Chi-Square and Expected number

  • Thread starter vipertongn
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In summary, the expected number in the chi square equation is calculated by finding the total number of observations and multiplying it by the percentage of the occurrence for each group. This value represents what would be expected if there were no differences between the groups being studied. Specific examples were given to illustrate this concept.
  • #1
vipertongn
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Ok, I am confused as to how we determine the expected number in the chi square equation: sum of (observed-expected)^2/expected. Can someone explain to me the concept of this. How do you find the expected number? Give examples too please,

My guess is that like the expected is like the the total progeny, and the ratio they are closest too, like for example if the ratio they are most similar to is 1:1:1:1. You add 1+1+1+1=4 so it's 1/4 and you multiply that by the total number to get the expected number.

Or for example if the ratio looks to be close to 9:3:3:1. you multiply the highest ratio number by the total (which is 16) so 9/16.
 
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  • #2
It's easier to see with specific examples. Usually the expected number is what you'd get if there were no difference between the various groups or classes in the study.
 
  • #3
Also, with a chi-square test you are normally given groups of objects, and then a percentage of the odds of something happening to each group are.

For example: say you have groups 1, 2, 3, and 4. Each group has 10 people in it, making your n = 40. Now, the odds for a group to do something is as follows; 1 - 25%, 2- 12%, 3 - 50%, 4 - 13%.

To get the expected value, you take n times the percentage the occurrence will happen to each group (as a decimal). So in this case, the expected value for Group 1 would be (40 x .25). Group 2 - (40 x .12), Group 3 - (40 x .50), and Group 4 - (40 x .13).

Sorry if this was kind of confusing, but i hope it helps!
 

What is the purpose of a Chi-Square test?

The Chi-Square test is a statistical tool used to determine whether there is a significant association between two categorical variables. It helps to determine if the observed data differs significantly from the expected data.

How is the Chi-Square test calculated?

The Chi-Square test is calculated by comparing the observed frequencies of each category with the expected frequencies. This is done by squaring the difference between the observed and expected values, dividing by the expected value, and then summing up all of these values. The resulting value is then compared to a critical value from a Chi-Square distribution with degrees of freedom equal to the number of categories minus one.

What does the expected number refer to in a Chi-Square test?

The expected number in a Chi-Square test refers to the number of observations that would be expected in each category if there was no relationship between the variables being studied. It is calculated by taking the total number of observations and dividing it by the number of categories.

What does it mean if the Chi-Square test results in a p-value less than 0.05?

If the Chi-Square test results in a p-value less than 0.05, it means that the observed data differs significantly from the expected data. This indicates that there is a significant association between the two variables being studied.

What are the assumptions of the Chi-Square test?

The Chi-Square test assumes that the observations are independent, the expected frequencies in each category are at least 5, and the total sample size is large enough. Violation of these assumptions can affect the accuracy of the results.

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