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Summary
Summary
This concise text discusses a wide range of quantitative research methods, including advanced techniques such as logic regression, multilevel modeling, and structural equation modeling. Because the text emphasizes concepts rather than mathematics and computation formulas, it is accessible to a wide range of users of research. Professional practitioners in areas such education, business, social work, and psychology can gain an understanding of research methods sufficient to base their work on advanced research in their fields. The text discusses the quantitative designs and analytic techniques most needed by students in the social sciences and in applied disciplines such as education, social work, and business. It teaches what the various methods mean, when to use them, and how to interpret their results. Since it emphasizes general understanding rather than mathematical foundations, students are able to review a broad range of methods in a comparatively short space.
Table of Contents
| Preface |
| Acknowledgements |
| I. THE BASICS |
| Introduction to Part I |
| 1 Design, Measurement, and Analysis |
| What is the role of research questions in the process of planning research? |
| How are design, measurement, and analysis defined and related? |
| What are the main types of research design? |
| What is measurement and what are its main types? |
| What different kinds of statistical analysis are there? |
| What is statistical significance? |
| How have recent controversies changed statistical practice? |
| What are Type I and Type II errors, and why should I care? |
| 2 Standard Deviation and Correlation |
| What is a standard deviation and what does it tell us? |
| How do we calculate the standard deviation and the variance? |
| What are standard scores and how can we use them? |
| What is the normal distribution and how is it related to standard scores? |
| What is a correlation coefficient and how do we interpret it? |
| How is a correlation coefficient calculated? |
| How do we interpret correlations and their statistical significance? |
| How can correlations be used to find relations in and interpret real data? |
| What is a large correlation? |
| What is linearity, and why is it important for interpreting correlations? |
| What is the relationship of correlation and cause? |
| 3 Variables and the Relations Among Them |
| How are different types of variables related? |
| How can we depict relations among variables and use the depictions to understand our research questions? |
| How does the inclusion of effect modifiers make our understanding of our research questions more realistic? |
| What is causal modeling and how do we move from graphics to equations--and back again? |
| How can we use causal modeling to think about a research topic? The example of parental involvement |
| How can we use causal modeling to think about a research topic? The example of student advisory programs |
| What is the nature of causation when studying research problems? |
| What are the criteria for assessing causation? |
| 4 The Uses of Descriptive Statistics |
| How do researchers use the term "descriptive" statistics? |
| How are descriptive statistics used to depict populations and samples? |
| What are measures of central tendency and how does one choose among them? |
| How do we explore the shape of data distributions? |
| How does the theoretical normal distribution relate to descriptions of actual data distributions? |
| What do you do if your data are not continuous and not (approximately) normally distributed? |
| What are non-parametric statistical techniques and how are they used? |
| How can we use descriptive statistics to check assumptions that have to be true for the proper use of other techniques? |
| What are some substantive uses of descriptive (non-inferential) statistics? |
| 5 Surveys and Random Sampling |
| What criteria define a good sample? |
| What are the main varieties of probability samples and what are the chief features of each? |
| What can be learned from non-probability samples? |
| How important is sample size? |
| How can surveys be designed to elicit the most valuable responses? |
| How can questions be written so they will lead to effective measurement? |
| How can responses to survey questions be analyzed? |
| When are surveys likely to b |
