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(This blog site does not support formatting therefore sometimes there could be errors in the post.)

An Assumption of outcome of statistical testing is called as hypothesis. e.g.: Sample is as per required norms according to the given parameter.

Parameter is criterion on which sample is accepted or rejected. Parameter could be mean, standard deviation etc.

Estimator is a parameter which is used to estimate the value of the population parameter. An example of an estimator is the sample mean, which is an estimator of the population mean.

Test statistics
Value of the test parameter is known as test statistics.

Null Hypothesis.
It is initial assumption about an outcome before testing. It is denoted by Ho. e.g.: Average strength is as per required norms, which means population mean is same as sample mean. It is written as Ho: μ =

Alternative Hypothesis
Another assumption if null hypothesis is proved to be false. It is denoted by H1 e.g.: Average strength is less than required norms.

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