Degrees of Freedom in Chi-square Test: n=Observed Values?

In summary, the degrees of freedom in the Chi-square test is equal to the number of trials minus one, and this applies even if the observed values are measuring the same variable. In the example with 2 trials of genetic crosses, the df is 1.
  • #1
zmike
139
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In the Chi-square test, my textbook says that degrees of freedom are the number of independent variables minus one so df = n - 1

does this mean that that n is equal to the number of observed values from the equation aka the number of times I've added together the numbers?

sum [(O-E)^2]/E

Is there an instance where it isn't equal to the number of observed values I have?

(there's an example in my book (but no answer) with an experiment with observed values of 2 trials of genetic crosses where observed in
trial 1 was 0.5
trial 2 was 0.3
but both of these values were measuring the same variable which was heterozygosity. The expected value is 0.8. Does this mean the df = 1? or is it 0 since there is only 1 independent variable?)

thanks!
 
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  • #2
df=n-1, n means number of the random variables, in this case n is the number of trials. df=n-1=2-1=1
 

1. What is the concept of degrees of freedom in a chi-square test?

Degrees of freedom in a chi-square test refer to the number of categories or groups in a dataset that are free to vary. In other words, it is the number of observations in a sample that can be varied without changing the overall results of the chi-square test.

2. How is the number of degrees of freedom determined in a chi-square test?

The number of degrees of freedom in a chi-square test is equal to the number of categories or groups in the dataset minus one. For example, if there are 5 categories in the dataset, the degrees of freedom would be 5-1=4.

3. Why is the concept of degrees of freedom important in a chi-square test?

Degrees of freedom play a crucial role in determining the significance of the chi-square test. The higher the degrees of freedom, the more accurate the test becomes. Additionally, it helps in determining the appropriate critical value for the test.

4. How does the number of observed values affect the degrees of freedom in a chi-square test?

The number of observed values has a direct impact on the degrees of freedom in a chi-square test. As the number of observed values increases, the degrees of freedom also increase, allowing for a more accurate test and a wider range of possible outcomes.

5. Can the degrees of freedom in a chi-square test ever be negative?

No, the degrees of freedom in a chi-square test can never be negative. It is a mathematical concept that represents the number of independent variables in a dataset, and therefore must always be a positive integer.

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