Res342 Dq Question and Answers Week 1

DQ1.1

Define the null and alternate hypothesis. Explain how you tell the difference.

Null hypothesis refers to a theory that has been put forward, either because it is believed to be true or because it is to be used as a basis for argument, but has not been proved.

The null hypothesis is stated in terms of “no difference” or equal and is always the simpler hypothesis and generally believed to be true.

Alternative hypothesis is a statement of what a statistical hypothesis test is set up to establish.

The alternative hypothesis can be stated in terms of simple inequality and represents the result that the experiment would like to show.

DQ1.2

How do you determine if a problem is a one-tailed or two-tailed test? How do you determine where the region of rejection is on a one-tailed test?

A one-tailed test is directional. One example of this would be a hypothesis is the mean weight of all hockey pucks are X. The alternative hypothesis could be A. X. It specifies a direction. This test is designed so the tolerance is either the upper or lower part of a distribution.

A two-tailed test does not specify a direction. Same example if you want to know whether the average dimensions are either X or not. This does not have a specific direction. This test is designed so that the tolerance uses both the upper and lower part of a distribution

DQ1.3

What is the level of significance and how is this used in determining the critical value?

The level of significance or significance level of a statistical hypothesis test is a fixed probability of wrongly rejecting the null hypothesis, if it is in fact true.

The critical value for any hypothesis test depends on the significance level at which the test is carried out, and whether the test is one-sided or two-sided. The hypothesis test procedure is adjusted so that there is a guaranteed 'low' probability of rejecting the null hypothesis wrongly.

What is the English interpretation of the critical...