 If you are studying relationship between two variables or comparing two groups then you will test a hypothesis. In any research we have two hypothesis. One is research hypothesis and null hypothesis. Research hypothesis or alternate hypothesis says there is a relationship between two variables whereas null hypothesis says there is no relationship. The null hypothesis may be actually true or false. In your study you may accept that null hypothesis or reject which will derive four situations. In the null hypothesis is false and you reject it correctly then it is called as true negative. When the null hypothesis is true and you accept it that is called as true positive. When the null hypothesis is true and you reject it that is called as false positive. When the null hypothesis is false and you accept it that is called as false negative. So this false positive is called as alpha error or type 1 error. False negative is called as beta error or type 2 error. The inverse of this beta error is called as power of the study. The probability of committing alpha error is called as p value. Then the p value is less than 0.05, you call it as statistically significant.