making the null and alternative hypothesis, labelling the claim.
step 1
we use normalcdf for this method and distribution.
what function do we use for the p-value method for the z distribution?
the conclusion statement is based on these two factors:
whether the claim is in the null or alternative hypothesis and whether we reject or fail to reject the null hypothesis.
pulling the relevant numbers from the context of the problem and plug them into either the z or t formula.
step 2 - test statistic
we use invNorm for this method and distribution.
what function do we use for the traditional method for the z distribution?
there is sufficient evidence to support the claim that...
we reject the null with claim in the alternative.
comparing the test statistic to the critical value.
step 3 - traditional method
we use invT for this method and distribution.
what function do we use for the traditional method for the t distribution?
there is not sufficient evidence to reject the claim that...
we fail to reject the null with claim in the null.
comparing the p-value to the alpha level.
step 3 - p-value method
we use tcdf for this method and distribution.
what function do we use for the p-vlaue method for the t distribution?
there is not sufficient evidence to support the claim that...
we fail to reject the null with claim in the alternative.
making inferences based on the results of the test.
step 4 - conclusion
when the test statistic is in the shaded region or when the p-value is less than alpha.
when do we reject the null hypothesis?
there is sufficient evidence to reject the claim that...
we reject the null with claim in the null.