hypothesis testing

A tutorial on lower tail test on hypothesis of population proportion

A tutorial on two-tailed test on hypothesis of population mean with unknown variance.

A tutorial on upper tail test on hypothesis of population mean with unknown variance.

A tutorial on lower tail test on hypothesis of population mean with unknown variance.

A tutorial on two-tailed test on hypothesis of population mean with known variance.

A tutorial on upper tail test on hypothesis of population mean with known variance.

A tutorial on lower tail test on hypothesis of population mean with known variance.

Researchers retain or reject hypothesis based on measurements of observed samples. The decision is often based on a statistical mechanism called hypothesis testing. A type I error is the mishap of falsely rejecting a null hypothesis when the null hypothesis is true. The probability of committing a type I error is called the significance level of the hypothesis testing, and is denoted by the Greek letter α .