This is an exhaustive course which helps in learning different aspects of statistical analysis, social researches and survey analysis. It covers hands on training on all functions available in tool and it's application on real world datasets.


Basic Knowledge of Statistics

Faculty Profile

She is an Assistant Professor in the Department of Statistics, with a prominent college of University of Delhi. Prior to this she has also taught at Lady Shri Ram College and has over 13 years of teaching experience in statistics. She completed her doctorate from the Faculty of Management Studies, University of Delhi. She has presented papers at a number of conferences in India and abroad in the area of quality management on which most of her research is based. She has published a number of papers in referred national and international journals. She has also authored two books in the area of quantitative techniques in management. She has been a part of co-operative teaching for post graduate classes at the Department of Statistics, University of Delhi. She has presented lectures at Management Development Programme for executives of Gas Authority of India Limited (GAIL) and at Orientation Programme for faculty at Centre for Professional Development in Higher Education (CPDHE), University of Delhi. Her other interests include music and travel. She has trained in Indian classical music and western vocal music. Combining her academic and cultural interests, her current research includes research on exploring links between music and mathematics. She has recently presented a paper on music and mathematics at an international conference.


  • Installation of software
  • Introduction to SPSS
  • Dealing with output : Editing output, Printing results, Creating and editing a data file
  • Managing data: Listing cases, replacing missing values, computing new variables, recording variables, exploring data, selecting cases, sorting cases and merging files
  • Graphs, Frequencies
  • Descriptive Statistics : measures of central tendency, variability, normality
  • Cross Tabulation, t-test
  • Correlation
  • Multiple regression
  • Factor analysis