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The focus of this book is on using quantitative research methods to test hypotheses and build theory in political science, public policy and public administration. It is designed for advanced undergraduate courses, or introductory and intermediate graduate-level courses. The first part of the book introduces the scientific method, then covers research design, measurement, descriptive statistics, probability, inference, and basic measures of association. The second part of the book covers bivariate and multiple linear regression using the ordinary least squares, the calculus and matrix algebra that are necessary for understanding bivariate and multiple linear regression, the assumptions that underlie these methods, and then provides a short introduction to generalized linear models.The book fully embraces the open access and open source philosophies. The book is freely available in the SHAREOK repository; it is written in R Markdown files that are available in a public GitHub repository; it uses and teaches R and RStudio for data analysis, visualization and data management; and it uses publically available survey data (from the Meso-Scale Integrated Socio-geographic Network) to illustrate important concepts and methods. We encourage students to download the data, replicate the examples, and explore further! We also encourage instructors to download the R Markdown files and modify the text for use in different courses.
In this course, you will obtain some insights about marketing to help determine whether there is an opportunity that actually exists in the marketplace and whether it is valuable and actionable for your organization or client. Week 1: Assess methods available for creating quantitative surveys, along with their advantages and disadvantages. Identify the type of questions that should be asked and avoid unambiguous survey questions. Week 2: Design, test, and implement a survey by identifying the target audience and maximizing response rates. You will have an opportunity to use Qualtrics, a survey software tool, to launch your own survey. Week 3: Analyze statistical models that can be applied to your marketing data, so that you can make data-driven decisions about your marketing mix. Week 4: Predict most likely outcomes from the marketing decisions and match the type of analysis needed for your business problem. Take Quantitative Research as a standalone course or as part of the Market Research Specialization. You should have equivalent experience to completing the second course in this specialization, Qualitative Research, before taking this course. By completing the third class in the Specialization, you will gain the skills needed to succeed in the full program.
An introduction and examples of how to use Correlation and Simple Linear Regression. Explaining concepts as coefficient of correlation, dependent variables, independent variables and the straight line equation and residuals.
reviews a range of survey data collection methods that are both interview-based (face-to-face and telephone) and self-administered (paper questionnaires that are mailed and those that are implemented online, i.e. as web surveys).