This section will calculate the.05 and.01 critical values for the Studentized range statistic Q. To proceed, enter the number of groups in the analysis (k) and the number of degrees of freedom, and then click «Calculate». Note that the value of k must be between 3 and 10, inclusive. Deciding whether a chi-square test statistic is large enough to indicate a statistically significant difference isn’t as easy it seems. It would be nice if we could say a chi-square test statistic 10 means a difference, but unfortunately that isn’t the case.
![Test Test](/uploads/1/2/4/6/124696447/862000026.jpg)
A test statistic is a random variable that is calculated from sample data and used in a hypothesis test. You can use test statistics to determine whether to reject the null hypothesis. The test statistic compares your data with what is expected under the null hypothesis. The test statistic is used to calculate the p-value.A test statistic measures the degree of agreement between a sample of data and the null hypothesis.
Its observed value changes randomly from one random sample to a different sample. A test statistic contains information about the data that is relevant for deciding whether to reject the null hypothesis. The sampling distribution of the test statistic under the null hypothesis is called the null distribution. When the data show strong evidence against the assumptions in the null hypothesis, the magnitude of the test statistic becomes too large or too small depending on the alternative hypothesis. This causes the test's p-value to become small enough to reject the null hypothesis.For example, the test statistic for a Z-test is the Z-statistic, which has the standard normal distribution under the null hypothesis. Suppose you perform a two-tailed Z-test with an α of 0.05, and obtain a Z-statistic (also called a Z-value) based on your data of 2.5. This Z-value corresponds to a p-value of 0.0124.
![Test statistic calculator x2 Test statistic calculator x2](http://www.statpac.com/images/calculator-scr1.jpg)
Because this p-value is less than α, you declare statistical significance and reject the null hypothesis.Different hypothesis tests use different test statistics based on the probability model assumed in the null hypothesis. Common tests and their test statistics include.
When you gather data or perform an experiment, you usually want to demonstrate that there's a connection between a change in one parameter and a change in another. For example, spaghetti dinners may lead to more trips to the dry cleaners. Statistical tools help you figure out if the data you collect is meaningful. Specifically, the T-test can help you decide if there's a significant difference between two sets of data. For example, one group of data can be trips to the dry cleaner for people who don't eat spaghetti, and the other can be dry cleaner visits for people who eat spaghetti.
Two different T-tests work in different circumstances, first for completely independent data, second for data groups that are connected in some way.