This book is useful for the postgraduate students of business management and statistics. The objective of this book is not only to make the students to get a basic understanding of statistical techniques but also to get a thorough understanding of how to apply the techniques for practical cases which can be applied during their project work and even when the students enter the industry after finishing their courses. The text uses simple analytical techniques to solve real-time business problems. The solutions to problems contain step-by-step instructions and Excel screenshots to reinforce the understanding of the topics.
This text will help students to: - develop the necessary skills to solve practical decision problems using Excel spreadsheets
- acquire knowledge of data analysis software for business modelling
- use analytical techniques which they had learnt to solve real-time problems.
Sprache
Verlagsort
Zielgruppe
Für höhere Schule und Studium
Maße
Höhe: 235 mm
Breite: 178 mm
Dicke: 20 mm
ISBN-13
978-81-203-5288-9 (9788120352889)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Hansa Lysander Manohar, PhD (Anna University), is Associate Professor, Department of Management Studies, College of Engineering, Guindy, Anna University, Chennai. An alumna of IIM Ahmedabad, Dr. Hansa Manohar has been involved with Academic Institutions like All India Council for Technical Education (AICTE) and University Grants Commission (UGC) in conducting training programmes and capacity building workshops. She has also collaborated with Industrial Institutions like Confederation of Indian Industries (CII) in conducting technical seminars. With over 25 years of teaching and research experience, she has published/presented several research papers in national and international journals/conferences. Her area of research interest includes Operations and Technology Management.
- Preface
- Acknowledgement
- 1. Introduction to Data Analysis Using Excel
- 2. Random Number Generation
- 3. Rank and Percentile
- 4. Sampling: Random and Systematic
- 5. Descriptive Statistics
- 6. Inferential Statistics: Small Samples-Student's t-Test: Comparison of Means
- 7. Inferential Statistics: Small Samples-Paired t-Test: Comparison of Means
- 8. Inferential Statistics: Large Samples-z-Test: Comparison of Means
- 9. Inferential Statistics: Analysis of Variance (ANOVA)
- 10. Inferential Statistics: Chi-Square Test
- 11. Inferential Statistics: Non-parametric Test-Mann-Whitney U Test
- 12. Inferential Statistics: Non-parametric Test-Kruskal-Wallis Test
- 13. Inferential Statistics: Correlation
- 14. Predictive Analytics: Linear Regression-Simple and Multiple Linear Regression
- 15. Predictive Analytics: Forecasting-Exponential Smoothing, Moving Average and Linear Trend
- 16. Portfolio Selection
- 17. Risk Analysis and Sensitivity Analysis
- 18. Sensitivity Analysis Using What-If Analysis
- 19. Prescriptive Analytics: Optimization-Transportation Problem
- 20. Prescriptive Analytics: Optimization-Assignment Problem
- 21. Prescriptive Analytics: Optimization-Shortest Path Problem: Maximum Flow Problem
- 22. Project Management: Critical Path Method (CPM)
- 23. Queuing Theory
- 24. Inventory Models: Economic Order Quantity (EOQ)
- Glossary
- Index
