Falsepositive or Type I error
The falsepositive or type I error occurs when the researcher rejects the null hypothesis even though it is true. It means that despite the null hypothesis is true, the research fails to accept it. Such a problem arises when a researcher sets the value of significance level higher.
For example:
Ho: There is no relationship between gender and mark obtained
H1: Males score higher marks in comparison to females.
Suppose that the pvalue is estimated as 0.12.
then,
Sig level  Accept or Reject Ho  Remark 
0.01  Accept  
0.05  Accept  
0.1  Accept  
0.2  Reject  Falsepositive 
The falsenegative or type II error occurs when the researcher fails to reject the null hypothesis even though it is false. It means that despite the null hypothesis is false, the research fails to reject it. Such a problem arises when a researcher sets the value of significance level lower.
For example:
Ho: There is no relationship between gender and mark obtained
H1: Females score higher marks in comparison to males.
Suppose that the pvalue is estimated at 0.015

If a researcher sets the tabulated pvalue at 1 percent, the researcher encounters a type II error.
What is the possible solution?
The researcher shall set the tabulated pvalue at 1 percent, 5 percent, and 10 percent, and compare it with the calculated pvalue. In general practice, the calculated pvalue less than 10 percent is preferable for rejection of the null hypothesis. But it depends upon the discretion of the researcher to set the rejection significance level.
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