A hypothesis is an evidenced-based explanation of observed processes that must be tested supported by experimental evidence the process by which phenomena are explained a scientific theory used to explain observations
Hypothesis test:
The process of making inference regarding the population based on the sample is called statistical inference. Mainly, statistical inference is classified as estimation of parameters and testing of hypothesis. Testing of hypothesis is a process whereby the analyst tests an assumption regarding population parameters. It indicates that whether or not the primary hypothesis is true. The process begins with a claim about population parameters and testing whether or not the data support the claim or not.
The aim of the hypothesis test is that to check whether there is enough statistical evidence to support a certain belief about population parameter. The result obtained from hypothesis test have theoretical basis. Those theories can be used to build complex theories.
Hypothesis:
Hypothesis is an assumption about the parameter of the population which will be made on the limited evidence as the start value to proceed for further investigation, and the assumption may or may not be true.
In testing the hypothesis is of two types. The two types are:
- Null hypothesis (H0)
- Alternative hypothesis (H1)
Null and alternative hypotheses:
Null hypothesis:
Null hypothesis is a statement which is tested for statistical significance in the test. The decision criterion indicates whether the null hypothesis will be rejected or not in the favor of alternative hypothesis. In other words it can be said that, the null hypothesis is a statement which indicates the relationship between statistical measurements, distributions or categories. More often, null hypothesis states no significance relationship between variables or populations. But, null does not indicate “0” all the time.
Alternative hypothesis:
Alternative hypothesis is contradictory statement of the null hypothesis.
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