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Über dieses Buch

This book is an easily accessible and comprehensive guide which helps make sound statistical decisions, perform analyses, and interpret the results quickly using Stata. It includes advanced coverage of ANOVA, factor, and cluster analyses in Stata, as well as essential regression and descriptive statistics. It is aimed at those wishing to know more about the process, data management, and most commonly used methods in market research using Stata.

The book offers readers an overview of the entire market research process from asking market research questions to collecting and analyzing data by means of quantitative methods. It is engaging, hands-on, and includes many practical examples, tips, and suggestions that help readers apply and interpret quantitative methods, such as regression, factor, and cluster analysis. These methods help researchers provide companies with useful insights.

Inhaltsverzeichnis

Frontmatter

1. Introduction to Market Research

Abstract
Market research is key to understanding markets and requires the systematic gathering and interpreting of information about individuals and organizations. This will give you an essential understanding of your customers’ needs, a head start on your competitors, allow you to spot potential problems, and future growth. Drawing on real examples, we show the value of market research, describe its main purposes, and explain how market research differs from marketing research. We explain what makes, or breaks, a successful market research study and describe when market research is most needed. We also provide a description of the different types of market research providers.
Erik Mooi, Marko Sarstedt, Irma Mooi-Reci

2. The Market Research Process

Abstract
How do companies design a suitable market research plan? We explore how you can plan, start, and identify the research question that will best guide your market research. Identifying the “right” question is difficult, but we provide several strategies and suggestions to help you quickly identify and formulate a market research process. In addition, we provide a practical overview of the different types of research, including exploratory, descriptive, and causal research; the different research goals and the needs they fulfil, and discuss their different uses and potential research outcomes. We offer guidelines that will help you determine the optimal match between the research question and the type of research design.
Erik Mooi, Marko Sarstedt, Irma Mooi-Reci

3. Data

Abstract
In market research, data is critical. Testing, measuring, improving, or creating new goods and services are difficult, or even impossible, without product and customer data. We discuss the different types of data, how they are constructed, and their attributes. We subsequently discuss the advantages and disadvantages of primary and secondary data and what each type allows you to do. We show you how to assess data’s validity and reliability, and discuss the implications that measurement errors can have for your data’s quality. We conclude with a discussion of important concepts, such as population, probability and non-probability sampling, and the relevance of sample size for market research.
Erik Mooi, Marko Sarstedt, Irma Mooi-Reci

4. Getting Data

Abstract
We first address the nuts-and-bolts questions of the data collection stage. How does one find secondary data and decide on their suitability? Can one best collect primary data through, for example, observations, questionnaires, or experiments if secondary data are unavailable? We thus provide the key theoretical concepts, choices, and practicalities associated with collecting data. We first discuss the practicalities of secondary data’s use, including their sources and availability, how to assess the inclusion of key variables, and the data’s validity and reliability. If secondary data are unavailable, outdated, or too costly, we show how to best collect your own data given the question you wish to study. Primary data collection styles, such as observations, survey questionnaires, and experiments, are reviewed and we provide a range of recommendations on the type of data to use for the relevant situation, or research question.
Erik Mooi, Marko Sarstedt, Irma Mooi-Reci

5. Descriptive Statistics

Abstract
We first provide an overview of market research’s workflow. We then discuss efficient strategies to help you structure your project’s database, as well as enter, clean, and easily check the collected data for inconsistencies. In addition, we provide easy strategies that allow you to handle missing data observations before we describe the most common and useful univariate and bivariate descriptive graphs and statistics. Thereafter, we take you through the basics of Stata, including its toolbar and shortcuts to frequently used commands, and provide useful tips on how to create and interpret descriptive graphs and table outputs. A range of descriptive statistics is illustrated and applied in Stata, including bar charts, histograms, box plots, pie charts, frequency tables, scatter graphs, crosstabs, and correlation tables, all of which are useful for differently scaled variables. We make use of a case study for an easy and meaningful interpretation of the graphs and table outputs. We conclude with recommendations for further readings and a case study with review questions.
Erik Mooi, Marko Sarstedt, Irma Mooi-Reci

