Chi-square test - I do not understand the results :-&

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The discussion centers on confusion regarding the results of chi-square tests applied to the same dataset, which yielded both significant and non-significant differences. The inconsistency arises from different statistical methods and potential corrections, such as Yates correction, affecting the outcomes. The user is investigating differences in opinions about extracurricular activities based on gender and school achievement, with results indicating a near-significant difference at the 95% confidence level. It is emphasized that the tests do not conclusively prove the absence of differences, only that the evidence is insufficient to confirm them. Overall, the interpretation of chi-square results can vary significantly based on the specific test applied and its parameters.
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In one case I get the results as a significant difference in the other with the same dana, the difference is not significant.


Data sample
A B
I 5 8
II 4 28

http://imageshack.com/a/img542/467/o61k.jpg

Same data and got significant difference

http://imageshack.com/a/img200/7366/y1le.jpg

Where I'm wrong? :frown:
 
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The images don't say what kind of chi-square test is being done.

Try using various options for chi-square tests on the page http://graphpad.com/quickcalcs/contingency1/. Different statistical tests on the same data may give different conclusions.
 
The second one says it does not apply a Yates correction. It's results are just barely significant at the 95% level. The first test may apply the correction and the result might become insignificant or it may use a different level than 95%.
 
Thank you, here is little more data; I used chi-square (χ2) test to investigate the statistical significance of differences of opinion about the students offered the choice of extra-curricular activities with regard to gender and school achievement, ie the most recently completed assessment of students in the English language.

Can I (completed by SPSS) results interpreted as: no statistically significant differences based on gender.?

http://imageshack.com/a/img837/3372/0wv6.jpg
 
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The test tried to prove that there was a difference with 95% confidence. It barely succeeded by Pearson chi-squared and barely failed by the other statistics tests. You should NOT conclude that it proved there was no difference. It was not trying to prove that.
 
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