Recently, I reviewed a number of research proposals in which some applied qualitative or mixed (i.e. quantitative and qualitative) methods to answer health questions. I had my “reviewer hat” on as I assessed the proposals for research quality. After 3-4 proposals, it occurred to me that while assessing quantitative research proposals for research quality and reproducible practices was straightforward, doing
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Research funders are beginning to require that data produced in the course of the research they fund should be made openly available. This is to encourage further discovery and exploration, as well as to extend research questions. In addition, releasing data and code can be in researchers’ interest because it provides a complete and transparent record of how the conclusions
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In previous posts, we learned that the aim of statistics is to extrapolate properties of samples to make inferences about population. However, random variation in individuals in the population produces sampling error, which means a single sample may not accurately reflect properties of the population. When data are binary, we learned how the 95% confidence interval (CI) of a sample
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At Scientifically Sound, we have shown how to verify whether data are Normally distributed, and discussed whether it matters that data are Normally distributed. Let’s take a step back and consider what a Normal distribution is. A Normal distribution is a bell-shaped curve observed when the number of data points that occur in a population (y-axis) is plotted against the
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In a previous post we used binary data to demonstrate sampling error and calculate 95% confidence intervals (CI). Now, suppose that data can take many values; for example, normal body temperature has many values and varies continuously over a physiological range. How can we measure this variability in body temperature? For continuous data, variability can be quantified as the standard
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Understanding the meaning of a confidence interval can take a little effort. The key idea is we want to infer findings from a study to subjects who were not part of the study. Sometimes, reading explanations in different words can help. Let’s pause in our series and see how others have explained what confidence intervals mean: Harvey Motulsky: The true
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