A student’s proposal, and a familiar methodological problem A student recently contacted me with a thesis proposal built around a very common design: one experimental group, one control group, and two measurements for each participant, one before and one after the intervention. The student proposed to analyze the data using…
Education Research by Design: Questions, Hypotheses, Data, and Methods
This is the first post in a new mini-series on RQ–RH–D–M across fields. The purpose of the series is to give readers a compact, practical toolkit showing how research questions (RQ), research hypotheses (RH) or working propositions, data (D), and methodology (M) can be aligned in different disciplines and under…
The Research Tetrad: Why Consistency Between Questions, Hypotheses, Data, and Methodology Is Everything
Intuitive introduction to the problem This is Part IV in the blog series on research design foundations. The earlier posts focused on research questions and research hypotheses across quantitative, qualitative, and mixed methods designs. This post takes the next natural step: it explains why those pieces only work when they…
Research Questions That Actually Work, Part III: How to Write a Good Mixed Methods Research Question
From parallel strands to an integrated research design This is the third post in the series Research Questions That Actually Work. The first post focused on quantitative research questions and the discipline of measurable design. The second examined qualitative research questions and the logic of meaning, context, and interpretive inquiry….
Research Questions That Actually Work, Part II: How to Write a Good Qualitative Research Question
From broad curiosity to meaningful and interpretable inquiry This is the second post in the series Research Questions That Actually Work. The first post examined quantitative research questions and the logic of measurable, answerable design. This post turns to qualitative research questions, where the central task is to formulate a…
Research Questions That Actually Work, Part I: How to Write a Good Quantitative Research Question
From broad interest to measurable, answerable design Many weak empirical studies do not fail because the software is wrong or the regression is badly coded. They fail earlier, when a broad topic is mistaken for a quantitative research question. A student says, “I want to study inflation and poverty,” or…
Quick start with R: Improving our regression model (Part 29)
Last time we created two variables and used the lm() command to perform a least squares regression on them, and diagnosing our regression using the plot() command. Here are the data again. height = c(176, 154, 138, 196, 132, 176, 181, 169, 150, 175)<br /> bodymass = c(82, 49, 53,…
Quick start with R: Diagnosing our regression model (Part 28)
Last time we created two variables and used the lm() command to perform a least squares regression on them, treating one of them as the dependent variable and the other as the independent variable. Here they are again. height = c(176, 154, 138, 196, 132, 176, 181, 169, 150, 175)…
Quick start with R: More on regression (Part 27)
In my last blog we created two variables and used the lm() command to perform a least squares regression on them, treating one of them as the dependent variable and the other as the independent variable. Here they are again. height = c(176, 154, 138, 196, 132, 176, 181, 169,…
Quick start with R: Scatterplot with regression line (Part 26)
Today let’s re-create two variables and see how to plot them and include a regression line. We take height to be a variable that describes the heights (in cm) of ten people. Copy and paste the following code to the R command line to create this variable. height <- c(176,…