Type I Error
-occurs if one rejects hypothesis when it it is true.

Example: Situation A - the medication might not significantly change the pulse rate off all the users in the population, but it might change the rate by chance of the subjects in the sample.  The researcher will reject the null hypothesis when it is really true, thus committing a Type 1 error.

Type II Error
-occurs if one does not reject the null hypothesis when it is false.

Example: Situation A - The medication might not change the pulse rate of the subjects of the sample, but when it is given to the general population, it might cause a significant increase or decrease in the pulse rate of the users.  The researcher, on the bases of the data obtained from the sample, will not reject the null hypothesis,  thus committing a Type II error.

A statistical test can be two-tailed or one tailed.

Types of Tests
1. Two-tailed test - When the alternate hypothesis contains the "not equal to" symbol.
2. Right-tailed test - When the alternate hypothesis contains the "greater than" symbol.
3. Left-tailed test - When the alternate hypothesis contains the "less than" symbol.

G.K. Elio