The following tables provide the critical value for *q*(*k, df, α*) for *α* = .10, .05 and .01 and values of *k* up to 20. Following these tables, we provide additional tables for *α* =.05, .025, .01, .005 and .001 and values of *k* up to 40, but with less granularity for higher values of *df*. See Unplanned Comparisons for ANOVA for more details.

**First group of tables**

**Alpha = 0.10**

**Alpha = 0.01**

**Alpha = 0.05**

**Alpha = 0.005**

Can you please tell me what the Q statistic is for alpha 0.05, df 21 and k 3? The numbers are so small I’m not sure I am reading them correctly.

Actually, is there a place where I can download these with greater resolution so that I can read all the numbers?

Sonja, if you download the Excel workbook with all the examples in this website, you will also find the table of Q statistics. Just go to http://www.real-statistics.com/free-download/real-statistics-examples-workbook/ for the free download. Charles

Sonja, it is 3.565. Charles

This question is regarding to one of the components of Tukey’s HSD procedure which is studentised range statistic i.e.q(k, df, α). Here I have k=9, df=441 and α=0.05.So in order to find q, I need to refer the critical values table and look for k=9 and df=441. But all the tables I get have values of df till 120 or 240 and then infinity. Since i am looking for df=441 which row of df should I use: 240 or Infinity? Hope my conveyance of the question is clear to you. Please help. Thanks

Sarthak,

After 240 you should use infinity. In the next release of the software you will be able to enter df = 441, but there will only be a small difference between that value and the value for infinity.

Charles

hello

Can you please tell me what the Q statistic is for two way anova (25×2), alpha 0.05, and df 200 ? Thx

I don’t know of a q statistic for two-way Anova. The q statistic is used in various Anova follow-up tests (e.g. Tukey HSD). These are described elsewhere on the website, but they apply to one-way as well as two-way Anova, although perhaps you are referring to some test that I am not familiar with.. For more information see http://www.real-statistics.com/one-way-analysis-of-variance-anova/unplanned-comparisons/ and http://www.real-statistics.com/two-way-anova/contrasts-two-factor-anova/.

Charles

Can anyone please tell me what the Q statistic is for alpha 0.05, df 75 and k 23? I have not found it in any reference table.

These are outside the range of values found in the table. You can use the Real Statistics Resource Pack’s

QINVfunction to find the approximate value. The formula =QINV(0.05,23,75) gives the value 5.306308907. More details can be found at http://www.real-statistics.com/students-t-distribution/studentized-range-distribution/.Charles

how can i get df 45, i can only see 40 and then 60. thanks

You have to interpolate. E.g. if the table value for 40 is .2 and the table value for 60 is .4 then the value for 45 would be .25.

Alternatively you can use the QCRIT or QINV functions provided in the Real Statistics Resource Pack which carry out this work for you. See the webpage http://www.real-statistics.com/students-t-distribution/studentized-range-distribution/.

Charles

how found Second group of tables 0.05 k=40

thanks

This comes from reference [Ha] on the Bibliography webpage of the Real Statistics website.

Charles

Second group of q tables 0.01 k=40

thanks

This comes from reference [Ha] on the Bibliography webpage of the Real Statistics website.

Charles

Can someone please tell me what the Q statistic is for alpha=0.05, df=156 and k=4? I can’t find it in the reference table.

Sarah,

You would need to interpolate between the table values for df = 120 and df = 240. Q-crit for df = 120 is 3.685 and the Q-crit for df = 240 id 3.659. A linear interpolation would give the value 3.6772, which can be calculated using the Real Statistics formula =QCRIT(4,156,0.05,2).

The Real Statistics formula =QINV(0.05,4,156,2), which does not use the table, will usually give a more accurate answer, which in this case is 3.6726.

Charles

thanks a lot prof. i can finish my task about this :).