If your chi square test has a probability of 0.05 or less it is likely, but not certain, that your hypothesis is not correct.
1. It is a probability distribution function and so the area under the curve must be 1.
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.
A hypothesis is the first step in running a statistical test (t-test, chi-square test, etc.) A NULL HYPOTHESIS is the probability that what you are testing does NOT occur. An ALTERNATIVE HYPOTHESIS is the probability that what you are testing DOES occur.
A probability sampling method is any method of sampling that utilizes some form of random selection. See: http://www.socialresearchmethods.net/kb/sampprob.php The simple random sample is an assumption when the chi-square distribution is used as the sampling distribution of the calculated variance (s^2). The second assumption is that the particular variable is normally distributed. It may not be in the sample, but it is assumed that the variable is normally distributed in the population. For a very good discussion of the chi-square test, see: http://en.wikipedia.org/wiki/Pearson%27s_chi-square_test
It means the data deviated a large amount from the model or from what you thought.
You could calculate it by integrating the chi-square probability distribution function but you are likely to be much better off using a table in a book or on the web.
The Chi-square probability distribution is a probability distribution that describes the distribution of the sum of squared standard normal random variables. It is often used in hypothesis testing and is characterized by its degrees of freedom. The shape of the distribution depends on the degrees of freedom parameter, with larger degrees of freedom resulting in a more symmetric and bell-shaped distribution.
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.
1. It is a probability distribution function and so the area under the curve must be 1.
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.
Because Chi-squares are used to analyze and compare observed frequencies to expected frequencies, they can help trace the probability of an offspring receiving a certain phenotype and genotype from their parents.
A hypothesis is the first step in running a statistical test (t-test, chi-square test, etc.) A NULL HYPOTHESIS is the probability that what you are testing does NOT occur. An ALTERNATIVE HYPOTHESIS is the probability that what you are testing DOES occur.
A probability sampling method is any method of sampling that utilizes some form of random selection. See: http://www.socialresearchmethods.net/kb/sampprob.php The simple random sample is an assumption when the chi-square distribution is used as the sampling distribution of the calculated variance (s^2). The second assumption is that the particular variable is normally distributed. It may not be in the sample, but it is assumed that the variable is normally distributed in the population. For a very good discussion of the chi-square test, see: http://en.wikipedia.org/wiki/Pearson%27s_chi-square_test
chi-square http://en.wikipedia.org/wiki/Chi-square_test
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.
It means the data deviated a large amount from the model or from what you thought.
Fisher's exact probability test, chi-square test for independence, Kolmogorov-Smirnov test, Spearman's Rank correlation and many, many more.