It is applied course in statistics that is designed to provide you with the concepts and methods of statistical analysis for decision making under uncertainties. This course is a combination of lectures and computer-based practice, joining theory firmly with practice. It introduces techniques for summarizing and presenting data, estimation, confidence intervals, hypothesis testing, modeling relationships and some multivariate techniques. The lectures focuses more on understanding of key concepts and statistical thinking, and less on formulas and calculations, which can now be done on statistical software.
- Introduction to Quantitative Techniques for Decision Making
- Descriptive Analysis for Qualitative and Quantitative Data
- Descriptive Analysis for Quantitative Data (Cont.)
- Testing of Hypotheses One Sample Inference
- Testing of Hypotheses, two samples Inference
- Testing of Hypotheses, Paired samples Inference
- Testing of Hypotheses, more than two samples inference
- Comparing Groups Parametric and Non-Parametric Inference
- Correlation and Regression Analysis
- Multiple Linear Regression
- Logistic Regression
- Analysis of Categorical Data
- Factor Analysis
- Discriminent Analysis
- David. S. Moore and George P. McCabe (2003), Basics of Practice Statistics, Freeman Publishers.
- Landau, Sabine. (2004) “A handbook of statistical analyses using SPSS”, Chapman & Hall/CRC Press LLC
- Vijay G. (2002), Statistical Analysis with Excel, VJ Books.
- Wayne L. Winston (2007), Data Analysis and Business Modeling, Microsoft Press