In our first post we learned about Python virtual environments and how to use conda to create and manage them. In our second post, we learned how to install packages that were not directly accessible from the command conda install. Specifically, we learned about conda channels hosted at https://anaconda.org as well as pip, both of which can be used to
Read more
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
Read more
In our previous post we learned about Python virtual environments and how conda makes it easy for us as scientists to use virtual environments and access hundreds of useful packages. Despite the number of packages directly available through conda, not all packages can be downloaded this way. In this post we will learn how to add such packages to our
Read more
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
Read more
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
Read more
I have been coding with Python for several years and I only recently took the time to learn about Python environments. Now that I understand them, I can see why they are so useful, especially in this day and age of large team collaborations, research reproducibility, and sharing data and code when research results are published. The purpose of this
Read more
Scientifically Sound 