RESEARCH METHODOLOGY

Detailed explanation-1: -The probability of committing a type I error (rejecting the null hypothesis when it is actually true) is called (alpha) the other name for this is the level of statistical significance.

Detailed explanation-2: -Type 1 errors have a probability of “” correlated to the level of confidence that you set. A test with a 95% confidence level means that there is a 5% chance of getting a type 1 error.

Detailed explanation-3: -Higher values of make it easier to reject the null hypothesis, so choosing higher values for can reduce the probability of a Type II error. The consequence here is that if the null hypothesis is true, increasing makes it more likely that we commit a Type I error (rejecting a true null hypothesis).

Detailed explanation-4: -If the null hypothesis is true, we have a 1- probability that we will make the correct decision and accept it. We call that probability (1-) our confidence level. Confidence and significance sum to one because rejecting and accepting a null hypothesis are the only possible choices when the null hypothesis is true.