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Quantitative Analysis Software (Workshop)

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Course Type Course Code No. Of Credits
Discipline Core SPG2PH507 1

Semester and Year Offered: 4th Semester, 2nd Year

Course Coordinator and Team: Samik Chowdhury

Email of course coordinator: samik@aud.ac.in

Pre-requisites: None

Aim:  The objective of the Quantitative Analysis workshop is to gain hands on training in applied statistical analysis of quantitative data. This course builds upon an assumed familiarity with basic theoretical statistics/biostatistics which the students had an exposure to in their first semester of the programme. The workshop will consist of two parts. In the first part the students will learn how to handle data, compute descriptive statistics and perform graphical analyses in Microsoft Excel. In the second part students will learn to perform analyses of data using any one of the statistical softwares – SPSS, STATA or R.

Course Outcomes:

  • Knowledge of summarising and presenting quantitative information
  • Skill to use any one software for statistical analysis
  • Ability to interpret and replicate statistical analysis in academic literature

 Brief description of modules/ Main modules:

Module No.

Title

Contents

Time (hours)

1

Handling raw data in MS-Excel and SPSS/STATA/R

Entering data, importing data, sorting, filtering, generating queries

Defining variables, loading and saving data files, examining and printing output files, defining variable measurement scales, transformation of a variable, creation of a new variable, recoding a variable and others

3 hrs

2

Exploratory analysis of data in MS-Excel and SPSS/STATA/R

MS-Excel

Charts, pivot tables, formulas and functions in MS-Excel

SPSS/STATA/R

Descriptive statistics – frequency distribution,crosstab outputs, measures of central tendency and dispersion.

Graphing data - Bar charts, pie charts, histograms, scatterplots, editing graphs

5 hrs

3

Inferential statistics, measuring association, causation using SPSS/STATA/R

Level of significance, confidence interval, correlation coefficient, simple linear regression, multiple linear regression, logistic regression, parametric inferential statistics, t-tests (independent, paired samples), ANOVA,  non-parametric inferential statistics (Chi square tests)

8 hrs

Total

16 hrs

Assessment Details with weights:

  • Class based exercise  -I – 50%
  • Class based exercise – II – 50%

Reading List:

  • Suárez, E. L., Pérez, C. M., Nogueras, G. M., & Moreno-Gorrín, C. (2016). Biostatistics in Public Health Using STATA. CRC Press.
  • Abbott, M. L. (2016). Using statistics in the social and health sciences with SPSS and excel. John Wiley & Sons.
  • Cunningham, J. B., & Aldrich, J. O. (2011). Using SPSS: An interactive hands-on approach. Sage.
  • Le, C. T. (2010). Health and numbers: a problems-based introduction to biostatistics. John Wiley & Sons.
  • Lalanne, C., & Mesbah, M. (2016). Biostatistics and Computer-based Analysis of Health Data Using R. Elsevier.
  • Berk, K. N., & Carey, P. (1998). Data analysis with Microsoft excel. Pacific Grove, CA: Duxbury Press.
  • Cronk, B. C. (2017). How to use SPSS®: A step-by-step guide to analysis and interpretation. Routledge.
  • Healey, J. F. (2015). The essentials of statistics: A tool for social research. Cengage Learning.
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