Answer:
Step-by-step explanation:
Hypothesis test is a method for derive information of a big population from data obtain from samples. So it is not a determinant procedure (in the sense that the results are exact ) is an evaluation dealing with probabilities, and parameters of a given distribution.
In most cases the test implies decision based on the comparison of two homologous elements, one you compute from data of the sample, and the other one is settled down according to the level of confidence you want.
Therefore you have:
-Opposite hypothesis
Null hypothesis H₀ is the reference hypotes is what somebody says about population ( companies about their products, label on boxes of food and so on)
Alternative hypothesis Hₐ is always the opposite that means if;
H₀ = something
we in the alternative hypothesis could settled down Hₐ ≠ something from that point on, the investigation consist in showing which one is true
-Elements you compute from data of the sample (normally call proof statistician )
- Confidence interval (zone where with high probability we will find values of a random variable)
-Critical values the fundamental element that is associated with the interval of confidence, and determine rejected and acceptance zone (for null hypothesis)
From comparison emerge expressions such as
= , ≠ , ≤ , ≥ , < . > and of course the elements (that is) a > b or wahtever is the comparison
So what is a two tail test, a test in which we will evaluate data from sample and look if something is bigger or smaller
One test tail (to the left )should be investigate in cases where the question is the calculated parameter is smaller than "certain value" (critical value) and one test tail (to the right) is for evaluation of parameters bigger than again "critical value"