6. Hypothesis Testing & ANOVA

Abstract
We first describe the essentials of hypothesis testing and how testing helps make critical business decisions of statistical and practical significance. Without using difficult mathematical formulas, we discuss the steps involved in hypothesis testing, the types of errors that may occur, and provide strategies on how to best deal with these errors. We also discuss common types of test statistics and explain how to determine which type you should use in which specific situation. We explain that the test selection depends on the testing situation, the nature of the samples, the choice of test, and the region of rejection. Drawing on a case study, we show how to link hypothesis testing logic to empirics in Stata. The case study touches upon different test situations and helps you interpret the tables and graphics in a quick and meaningful way.
Erik Mooi, Marko Sarstedt, Irma Mooi-Reci

7. Regression Analysis

Abstract
We first provide comprehensive, but simple, access to essential regression knowledge by discussing how regression analysis works, the requirements and assumptions on which it relies, and how you can specify a regression analysis model that allows you to make critical decisions for your business, clients, or project. Each step involved in regression analysis is linked to its execution in Stata (using menus and code). We show how to use a range of Stata’s easy-to-learn statistical procedures that underlie regression analysis, which will allow you to analyze, chart, and validate regression analysis results and to assess your analysis’s robustness. Interpretation of Stata output can be difficult, but we make this easier by means of an annotated case study. We conclude with suggestions for further readings on the use, application, and interpretation of regression analysis.
Erik Mooi, Marko Sarstedt, Irma Mooi-Reci

8. Principal Component and Factor Analysis

Abstract
We first provide comprehensive and advanced access to principal component analysis, factor analysis, and reliability analysis. Based on a discussion of the different types of factor analytic procedures (exploratory factor analysis, confirmatory factor analysis, and structural equation modeling), we introduce the steps involved in a principal component analysis and a reliability analysis, offering guidelines for executing them in Stata. Specifically, we cover the requirements for running an analysis, modern options for extracting the factors and deciding on their number, as well as for interpreting and judging the quality of the results. Based on a step-by-step description of Stata’s menu options and code, we present an in-depth discussion of each element of the Stata output. Interpretation of output can be difficult, which we make much easier by means of various illustrations and applications, using a detailed case study to quickly make sense of the results. We conclude with suggestions for further readings on the use, application, and interpretation of factor analytic procedures.
Erik Mooi, Marko Sarstedt, Irma Mooi-Reci

9. Cluster Analysis

Abstract
We provide comprehensive and advanced knowledge of cluster analysis knowledge. We first introduce the principles of cluster analysis and outline the steps and decisions involved. We discuss how to select appropriate clustering variables and subsequently introduce modern hierarchical and partitioning methods for cluster analysis, using simple examples to illustrate how they work. We also discuss the key measures of similarity and dissimilarity, and offer guidance on how to decide the number of clusters to extract from the data. Each step in a cluster analysis is subsequently linked to its execution in Stata (using menus and code), thus enabling readers to analyze, chart, and validate the results. Interpretation of Stata output can be difficult, but we make this easier by means of an annotated case study. We conclude with suggestions for further readings on the use, application, and interpretation of cluster analysis.
Erik Mooi, Marko Sarstedt, Irma Mooi-Reci

10. Communicating the Results

Abstract
Communicating the results of your study, project, or business case is crucial in market research. We discuss the core elements of a written research report, provide guidelines on how to structure its core elements, and how you can communicate the research findings to your audience in terms of their characteristics and needs. We show you how to organize and simplify complex and dense information in an efficient and reader-friendly way. Using Stata, and drawing on a case study, we show how you can combine and present several graphs and (regression) tables concisely and clearly. We also provide guidelines for oral presentations, suggestions for visual aids that facilitate the communication of difficult ideas, and ideas on how to best structure the oral presentation of results. Finally, we discuss ethical issues that may arise when communicating report findings to your client.
Erik Mooi, Marko Sarstedt, Irma Mooi-Reci

Backmatter

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