Ahmad Daryanto
An Introduction to Quantitative Research Methods for Marketing
Tools and Techniques Using SPSS and R
Ahmad Daryanto
An Introduction to Quantitative Research Methods for Marketing
Tools and Techniques Using SPSS and R
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This introductory text covers the foundational concepts and statistical applications of quantitative research techniques using SPSS and R. Using step-by-step examples throughout, the book is designed to make this complex subject accessible to students with no background in quantitative methods.
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This introductory text covers the foundational concepts and statistical applications of quantitative research techniques using SPSS and R. Using step-by-step examples throughout, the book is designed to make this complex subject accessible to students with no background in quantitative methods.
Produktdetails
- Produktdetails
- Verlag: Routledge
- Seitenzahl: 490
- Erscheinungstermin: 3. Juni 2025
- Englisch
- Abmessung: 250mm x 175mm x 31mm
- Gewicht: 1017g
- ISBN-13: 9781032525662
- ISBN-10: 1032525665
- Artikelnr.: 72211569
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- gpsr@libri.de
- Verlag: Routledge
- Seitenzahl: 490
- Erscheinungstermin: 3. Juni 2025
- Englisch
- Abmessung: 250mm x 175mm x 31mm
- Gewicht: 1017g
- ISBN-13: 9781032525662
- ISBN-10: 1032525665
- Artikelnr.: 72211569
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- gpsr@libri.de
Ahmad Daryanto is a Professor of Marketing at Lancaster University Management School in the United Kingdom. He received his BSc degree in Environmental Engineering from Bandung Institute of Technology in Indonesia, a MSc degree in Engineering Mathematics from Twente University in the Netherlands, and a PhD degree in Marketing from Maastricht University in the Netherlands. He has published in top international journals such as the Journal of Consumer Psychology, Journal of the Academy of Marketing Science, Journal of Service Research, Industrial Marketing Management, Personality and Individual Differences, Cities, Journal of Business Research among others. Some of his research has been funded by the Fundamental Research Funds for the Central Universities in China. Anto currently acts as an associate editor of an Elsevier journal, Sustainable Futures, and has acted as a co-chair session on marketing analytics and big data at the prestigious AMA winter conference. Anto held a visiting professor position at Beijing Foreign Studies University under the scheme of High-End Foreign Expert Program of Government of China, and has acted as an external grant reviewer for UK Research Innovation (UKRI) future leadership and a lead reviewer for the British Academy small research grants. He is currently an external examiner at two universities: International Business School of Xi'an-Jiaotong Liverpool University for its Marketing degree programs, and Regents' University of London for its new MSc program in Data Science and Business. He was an external examiner at Imperial College Business School, London, for its MSc in Strategic Marketing program. Anto is a statistical programmer who has written several SPSS macros. He is the inventor of EndoS, which is a software that can be used to address an endogeneity problem discussed in this book; his HeteroskedasticityV3 software has been used by graduate students and researchers worldwide. Anto is a keen chess player and runs a chess club at the Lancaster public library in the UK.
Part 1: Getting Started 1. An Introduction 2. Getting Started with SPSS 3.
Getting Started with R Part 2: Basic Concepts in Measurement, Data
Descriptions and Distributions 4. Construct and Measurement 5. Describing
Quantitative Data 6. Normal Distribution 7. Distributions Derived from
Normal Distribution 8. Sampling Distribution Part 3: Hypothesis Testing and
Basic Statistical Tests 9. Hypothesis Testing and Significance 10. Testing
Proportions 11. Correlation Part 4: Regression Analysis 12. Simple Linear
Regression 13. Multiple Regression 14. Regression Diagnostics Part 5:
Advanced Topics in Regression and ANOVA 15. Mediation 16. Moderation 17.
Endogeneity 18. Analysis of Variance 19. Experiment Part 6: Advanced
Statistical methods 20. Cluster Analysis 21. Principal Component Analysis
22. Factor Analysis 23. Binary Logistic Regression
Getting Started with R Part 2: Basic Concepts in Measurement, Data
Descriptions and Distributions 4. Construct and Measurement 5. Describing
Quantitative Data 6. Normal Distribution 7. Distributions Derived from
Normal Distribution 8. Sampling Distribution Part 3: Hypothesis Testing and
Basic Statistical Tests 9. Hypothesis Testing and Significance 10. Testing
Proportions 11. Correlation Part 4: Regression Analysis 12. Simple Linear
Regression 13. Multiple Regression 14. Regression Diagnostics Part 5:
Advanced Topics in Regression and ANOVA 15. Mediation 16. Moderation 17.
Endogeneity 18. Analysis of Variance 19. Experiment Part 6: Advanced
Statistical methods 20. Cluster Analysis 21. Principal Component Analysis
22. Factor Analysis 23. Binary Logistic Regression
Part 1: Getting Started 1. An Introduction 2. Getting Started with SPSS 3.
Getting Started with R Part 2: Basic Concepts in Measurement, Data
Descriptions and Distributions 4. Construct and Measurement 5. Describing
Quantitative Data 6. Normal Distribution 7. Distributions Derived from
Normal Distribution 8. Sampling Distribution Part 3: Hypothesis Testing and
Basic Statistical Tests 9. Hypothesis Testing and Significance 10. Testing
Proportions 11. Correlation Part 4: Regression Analysis 12. Simple Linear
Regression 13. Multiple Regression 14. Regression Diagnostics Part 5:
Advanced Topics in Regression and ANOVA 15. Mediation 16. Moderation 17.
Endogeneity 18. Analysis of Variance 19. Experiment Part 6: Advanced
Statistical methods 20. Cluster Analysis 21. Principal Component Analysis
22. Factor Analysis 23. Binary Logistic Regression
Getting Started with R Part 2: Basic Concepts in Measurement, Data
Descriptions and Distributions 4. Construct and Measurement 5. Describing
Quantitative Data 6. Normal Distribution 7. Distributions Derived from
Normal Distribution 8. Sampling Distribution Part 3: Hypothesis Testing and
Basic Statistical Tests 9. Hypothesis Testing and Significance 10. Testing
Proportions 11. Correlation Part 4: Regression Analysis 12. Simple Linear
Regression 13. Multiple Regression 14. Regression Diagnostics Part 5:
Advanced Topics in Regression and ANOVA 15. Mediation 16. Moderation 17.
Endogeneity 18. Analysis of Variance 19. Experiment Part 6: Advanced
Statistical methods 20. Cluster Analysis 21. Principal Component Analysis
22. Factor Analysis 23. Binary Logistic Regression







