TEACHING

Course Description:This course aims to provide  an understanding  of  basic  concepts  of biostatistics and the process involved in the scientific method of research. Students will be able to  identify the appropriate  statistical  methods  in  organizing and displaying  biological data and will  be  able  to apply  various discrete and continuous probability distributions concepts in biological data analysis. The course will help students in understanding  the application of parametric and  non-parametric methods  in  biological  data. Students  will  be able to understand the concepts of Epidemiology and Demography.

Course Description: This course covers applied statistical methods pertaining to time series and forecasting  techniques. Moving average models like simple, weighted and exponential are dealt with. Stationary time series models and non-stationary time series models like AR, MA, ARMA and ARIMA are introduced  to analyse  time  series  data.  Ability  to  approach andnanalyse univariate time series Ability to differentiate between various time series models like AR, MA, ARMA  and ARIMA models Evaluate stationary and non-stationary time series models Able to forecast future observations of the time series.

Course Description: The objective of this course is to Understand fundamental geospatial data analysis techniques .Apply geospatial data visualization methods to represent spatial patterns and trends. Apply different geospatial analysis techniques.Implement  geospatial  data  analytics workflows using relevant software tools.

Course  Description:  Upon  completing  the  course  the students will  learn  the  basics  of  R programming, perform basic statistical operation on data, visualize the data etc. This course is used to provide an introduction to R, statistical language and environment that provides more flexible graph capabilities  than other  popular statistical  packages.  The course  also  covers  the basics  of  R  for statistical computation, exploratoryanalysis ,and modeling.Demonstrate data handling using statistical tool R Perform graphical  representation  of data  using  R  Demonstrate the usage  of  R  for  an introductory statistics.

Course Description: This course will equip students with a wide variety of statistical methods for modelling and assessing risk across various domains. This course is designed to introduce the
concepts  of  estimation  and testing of  hypotheses.  This course also  deals  with  the  concept  of parametric  tests  for large  and small  samples.  It  also  provides knowledge about non-parametric tests  and  its  applications.  This  course  will enable students to understand the concept of estimation, test of hypothesis and to apply appropriate  estimation technique  and test  of hypothesis.

Course Description: This course is used to provide an introduction to R, statistical language and environment that provides  more  flexible  graph  capabilities  than  other  popular statisticalpackages. The course also covers the basics of R for statistical computation, exploratory analysis, and modeling. Understand R and R studio and create reports using R markdown. Demonstrate data  handling  using  loops  and control  structures  in  R.  Demonstrate  the  usage  of  R  for data manipulation and introductory Statistics.

This course is designed to introduce the concepts of estimation and testing of hypotheses. This course  also  deals  with  the concept  of  parametric  tests  for  large  and  small  samples.  It also provides  knowledge  about  non-parametric  tests  and  its applications.  This  course  will  enable students  to  understand the  concept  of  estimation,  test  of  hypothesis  and  to  apply appropriate estimation technique and test of hypothesis.