For the t ratio, the larger the difference between the sample mean and the population mean (other things being equal), the greater the likelihood of
A) rejecting Ho
B) failing to reject Ho
C) sampling error
D) committing the standard error

Question

Quizplus · Accepted Answer

The t ratio measures the difference between the sample mean and the population mean in terms of the standard error of the mean. When the difference between the sample mean and the population mean is large, the t ratio will be large as well, increasing the likelihood of rejecting Ho. This is because a large difference implies that the sample is less likely to have occurred by chance alone, and more likely to be a true difference between the sample and population.

For the T Ratio, the Larger the Difference Between the Sample