Dr. Mark Gardener


Providing training for:

  • Ecology
  • Data analysis
  • Statistics
  • R The statistical programming language
  • Data management
  • Data mining

Statistics – A guide

These pages are aimed at helping you learn about statistics. Why you need them, what they can do for you, which routines are suitable for your purposes and how to carry out a range of statistical analyses.

On this page:

Data Analysis Home | Forward to Summarizing data =>

See also:

Table of Contents for Statistics – A guide


Table of contents

This table lists the major pages and high-level sub-headings. Each page has its own, more detailed TOC. Use the links in the table of contents to jump directly to a topic. Alternatively work your way back and forth in a linear manner using the <= Previous and Next => links at the end of each section.

Statistics can: Summarize data.

Statistics can: Help you make decisions.

Statistics can: Highlight patterns not evident from the original dataset.

Table of Contents


What are "statistics"...

...and what can they do for you?

So what are "statistics"? The word has various connotations, not all of them favourable. The world is an uncertain place and statistics are a way of making sense of things. You could think of statistics in two main ways:

  • As a way of describing a complex situation in a more simple fashion.
  • As a way of making decisions about a complex situation.

In the first case you are able to simplify a complex situation and make it more understandable. This is essentially summarizing data. It is an important stage in data analysis, especially when coupled with visual methods of summary (graphs and charts). Data summary becomes especially important when you are presenting or sharing your work.

The second case is about adding some kind of value to your uncertainty about the data – for example, how certain are you that two samples are really different? Is there a link between two variables? Most classic hypothesis tests are designed to give you a "decision point" – if you end up one side of the point you cannot be certain about the differences or links in your data. If you end up the other side of the point you can say with a level of certainty that your samples are different, or that there is a link between variables (or whatever it is the test is looking at).

Some kinds of statistical test are not classical hypothesis tests but nevertheless allow you to make decisions that you could not do using the raw data. In most cases these kinds of analysis bring out patterns that were not evident in the original dataset. You can look at the patterns and make decisions based on what you see.

So what can statistics do for you?

  • Help you summarize a complex situation more clearly.
  • Help you to make a decision about patterns in your data.
  • Help you to spot patterns in your data that were not evident originally.

Other articles on these pages will show you how to summarize, analyze and present your data. This is a work in progress so watch this space...


<= Data Analysis Home| Table of Contents | Summarizing data =>

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