Statking

There are two types of ERROR that we will dealing during conducting hypothesis testing; TYPE I ERROR: The probability of rejecting the Ho when Ho is TRUE. TYPE II ERROR: The probability of accepting the Ho when Ha is TRUE. TYPE I ERROR is serious form of error thus, it is denoted by alpha and is commonly referred as the SIGNIFICANCE LEVEL. TYPE II ERROR is usually denoted by beta where 1-beta is the POWER OF THE TEST. POWER OF THE TEST is the probability of rightly rejecting Ho when it is FALSE. In order words, we are RIGHT on deciding to accept Ha as our decision. There are some factors need to be considered when looking into the power of the test; When the significance level or a is made smaller, then the power will be decreases. In condition where the standard deviation of individual observation increases, the power will be decreases. By increasing sample size, then the power will be increasing too. The power of the test will be increases if the alternative me

When we are conducting hypothesis testing, there will be four possible outcomes can occur: i.                We accept Ho, and Ho is in fact TRUE ii.               We accept Ho, and Ha is in fact TRUE iii.             We reject Ho, and Ho is in fact TRUE iv.              We reject Ho, and Ha is in fact TRUE In practice, it is impossible to prove the Ho (null hypothesis) is TRUE. Therefore, if we ACCEPT Ho, then we have actually FAILED to reject Ho! If Ho is TRUE and Ho is accepted, or if Ha is TRUE and Ho is rejected, then the correct decision has been made. Therefore, if we accidently rejecting Ho when Ho is actually TRUE, or if Ha is TRUE but now Ho is accepted, then an ERROR has been made. So now the two concepts of ERROR will then be introduced and need to be treated differently.