Null and Alternative Hypothesis

The reason null and alternative hypotheses are two opposite roads that lead to the same place.
Definition:The null and alternative hypotheses are opposites and mutually exclusive.
- The null is either rejected or it is not, only if the null is rejected then we can proceed with the alternative.
Researchers can start with either the null or the alternative.
Which to start depends on the point of view of the researcher, the context of the problem.
Null Hypotheses:This is accepted as true, let's test it.
Alternative Hypotheses:This might be true, let's test it, if not, the truth is something else.
Symbols
H(nought)- Null means nothing new or different assumptions.
H(a)- Alternative is simply the other option when null is rejected.

Null and Alternative Hypothesis Summary:

All statistics conclusions are made in reference to the null hypothesis.
As researchers, we either reject the null hypothesis or fail to reject the null hypothesis; we do not accept the null.
If we reject null hypothesis, then we conclude the data supports the alternative hypothesis.
If we fail to reject the null hypothesis, it does not mean we have proven the null hypothesis is true.Because failure to reject the null does not equate to "proof" about its truth.

RatnaKumari26 commented 2 years ago

Type 1 = A Type I error means rejecting the null hypothesis when it’s actually true.
- Ex-False Positive,The test result says you have coronavirus, but you actually don’t.
Type 2 = A Type II error means not rejecting the null hypothesis when it’s actually false.
- False Negative,The test result says you don’t have coronavirus, but you actually do.