Test for Proportions, Other Statistical Tests for Categorical Data, Simple Linear Regression, Multiple Linear Regression, Regression Model with Indicator Variables, Simple Logistic Regression Model, Multiple Logistic Regression Model, Poisson Regression Model, Estimation of Survival Functions, Kaplan and Meier Method, and Log Rank Test.