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MadViolinist
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How can I determine what the smallest value of a χ2 statistic must be to reject the null hypothesis at α = 5%, for a distribution with 9 degrees of freedom? Thanks in advance.
MadViolinist said:How can I determine what the smallest value of a χ2 statistic must be to reject the null hypothesis at α = 5%, for a distribution with 9 degrees of freedom? Thanks in advance.
Inverse chi square is a statistical test used to determine whether there is a significant relationship between two variables. It involves calculating the inverse of the chi square statistic, which is used to measure the difference between the observed and expected values in a contingency table.
The inverse chi square statistic is calculated by taking the sum of the squared differences between the observed and expected values, divided by the expected values. This result is then compared to a critical value from a chi square distribution table to determine if the null hypothesis should be rejected.
This means that there is a 5% chance of obtaining the observed result if the null hypothesis is true. The 9DF refers to the degrees of freedom, which is the number of categories or variables in the contingency table minus 1. If the calculated inverse chi square value is higher than the critical value at α=5%, then the null hypothesis is rejected.
The significance level, denoted as α, is the probability of rejecting the null hypothesis when it is actually true. In inverse chi square, a significance level of 5% is commonly used, meaning that there is a 5% chance of rejecting the null hypothesis even if it is true.
Inverse chi square assumes that the sample is representative of the population, the variables are categorical, and the expected values in the contingency table are greater than 5. It also assumes that the observations are independent and that there is no significant relationship between the variables.