# dirty data

11 January 2017

## Why people hate statistics

This summer/Christmas break it has been my pleasure to help a young woman who is struggling with statistics, and it has prompted me to ask people who teach postgraduate statistical methods – WTF are you doing? Louise (name changed) is a bright, hard-working young woman, who has finished an undergraduate degree at a prestigious university and is now doing a Masters degree at a different prestigious university, which is a long way from where I live and will remain nameless. I have been working through her lecture slides, past and future and attempting to develop in her some confidence that she […]
16 February 2016

## Data for teaching – real, fake, fictional

There is a push for teachers and students to use real data in learning statistics. In this post I am going to address the benefits and drawbacks of different sources of real data, and make a case for the use of good fictional data as part of a statistical programme. Here is a video introducing our fictional data set of 180 or 240 dragons, so you know what I am referring to. Real collected, real database, trivial, fictional There are two main types of real data. There is the real data that students themselves collect and there is real data in […]
20 January 2014

## The Myth of Random Sampling

I feel a slight quiver of trepidation as I begin this post – a little like the boy who pointed out that the emperor has  no clothes. Random sampling is a myth. Practical researchers know this and deal with it. Theoretical statisticians live in a theoretical world where random sampling is possible and ubiquitous – which is just as well really. But teachers of statistics live in a strange half-real-half-theoretical world, where no one likes to point out that real-life samples are seldom random. The problem in general In order for most inferential statistical conclusions to be valid, the sample […]
30 September 2013

## Those who can, teach statistics

The phrase I despise more than any in popular use (and believe me there are many contenders) is “Those who can, do, and those who can’t, teach.” I like many of the sayings of George Bernard Shaw, but this one is dismissive, and ignorant and born of jealousy. To me, the ability to teach something is a step higher than being able to do it. The PhD, the highest qualification in academia, is a doctorate. The word “doctor” comes from the Latin word for teacher. Teaching is a noble profession, on which all other noble professions rest. Teachers are generally […]
9 September 2013

## How to study statistics (Part 1)

To students of statistics Most of my posts are directed at teachers and how to teach statistics. The blog this week and next is devoted to students. I present principles that will help you to learn statistics. I’m turning them into a poster, which I will make available for you to printing later. I’d love to hear from other teachers as I add to my list of principles. 1. Statistics is learned by doing One of the best predictors of success in any subject is how much time you spent on it. If you want to learn statistics, you need […]
1 April 2013

## Context – if it isn't fun…

The role of context in statistical analysis The wonderful advantage of teaching statistics is the real-life context within which any applicaton must exist. This can also be one of the difficulties. Statistics without context is merely the mathematics of statistics, and is sterile and theoretical.  The teaching of statistics requires real data. And real data often comes with a fairly solid back-story. One of the interesting aspects for practicing statisticians, is that they can find out about a wide range of applications, by working in partnership with specialists. In my statistical and operations research advising I have learned about a […]
25 February 2013

## Interpreting Scatterplots

Patterns, vocab and practice, practice, practice An important part of statistical analysis is being able to look at graphical representation of data, extract  meaning and make comments about it, particularly related to the context. Graph interpretation is a difficult skill to teach as there is no clear algorithm, such as mathematics teachers are used to teaching, and the answers are far from clear-cut. This post is about the challenges of teaching scatterplot interpretation, with some suggestions. When undertaking an investigation of bivariate measurement data, a scatterplot is the graph to use. On a scatterplot we can see what shape the […]
24 September 2012

## Teaching experimental design

Teaching Experimental Design – a cross-curricular opportunity The elements that make up a statistics, operations research or quantitative methods course cover three different dimensions (and more). There are: techniques we wish students to master, concepts we wish students to internalise, and attitudes and emotions we wish the students to adopt. Techniques, concepts and attitudes interact in how a student learns and perceives the subject. Sadly it is possible (and not uncommon) for students to master techniques, while staying oblivious to many of the concepts, and with an attitude of resignation or even antipathy towards the discipline. Techniques Often, and less […]
3 September 2012

## What Mathematics teachers need to know about statistics

My post suggesting that statistics is more vital for efficient citizens than algebra has led to some interesting discussions on Twitter and elsewhere. Currently I am beginning an exciting venture to provide support materials for teachers and students of statistics, starting with New Zealand. These two circumstances have led me to ponder about why maths teachers think that statistics is a subset of mathematics, and what knowledge and attitudes will help them make the transition to teaching statistics as a subject. An earlier post called for mathematics to leave statistics alone. This post builds on that by providing some ways […]
11 June 2012

## Lies and statistics

One of the most famous sayings about statistics is the line: “There are three types of lies, lies, damned lies and statistics.” This was stated by author Mark Twain (Samuel Clements)  and quoted by British statesman Benjamin Disraeli.  There is a book entitled, “How to lie with statistics”. Within high school education students are taught about misleading graphs. It seems clear that statistics and facts are not the same thing. Yet one True/False question many of my students continue to get wrong says “Statistical analysis is an objective science, unaffected by the researcher’s opinions.” The correct response is False, yet […]