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What does the p value have to be for you to reject it in chi square conclusions?
Weirdogirl716
The p value for rejecting an hypothesis is more closely related to the type of errors and their consequences. The p value is not determined by the chi square - or any other - test but by the impact of the decision made on the basis of the test.
The two types of errors to be considered are:
what is the probability that you reject the null hypothesis when it is actually true (type I error), and
what is the probability that you accept the null hypothesis when, in fact, it is false (type I error)..
Reducing one type of error increase the other and there is a balance to be struck between the two. This balance will be influenced by the costs associated with making the wrong error. In real life, the effects (costs/benefits) of decisions are very asymmetrical.
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Does use of chi-square demand a random sample?
Well, sort of. The Chi-square distribution is the sampling distribution of the variance. It is derived based on a random sample. A perfect random sample is where any value in the sample has any relationship to any other value. I would say that if the Chi-square distribution is used, then every effort should be made to make the sample as random as possible. I would also say that if the Chi-square distribution is used and the sample is clearly not a random sample, then improper conclusions may be reached.
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 a Chi Square table used for?
A Chi-square table is used in a Chi-square test in statistics. A Chi-square test is used to compare observed data with the expected hypothetical data.
What does a high chi square value mean?
It means the data deviated a large amount from the model or from what you thought.
Why use chi-square?
the Chi Square distribution is a mathematical distribution that is used directly or indirectly in many tests of significance. The most common use of the chi square distribution is to test differences among proportions
If the chi-square is very large what does it mean?
The null hypothesis in a chi-square goodness-of-fit test states that the sample of observed frequencies supports the claim about the expected frequencies. So the bigger the the calculated chi-square value is, the more likely the sample does not conform the expected frequencies, and therefore you would reject the null hypothesis. So the short answer is, REJECT!
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.
Does use of chi-square demand a random sample?
Well, sort of. The Chi-square distribution is the sampling distribution of the variance. It is derived based on a random sample. A perfect random sample is where any value in the sample has any relationship to any other value. I would say that if the Chi-square distribution is used, then every effort should be made to make the sample as random as possible. I would also say that if the Chi-square distribution is used and the sample is clearly not a random sample, then improper conclusions may be reached.
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.
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.
Chi-square distribution assumes only positive value?
1
How do you determine critical value in Chi Square?
How, i want to know too
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.
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.
What is the value of chi square test positive or negative?
There must be some value otherwise nobody would do them. On that basis, the value must be positive.
