Correlation analysis of Nominal data with Chi-Square Test in Data Mining

Correlation analysis of Nominal data with Chi-Square Test in Data Mining

Chi-Square Test

This analysis can be done by chi-square test.Chi-square test is the test to analyze the correlation of nominal data.

Correlation VS Causality:

Correlation does not always tell us about causality.

Example:

  • The number of students passed in exam and number of car theft in a country is correlated with each other but maybe it does not mean that number of student passed effects car theft in a country.

But in some cases it may be;

  • The number of students passed in exam and number of students who live near to the university is correlated with each other and maybe a number of students who live near to the university can be a cause of the student result.
[quads id=2]
 Passed studentNot passed studentSum
Live near UniversityObserved=140

Expected = 180*330/1320

Expected =45

Observed=190

Expected = 1140*330/1320

Expected =285

330
Not live near UniversityObserved=40

Expected = 180*990/1320

Expected =135

Observed=950

Expected = 1140*990/1320

Expected =855

990
Sum140 + 40 = 180190 + 950 = 11401320

correlation analysis

Degrees of freedom:

DF = (r – 1) * (c – 1)

Level of significance:

.01.05.10

 

Fazal Rehman Shamil Click Here to Know More
Instructor, Researcher, Blogger, SEO Expert, Poet and Publisher of International Journal Of Software, Technology & Science ISSN : 2616 - 5325
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