# Eat your greens

## Introduction to Power Analysis

In this series of ‘eat your greens‘ posts looking at core statistical concepts in more detail, we have looked closely at what a test of statistical significance actually is. In particular, we have focused on how to interpret the statistical probability value that various tests generate. This value, often labelled ‘P=’, ‘Prob’ or ‘Sig.’ in …

## Making sense of significance tests

A worked example of a classic inferential statistical procedure: the independent samples t-test.

## Understanding correlation

This is the latest in our ‘eat your greens’ series – a back to basics look at core statistical concepts that are often misunderstood or misapplied. In everyday speech the term ‘correlation’ refers to a mutual connection or relationship between two things. In statistics correlations are specific measures or values that attempt to quantify the …

## The gateway to inference – the standard error and confidence intervals

This is the fifth post in our ‘eat your greens’ series – a back to basics look at some of the core concepts of statistics and analytics that, in our experience, are frequently misunderstood or misapplied. In this post we’ll look in more depth at the concept of the standard error and confidence intervals. In …

## What’s ‘standard’ about a standard deviation?

This is the third post in our ‘eat your greens’ series – a back to basics look at some of the core concepts of statistics and analytics that, in our experience, are frequently misunderstood or misapplied. In this post we’ll look in more depth at the concept of the standard distribution. I’m often struck by …

## Testing versus inferring

This is the second post in our ‘eat your greens’ series – a back to basics look at some of the core concepts of statistics and analytics that, in our experience, are frequently misunderstood or misapplied. In this post we’ll look in more depth at the concept of testing versus inferring. One of most daunting …

## Just because something is statistically significant doesn’t mean it’s practically significant

What do we mean when we say something is statistically significant? A guide to one of the most misused concepts in statistics.

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