Statistic 202, Chp 8-10

Is the statement below true or​ false? The mean of the sampling distribution of p-hat is p.

True.

Point estimate

A sample statistic used to estimate the exact value of a population parameter.

Explain the difference between statistical significance and practical significance. A. Statistical significance means that the sample statistic is not likely to come from the population whose parameter is stated in the null hypothesis. Practical significance refers to whether the difference between the sample statistic and the parameter stated in the null hypothesis is large enough to be considered important in an application. B.Statistical significance refers to the type of hypothesis test needed to analyze a​ population, with some tests being more important than Z tests. Practical significance refers to how difficult a desired hypothesis test is to perform in an​ application, with some tests being easier to perform than others. C.Statistical significance refers to how an unusual event is unlikely to actually appear in a real world​ application, such as every entry in a sample of size 50 having the same value. Practical significance refers to how an unusual event is likely to actually appear in a real world​ application, such as a rejection of a null hypothesis using data that looks feasible. D.Statistical significance means that the hypothesis test being performed is useful for building theoretical foundations for other statistical work. Practical significance means that the particular application of the hypothesis test is of great importance to the real world.

A. Statistical significance means that the sample statistic is not likely to come from the population whose parameter is stated in the null hypothesis. Practical significance refers to whether the difference between the sample statistic and the parameter stated in the null hypothesis is large enough to be considered important in an application.

The standard deviation of the sampling distribution of x̅ ​​, is called the​

standard error of the mean.

Central limit theorem

mean of the sample would be equal to the mean of the population. -should always be larger than or equal to 30 if possible. -when the sample size is large, the sampling distribution is approximately normal;