You will be given a
number of hypothesis tests. In each case a null and alternative hypothesis will
be suggested, where m refers to
the population mean, and a level of test. You will then be given the population
standard deviation, s, and the
mean and size of a sample from that population. You must decide if the
hypothesis test should have a non-significant or significant result based on
that sample mean. A table of critical values is provided but you will have to
work out the test statistic yourself, using:
Critical
values
One-tailed
One-tailed
Two-tailed
10%
1.282
-1.282
±1.645
5%
1.645
-1.645
±1.96
2.5%
1.96
-1.96
±2.241
1%
2.326
-2.326
±2.575
Summary
In any
hypothesis test we are testing the evidence to see if it is sufficient to
reject the null hypothesis. A significant result implies:
the null hypothesis is
rejected
the alternative hypothesis is accepted
as true
there is a chance that this conclusion
is wrong and that the null hypothsis is in fact true. This is called a Type
I error
the probability of a Type I error is
given by the level of the test
A non-significant result implies:
the null hypothesis is not
rejected
there is a chance that this conclusion
is wrong and that the null hypothsis is in fact false. This is called a Type
II error