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    https://sophisticatedspectra.com/article/drosia-serenity-a-modern-oasis-in-the-heart-of-larnaca.2521391.html

    DROSIA SERENITY
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    An Introduction to Quantitative Research Methods for Marketing: Tools and Techniques Using SPSS and R

    Posted By: yoyoloit
    An Introduction to Quantitative Research Methods for Marketing: Tools and Techniques Using SPSS and R

    An Introduction to Quantitative Research Methods for Marketing
    by Daryanto, Ahmad;

    English | 2025 | ISBN: 1032525649 | 490 pages | True EPUB | 18.35 MB




    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 broken down into six core sections: Part 1 covers an introduction to quantitative research methods and how to get started with SPSS and R; Part 2 covers basic concepts in measurement, data descriptions, and distributions; Part 3 discusses hypothesis testing, and basic statistical tests; Part 4 covers regression analysis; Part 5 discusses advanced topics in regression analysis and analysis of variance; and finally Part 6 covers advanced statistical methods. Each chapter contains learning objectives and summaries to structure learning, while breakout boxes provide tips and draw students’ attention to dos and don’ts in statistical research. SPSS and R Action Boxes present step-by-step instructions on how to perform statistical tests and procedures with SPSS and R. Review questions prompt self-reflection on concepts taught in each chapter and are complemented by exercises that allow students to put their learning into practice.

    A very applied text designed to make this complex subject accessible to students with no background in quantitative methods, this book is valuable recommended and core reading for advanced undergraduate and postgraduate students studying business and marketing research methods, business analytics, marketing analytics, statistical skills and quantitative methods.

    Online supplementary resources include data sets and programming files.


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