Question

In: Statistics and Probability

In a study to determine whether an association exists between maternal rubella and congenital cataracts, samples...

In a study to determine whether an association exists between maternal rubella and congenital cataracts, samples of 20 children with congenital cataracts and 25 children without congenital cataracts were selected. The mother of each child was asked whether she had rubella while carrying the child. The data are given below. Assume that all z-based methods are valid.

RUBELLA

CATARACTS

Frequency
Row Pct

1_YES

2_NO

Total

1_YES

14
58.33

10
41.67

24

2_NO

6
28.57

15
71.43

21

Total

20

25

45

Statistic

DF

Value

Prob

Chi-Square

1

4.0179

0.0450

Likelihood Ratio Chi-Square

1

4.0979

0.0429

Continuity Adj. Chi-Square

1

2.9029

0.0884

Mantel-Haenszel Chi-Square

1

3.9286

0.0475

Phi Coefficient

0.2988

Contingency Coefficient

0.2863

Cramer's V

0.2988

Column 1 Risk Estimates

Risk

ASE

95%
Confidence Limits

Exact 95%
Confidence Limits

Row 1

0.5833

0.1006

0.3861

0.7806

0.3664

0.7789

Row 2

0.2857

0.0986

0.0925

0.4789

0.1128

0.5218

Total

0.4444

0.0741

0.2993

0.5896

0.2964

0.6000

Difference

0.2976

0.1409

0.0215

0.5737

Difference is (Row 1 - Row 2)

What are the null and alternative hypotheses? Be sure to define any symbols that you use.

Solutions

Expert Solution

The Chi-Square test of independence is used to determine if there is a significant relationship between two nominal (categorical) variables. The frequency of each category for one nominal variable is compared across the categories of the second nominal variable.

First we have to calculate the expected value of the two nominal variables. We can calculate the expected value of the two nominal variables by using this formula:


Where

= expected value

= Sum of the ith column

= Sum of the kth row

N = total number

After calculating the expected value, we will apply the following formula to calculate the value of the Chi-Square test of Independence:


= Chi-Square test of Independence
= Observed value of two nominal variables
= Expected value of two nominal variables

Null hypothesis: Assumes that there is no association between maternal rubella and congenital cataracts

Alternative hypothesis: Assumes that there is an association between maternal rubella and congenital cataracts


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