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Q: How do you determine critical value in Chi Square?
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What is the critical value of chi-square with a significant level of equals 0.05?

Critical values of a chi-square test depend on the degrees of freedom.


What happens to the crtitical value for a chi square test if the size of the sample is increased?

The size of the sample should not affect the critical value.


What is the chi square test used for?

The chi-squared test is used to compare the observed results with the expected results. If expected and observed values are equal then chi-squared will be equal to zero. If chi-squared is equal to zero or very small, then the expected and observed values are close. Calculating the chi-squared value allows one to determine if there is a statistical significance between the observed and expected values. The formula for chi-squared is: X^2 = sum((observed - expected)^2 / expected) Using the degrees of freedom, use a table to determine the critical value. If X^2 > critical value, then there is a statistically significant difference between the observed and expected values. If X^2 < critical value, there there is no statistically significant difference between the observed and expected values.


Can you get a negative chi square statistic?

The characteristics of the chi-square distribution are: A. The value of chi-square is never negative. B. The chi-square distribution is positively skewed. C. There is a family of chi-square distributions.


Find the critical value or values of x2 based on the given information?

how do you find the critical value for x squared when relating it to chi squares?


Is chi-square distribution symmetrical about mean value?

No.


What does the number that Chi-Square produces represent?

It is the value of a random variable which has a chi-square distribution with the appropriate number of degrees of freedom.


Chi-square distribution assumes only positive value?

1


What is difference between chi square and reduced chi square?

A reduced chi-square value, calculated after a nonlinear regression has been performed, is the is the Chi-Square value divided by the degrees of freedom (DOF). The degrees of freedom in this case is N-P, where N is the number of data points and P is the number of parameters in the fitting function that has been used. I have added a link, which explains better the advantages of calculating the reduced chi-square in assessing the goodness of fit of a non-linear regression equation. In fitting an equation to the data, it is possible to also "over fit", which is to account for small and random errors in the data, with additional parameters. The reduced chi-square value will increase (show a worse fit) if the addition of a parameter does not significantly improve the fit. You can also do a search on reduced chi-square value to better understand its importance.


Uses of chi-square test?

The chi-square test is used to analyze a contingency table consisting of rows and columns to determine if the observed cell frequencies differ significantly from the expected frequencies.


How does the difference between fe and fo influence the outcome of a chi-square test?

The larger the difference, the larger the value of chi-square and the greater the likelihood of rejecting the null hypothesis


How do you calculate a chi square using excel 2007?

For each category, you should have an observed value and an expected value. Calculate (O-E)2 / E for each cell. Add the values across the categories. That is your chi-square test statistic.