*Updated April 2013*

*Author
Dr. Barbara Smith
Research Analyst, NICHCY
Approx. 5 pages when printed*

When you read a research article, you’re likely to run across descriptions of how the researchers analyzed the data they collected. There may be many terms about their statistical methods that leave you wondering, *huh?* In order to understand what the authors are trying to say, you need to understand their lingo. This * Research Basic *can help you do just that.

Below are links to resources that will help you understand more about the statistical tests and terms mentioned in research documents. These resources run the gamut of complexity–you’ll find everything from an entire online introductory statistics course to glossaries defining individual statistical terms. Hopefully, these resources will be helpful in illuminating your reading of research.

- Probability & statistics for the average person
- Statistical inference defined
- Introduction to “stats” in plain language
- Are you a visual learner?
- Glossaries

#### Probability & Statistics for the Average Person

What are “statistics” anyway?

http://paleo.cortland.edu/class/stats/documents/01_Introduction.pdf * *

What is “probability” anyway?

From Life 123.

http://www.life123.com/parenting/education/probability-statistics/what-is-probability.shtml

The 12 essential concepts of statistics and why to use them.

http://www.graphpad.com/guides/prism/6/statistics/index.htm?stat_the_essential_concepts_of_stat.htm

Want an indepth intro to probability?

Here’s the full-text of the book* Introduction to Probability**.*

http://www.dartmouth.edu/~chance/teaching_aids/books_articles/probability_book/book.html

#### Statistical Inference Defined

According to the encyclopedia.

http://www.encyclopedia.com/topic/Inferential_statistics.aspx#2-1O88:statisticalinference-full

From the Research Knowledge Database, Cornell.

www.socialresearchmethods.net/kb/statinf.htm

Overview of descriptive and inferential methods.

http://infinity.cos.edu/faculty/woodbury/stats/tutorial/Data_Descr_Infer.htm

So how come a survey of 1,600 people can tell me what 250 million are thinking?

http://www.robertniles.com/stats/margin.shtml

#### Introduction to “Stats” in Plain Language

Little handbook of statistical practice.

A step-by step tutorial from Tufts.

http://www.tufts.edu/~gdallal/LHSP.HTM

Those scary statistics.

From Craig Hospital in Colorado.

http://tinyurl.com/c2aqv2s

Statistics every writer should know.

From journalist Robert Niles.

www.robertniles.com/stats/

How to read a paper: Statistics for the non-statistician.

I: Different types of data need different statistical tests.

From the British Medical Journal.

http://bmj.bmjjournals.com/cgi/content/full/315/7104/364

How to read a paper: Statistics for the non-statistician.

II: “Significant” relations and their pitfalls.

From the British Medical Journal.

http://bmj.bmjjournals.com/cgi/content/full/315/7105/422

Pitfalls of data analysis (or how to avoid lies and damned lies).

From material covered in a workshop at the Third International Applied Statistics in Industry Conference in Dallas, TX, June 5-7, 1995.

http://my.execpc.com/~helberg/pitfalls/

#### Are You a Visual Learner?

Against all odds: Inside statistics.

This links to a video series from the Annenberg/CPB projects consisting of 26 half-hour video programs, emphasizing how to “do” statistics.

www.learner.org/resources/series65.html?pop=yes&vodid=44107&pid=140

Lesson on the introduction to probability.

From Math Goodies.

www.mathgoodies.com/lessons/vol6/intro_probability.html

Online math manipulatives for data analysis and probabilities.

From the National Library of Virtual Manipulatives, at Utah State University.

http://nlvm.usu.edu/en/nav/category_g_3_t_5.html

BERRIES statistics page.

http://huizen.dds.nl/~berrie/

Virtual laboratories in probability and statistics.

From University of Alabama, Huntsville.

www.math.uah.edu/stat/

Demonstration of group differences.

From Rice University.

www.ruf.rice.edu/~lane/stat_sim/gdexpl.html

#### Glossaries

Baffled by a word or a concept that seems like statistics or probability? Look in these glossaries. You are likely to find the definition inside one of ‘em.

From Colorado State University.

http://writing.colostate.edu/guides/research/stats/

From the University of Glasgow.

www.stats.gla.ac.uk/steps/glossary/index.html

From Berkeley.

www.stat.berkeley.edu/~stark/SticiGui/Text/gloss.htm

From University of Vermont.

http://www.uvm.edu/~dhowell/methods8/Glossary/Glossary.html

From Statistical Education through Problem Solving (STEPS)

http://www.stats.gla.ac.uk/steps/glossary/index.html

You can use this page in combination with the other offerings in our collection of pages designed to make sense of research. At the moment, we offer these basic introductions:

- Research 101 | What makes for good research?
- Research 102: Adding Up the Evidence | How do you combine the findings of multiple research studies?
- Making Sense of Statistics in Research (you’re here!)
- Weighing Info for Its Worth | Is this research well done?
- Special Education Research: Where to Start? | How to begin finding and applying research.
- What Works: Can We Say? | Where can I find information on evidence-based practices?
- Research-Based Resources on Specific Disabilities | A starting place for research-based information on disabilities.