Tag Archives: confidence intervals

What are degrees of freedom in statistics? – Part 2

In a previous post we saw that t distributions with more degrees of freedom approximate the Normal distribution more closely, and degrees of freedom are increased by testing more subjects. How do degrees of freedom influence t values when calculating confidence intervals? The confidence interval about an effect indicates how the effect varies if the study is repeated many times.

Read more

Calculating sample size using precision for planning

Most sample size calculations for independent or paired samples are performed based on power to detect an effect of a certain size, assuming there’s no effect. Instead, Cumming and Calin-Jageman recommend that readers plan studies to detect precise effects. The 95% confidence interval (CI) indicates precision about effects. Therefore, it is possible to plan studies to detect narrow 95% CIs

Read more

The Conversation: Seven deadly sins of statistical misintepretation, and how to avoid them

The Conversation recently published a nice piece by Louis and Chapman on common statistical misinterpretations and how they can be avoided. Here is summary of the main points: Problem Reason Solution 1. Assuming small differences are meaningful Most small differences are due to chance, not meaningful differences Ask for the margin of error (ie. half of the 95% CI): if

Read more

Independent t-test in Python

In a previous post we learned how to perform an independent t-test in R to determine whether a difference between two groups is important or significant. In this post we will learn how to perform the same test using the Python programming language. Along the way we will learn a few things about t distributions and calculating confidence intervals. dataset.In

Read more

Why we need confidence intervals

At Scientifically Sound, we have reviewed ongoing discussions on the benefits of confidence intervals (CIs) over p values for statistical analysis and reproducibility in research. In a short editorial, the statistician Doug Altman summarised why we need confidence intervals and showed how confidence intervals force investigators to consider sizes of effects. Here are the key points: Two different but complementary

Read more
« Older Entries