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How to do a Chi-square test when you only have proportions and denominators

March 18th, 2011 by

by Annette Gerritsen, Ph.D.

In an earlier article I discussed how to do a cross-tabulation in SPSS. But what if you do not have a data set with the values of the two variables of interest?

For example, if you do a critical appraisal of a published study and only have proportions and denominators.

In this article it will be demonstrated how SPSS can come up with a cross table and do a Chi-square test in both situations. And you will see that the results are exactly the same.

‘Normal’ dataset

If you want to test if there is an association between two nominal variables, you do a Chi-square test.

In SPSS you just indicate that one variable (the independent one) should come in the row, (more…)


On Puzzles, Statistics, Algorithms, and Understanding

July 1st, 2009 by

My 8 year-old son got a Rubik’s cube in his Christmas stocking this year.

I had gotten one as a birthday present when I was about 10.  It was at the height of the craze and I was so excited.

I distinctly remember bursting into tears when I discovered that my little sister sneaked playing with it, and messed it up the day I got it.  I knew I would mess it up to an unsolvable point soon myself, but I was still relishing the fun of creating patterns in the 9 squares, then getting it back to 6 sides of single-colored perfection.  (I loved patterns even then). (more…)


Observed Values less than 5 in a Chi Square test – No biggie.

June 19th, 2009 by

I was recently asked this question about Chi-square tests.  This question comes up a lot, so I thought I’d share my answer.

I have to compare two sets of categorical data in a 2×4 table. I cannot run the chi-square test because most of the cells contain values less than five and a couple of them contain values of 0. Is there any other test that I could use that overcomes the limitations of chi-square?

And here is my answer: (more…)


Outliers: To Drop or Not to Drop

September 17th, 2008 by

Should you drop outliers? Outliers are one of those statistical issues that everyone knows about, but most people aren’t sure how to deal with.  Most parametric statistics, like means, standard deviations, and correlations, and every statistic based on these, are highly sensitive to outliers.

And since the assumptions of common statistical procedures, like linear regression and ANOVA, are also based on these statistics, outliers can really mess up your analysis.

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Despite all this, as much as you’d like to, it is NOT acceptable to

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