Testing of Hypothesis

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MCQs Chi-Square Association

This post is about MCQs on the Chi-Square Association.
The relationship/ Dependency between the attributes is called association and the measure of degrees of relationship between the attributes is called the coefficient of association. The Chi-Square Statistic is used to test the association between the attributes. The Chi-Square Association is defined as

$$\chi^2 = \sum \frac{(of_i – ef_i)^2}{ef_i}\sim \chi^2_{v},$$

where $v$ denotes the degrees of freedom

The following is the MCQs Chi-Square Association Test

MCQs about Association between the attributes.

1. Two attributes $A$ and $B$ are said to be independent if

 
 
 
 

2. Two attributes $A$ and $B$ are said to be positively associated if

 
 
 
 

3. If for a contingency table $df=12$ and number of rows is 4 then the number of columns will be

 
 
 
 

4. Association is a measure of the strength of the relationship between

 
 
 
 

5. For a $2\times 2$ contingency table, the degrees of freedom is

 
 
 
 

6. If $AB<\frac{(A)(B)}{N}$ then the association between two attributes $A$ and $B$ is

 
 
 
 

7. If $\chi^2=5.8$ and $d.f.=1$, we make the following decision

 
 
 
 

8. Eye color of 100 men is an example of

 
 
 
 

9. For a $r \times c$ contingency table, the Chi-Square test has d.f.?

 
 
 
 

10. The parameter of Chi-Square distribution is

 
 
 
 

11. For a $3\times 3$ contingency table, the degrees of freedom is

 
 
 
 

12. A characteristic that varies in quality from one individual t0 another is called

 
 
 
 

13. For a $4\times 5$ contingency table, there are

 
 
 
 

14. The range of $\chi^2$ is

 
 
 
 

15. The value of $\chi^2$-square distribution cannot be

 
 
 
 

16. The number of parameters in Chi-Square distribution is

 
 
 
 

17. In Chi-Square association, presence of attribute is denoted by

 
 
 
 

18. The process of dividing the objects into two mutually exclusive classes is called

 
 
 
 

Attributes are said to be independent if there is no association between them. Independence means the presence or absence of one attribute does not affect the other. The association is positive if the observed frequency of attributes is greater than the expected frequency and negative association or disassociation (negative association) is if the observed frequency is less than the expected frequency.

MCQs Chi-Square Association

Perform another Non-Parametric Test: MCQs Non-Parametric