Formulae, Flow Charts, and Tables

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QMS202

Business Statistics II

Formulae, Flow Charts, and Tables

Hypothesis Testing Steps

Two Types of Errors in Hypothesis Testing

Type I Error
Rejecting the null hypothesis when is actually true. / Type II Error
Failing to rejecting the null hypothesis when is actually false.

The Relationship between Conclusions and States of Nature.

Actual Situation

H0 True / H0 False

StatisticalDecision

/ Fail to reject H0 / Correct
Decision / Type II error
P(Type II)=β
Reject H0 / Type I error
P(Type I)=a / Correct
Decision

Writing Conclusions

Regardless of whether your original claim as a null or alternative hypothesis your conclusion should be “weak” if you conclude that H0 is better than H1 since your test was based on that assumption.

ie: is not significantly greater than (note this is just a negation of a strong alternative.)

If the sample implies H1 is better than H0 then the conclusion can be strong.

ie: is significantly greater than (note this is a strong version of the alternative.)