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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.
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What is the difference between a chi-square and t-distribution?
Chi-square is a distribution used to analyze the standard deviation of two samples. A t-distribution on the other hand, is used to compare the means of two samples.
How do pronounce chi-square test?
The chi-square test is pronounced "keye-skwair" test.
What can a chi square never be?
Negative?
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.
The properties of chi-square distribution?
it has reproductive property
What is the difference between odds ratio and Chi square?
none
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
What is the difference between correlation coefficient and chi square?
correlation is used when there is metric data and chi square is used when there is categorized data. sayan chakrabortty
What is the difference between the Chi and the Chi Nano?
the color and temperature.
What is the difference between a chi-square and t-distribution?
Chi-square is a distribution used to analyze the standard deviation of two samples. A t-distribution on the other hand, is used to compare the means of two samples.
WHAT IS THE Difference between A t test and chi square?
t test is used when- a) variables are studied b)the size of sample is a small one.(n<30) chi square test is studied when a) attributes are studied
Is chi square a test of relationship or test of difference?
yes it is
Difference between chi square and Anova?
ANOVA is a statistical test of whether the means of several groups are all equal. The chi-square test of association is used to test the null hypothesis that there is no association between two nominal scale variables. It does not require a distinction between independent and dependent variables.
What is the difference of chi-square and t test?
They are applicable in different circumstances.
Importance of chi-square test?
It enables us to tell the difference between observed and expected frequencies objectively as it is practically impossible to tell the difference just by looking at the data.
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.
Is chi-square test examines extent of errors between variables?
No.
