The difference between the sample mean and the population mean is called the sampling error.
举一反三
- The difference between the sample mean and the population mean is called the: A: population deviation. B: population standard deviation. C: standard error of the mean. D: sampling error.
- The difference between the sample size and the population size is called the sampling error.
- From a population of 500 elements, a sample of 225 elements is selected. It is known that the variance of the population is 900. The standard error of the mean is approximately
- A researcher is interested in testing to determine if the mean of population one is greater than the mean of population two. The null hypothesis is that there is no difference in the population means (i.e. the difference is zero). The alternative hypothesis is that there is a difference (i.e. the difference is not equal to zero). He randomly selects a sample of 9 items from population one resulting in a mean of 14.3 and a standard deviation of 3.4. He randomly selects a sample of 14 items from population two resulting in a mean of 11.8 and a standard deviation 2.9. He is using an alpha value of .10 to conduct this test. Assuming that the populations are normally distributed, the critical t-value from the table is _______.
- If a paired comparison test of mean differences supports rejecting the null hypothesis, then the: A: independence of the samples is statistically significant. B: standard error of the mean differences is low relative to the sample mean difference. C: difference in means is not statistically significant.