Hundreds, if not more.
For a given set of data, you calculate a statistic.
Select a null and alternative hypotheses. These may include the kind of distribution as well as parameters about its location and spread (mean and variance).
Determine the probability distribution function (pdf) of that statistic when the null hypothesis is true.
Decide on the significance level that you wish to use.
Determine values of the statistic such that the probability of observing a value at least as extreme is less than the significance level.
You have a test.
There are almost no constraints on the distribution that you select at the second stage and so, provided you can determine the pdf of the test statistic under your assumptions, there are no limits to the number of tests you can devise.
Answer this question...how many paramatic trdy
Parametric statistical tests assume that your data are normally distributed (follow a classic bell-shaped curve). An example of a parametric statistical test is the Student's t-test.Non-parametric tests make no such assumption. An example of a non-parametric statistical test is the Sign Test.
A pie chart is never, ever, appropriate for statistical tests. It can be a useful way of illustrating results but it has no usefulness in testing.
Dose response tests are used, which are a kind of statistical tests.
* Always when the assumptions for the specific test (as there are many parametric tests) are fulfilled. * When you want to say something about a statistical parameter.
Answer this question...how many paramatic trdy
Parametric statistical tests assume that your data are normally distributed (follow a classic bell-shaped curve). An example of a parametric statistical test is the Student's t-test.Non-parametric tests make no such assumption. An example of a non-parametric statistical test is the Sign Test.
statistical tests. <><><><><><>
statistical tests
A pie chart is never, ever, appropriate for statistical tests. It can be a useful way of illustrating results but it has no usefulness in testing.
Dose response tests are used, which are a kind of statistical tests.
statistical tests. <><><><><><>
statistical tests. <><><><><><>
statistical tests. <><><><><><>
Parametric tests draw conclusions based on the data that are drawn from populations that have certain distributions. Non-parametric tests draw fewer conclusions about the data set. The majority of elementary statistical methods are parametric because they generally have larger statistical outcomes. However, if the necessary conclusions cannot be drawn about a data set, non-parametric tests are then used.
* Always when the assumptions for the specific test (as there are many parametric tests) are fulfilled. * When you want to say something about a statistical parameter.
statistical tests