Qualitative Research Guidelines Project
Interactive Statistical Calculation Pages
Qualitative research
In the conventional view, qualitative methods produce information only on the particular cases studied, and any more general conclusions are only propositions (informed assertions). Quantitative methods can then be used to seek empirical support for such research hypotheses. History[edit] Data collection[edit] Qualitative researchers face many choices related to data collection ranging from grounded theory practice, narratology, storytelling, classical ethnography, or shadowing. Qualitative methods are also loosely present in other methodological approaches, such as action research or actor-network theory. Qualitative research often categorizes data into patterns as the primary basis for organizing and reporting results. The ways of participating and observing can vary widely from setting to setting. The data that is obtained is streamlined to a definite theme or pattern. Some distinctive qualitative methods are the use of focus groups and key informant interviews. 10. Data analysis[edit]
Spatial Statistical Sites
13887_Chapter5.pdf
Structural Equation Modeling
David A. Kenny January 12, 2014 Structural Equation Modeling Find out about an interesting conference about SEM: Modern Modeling Methods 2015. This page serves as a gateway to a tutorial on structural equation modeling or SEM. Go to SEM links. Tutorials Ed Rigdon's pages G. Books Kline book on SEM Brown book on CFA Enders book on missing data Pearl’s Causality book Download the revised edition of Correlation and Causality Download Estimating the Effects of Social Interventions written with C. Go back to homepage.
It's (Beyond) Time to Drop the Terms Causal-Comparative and Correlational Research
It's (Beyond) Time to Drop the Terms Causal-Comparative and Correlational Research in Education Burke Johnson University of South Alabama Instructional Design & Development Program Abstract Presentations of causal-comparative and correlational research methods in educational research textbooks are critiqued. The first major contention in this paper is that, ceteris paribus, causal-comparative research is neither better nor worse than correlational research in establishing evidence of causality. What is the Issue? Authors of several popular educational research methods books make a distinction between two nonexperimental methods called causal-comparative research and correlational research (e.g., Charles, 1995; Fraenkel & Wallen, 1996; Gay, 1996; Martella, Nelson, & Marchand-Martella, 1999). Charles (1998) says, "Causal-comparative research strongly suggests cause and effect..." To illustrate the point about variable scaling, consider the following example. Figure 1. Conclusion References 1.
Almost Sure | A random mathematical blog
qualitative research designs?preview=Patton 10 tips for doc students and types of qual designs
Statistical Inference (and what is wrong with classical statistics)
Home Scope This page concerns statistical inference as described by the most prominent and mainstream school of thought, which is variously described as ‘classical statistics’, ‘conventional statistics’, ‘frequentist statistics’, ‘orthodox statistics’ or ‘sampling theory’. Oddly, statistical inference—to draw conclusions from the data—is never defined within the paradigm. The practice of statistical inference as described here includes estimation (point estimation and interval estimation (using confidence intervals)) and significance tests (testing a null hypothesis and calculating p-values). The important point is that all of these methods involve pretending that our sample came from an imaginary experiment that involved considering all possible samples of the same size from the population. History The frequentist interpretation of probability is very limited A frequentist subscribes to the long run relative frequency interpretation of probability. The nature of the null hypothesis test Links
Core Concepts § Q: Foundations of Qualitative Research in Education
Core Concepts in Qualitative Research In this section, we discuss a number of issues, areas of contention, and concepts that are important to the constantly evolving field of qualitative research. Subjectivity offers a starting point for understanding how a researcher's perspectives, biographies, assumptions, and commitments shape the research process. Paradigms engages with question like what is knowledge, and, as researchers, how do we know what we know? Emic & Etic outlines two general, contrasting approaches to qualitative research. Computer Assisted Analysis frames some of the discussion around new qualitative data analysis software.
HyperStat Online: An Introductory Statistics Textbook and Discussion of whether most published research is false
Recommend HyperStat to your friends on Facebook Click here for more cartoons by Ben Shabad. Other Sources NIST/SEMATECH e-Handbook of Statistical Methods Stat Primer by Bud Gerstman of San Jose State University Statistical forecasting notes by Robert Nau of Duke University related: RegressIt Excel add-in by Robert Nau CADDIS Volume 4: Data Analysis (EPA) The little handbook of statistical practice by Gerard E. Stat Trek Tutorial Statistics at square 1 by T. Concepts and applications of inferential statistics by Richard Lowry of Vassar College CAST by W. SticiGui by P. SurfStat by Keith Dear of the University of Newcastle. Introductory statistics: Concepts, models, and applications by David W. Multivariate statistics: Concepts, models, and applications by David W. Electronic textbook by StatSoft A new view of statistics by Will Hopkins of the University of Otago The knowledge base: An online research methods textbook by William M.
