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LimitedInfo
Level II

How do I do a Chi-Square test with duplicate rows of data?

I'm trying to do a Chi-Square test. I have multiple rows of data for individual restaurants. I only need one row per restaurant because the type of cuisine for each restaurant is constant between months. Should I reformat the data or is there a way to do the Chi-Square test with the data in the picture? 

 

(I wouldn't have to worrry about this problem if I had the same number of months per restaurant, however I do not.)

 

capture6.png

1 ACCEPTED SOLUTION

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Re: How do I do a Chi-Square test with duplicate rows of data?

This is a quick way with a summary table.

 

  1. Select Tables > Summary.
  2. Select Ticket, Cuisine, and Sig, then click Group.
  3. Click OK.

Now use the new summary table,

  1. Select Analyze > Fit Y by X
  2. Select Cuisine and click Y
  3. Select Sig and click X
  4. Click OK.

Your mosaic plot and contingency table should depict the conditional probabilities and the Chi square test should be at the bottom.

Learn it once, use it forever!

View solution in original post

3 REPLIES 3
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Re: How do I do a Chi-Square test with duplicate rows of data?

I test of what, in terms of the variables you show in the picture of the data table?

Learn it once, use it forever!
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LimitedInfo
Level II

Re: How do I do a Chi-Square test with duplicate rows of data?

A test of whether there is a significant difference in the frequency of cuisine type between Sig of 0 restaurants and Sig of 1 restaurants.

Highlighted

Re: How do I do a Chi-Square test with duplicate rows of data?

This is a quick way with a summary table.

 

  1. Select Tables > Summary.
  2. Select Ticket, Cuisine, and Sig, then click Group.
  3. Click OK.

Now use the new summary table,

  1. Select Analyze > Fit Y by X
  2. Select Cuisine and click Y
  3. Select Sig and click X
  4. Click OK.

Your mosaic plot and contingency table should depict the conditional probabilities and the Chi square test should be at the bottom.

Learn it once, use it forever!

View solution in original post

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