CHI square independent test (small expected frequency)

In summary, the expected frequency for the age of 21-30, 31-36, and more than or equal to 37 for an operation is less than 5. Therefore, combining these numbers is necessary to achieve an expected frequency of 5 or more. The question is which numbers should be combined. The solution suggests combining the rows 21-30 and 31-36, or 31-36 and 37+, to fix the problem. As for combining less than 21 and 21-30, or 31-36 and more than 37, it is suggested to compute both options and see if one contradicts the decision of the other.
  • #1
somecelxis
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Homework Statement


the expected frequency for the age of (21-30, 31-36, more than or equal to 37) for operation is less than 5 , so combination of these numbers are required for the expected frequency to be more than or equal to 5 .
my question is which numbers should i combine?

would my ans be different?

Homework Equations

The Attempt at a Solution


in the solution, i combine the (21-30, 31-36, more than or equal to 37) for normal birth to get my Observed frequency = 34 and expected frequency = 38.37...

for operation, combine the (21-30, 31-36, more than or equal to 37) for normal birth to get my Observed frequency = 12 and expected frequency = 7.57...

can i combine less than( 21 and 21-30 ) , (31-36 , more than 37) ?[/B]
 

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  • #2
This may be a solution to your problem.

I'm not sure if this was your plan. I would think if you combine the the rows 21-30 and 31-36, or 31-36 and 37+, then that'd fix the problem.

For your second question, why don't you just compute both and see if one contradicts the decision of the other?
 

1. What is a chi square independent test?

A chi square independent test is a statistical test used to determine the relationship between two categorical variables. It is used to test whether there is a significant association between the two variables or if the association is due to chance.

2. When is a chi square independent test used?

A chi square independent test is used when analyzing data with two categorical variables and the expected frequency in each category is small (less than 5). It is commonly used in fields such as social sciences, psychology, and biology.

3. How is a chi square independent test calculated?

The chi square statistic is calculated by taking the sum of the squared differences between the observed and expected frequencies in each category, divided by the expected frequency in each category. This calculation results in a test statistic that can be compared to a critical value to determine if there is a significant relationship between the variables.

4. What is the null hypothesis in a chi square independent test?

The null hypothesis in a chi square independent test is that there is no significant relationship between the two variables being tested. In other words, any observed association between the variables is due to chance and not a true relationship.

5. What is the significance level in a chi square independent test?

The significance level in a chi square independent test is the probability of obtaining the observed results if the null hypothesis is true. It is typically set at 0.05 or 5%, meaning that if the p-value (probability value) is less than 0.05, the results are considered statistically significant and the null hypothesis can be rejected.

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