type I and type II errors

Question 1

type I

Answer 1

The incorrect rejection of a true null hypothesis (a false positive).
Occurs when the null hypothesis is rejected and the alternative accepted, claiming to have found a significant difference or correlation when in fact one does not exist.
More likely if the significance level is too lenient rather than 5%.

Question 2

type II

Answer 2

The failure to reject a false null hypothesis ( false negative).
The null hypothesis is accepted but it should have been rejected, and the alternative accepted instead, claiming to have not found a significant difference or correlation when in fact this does exist.
More likely if the significance level is too tough as potentially significant values may be missed.

Question 3

overcome

Answer 3

One way to reduce the possibility of making either error is to increase sample size, as if there are more people there will be more results so the chance of making error when interpreting results is less.