## What is a Hypothesis Test?

A hypothesis test is a statistical technique used to determine if there is enough evidence in a sample of data to infer a certain conclusion about a population parameter. It is used to test a hypothesis about a population parameter, such as the mean or proportion, by using sample data.

### Steps of a Hypothesis Test

The steps of a hypothesis test are as follows:

- State the null hypothesis and the alternative hypothesis.
- Determine the level of significance, or alpha.
- Collect the data and calculate the test statistic.
- Compare the test statistic to the critical value and make a decision.

### Null Hypothesis

The null hypothesis is a statement of no difference or no effect. It is usually denoted by H0. The null hypothesis states that the population parameter is equal to the hypothesized value.

### Alternative Hypothesis

The alternative hypothesis is a statement of difference or effect. It is usually denoted by H1. The alternative hypothesis states that the population parameter is not equal to the hypothesized value.

### Level of Significance

The level of significance is the probability of rejecting the null hypothesis when it is true. It is usually denoted by alpha (α). The most commonly used level of significance is 0.05, which means that there is a 5% chance of rejecting the null hypothesis when it is true.

### Test Statistic

The test statistic is a measure of the strength of the evidence in the sample data. It is calculated using the sample data and is compared to the critical value to determine whether or not to reject the null hypothesis.

### Conclusion

A hypothesis test is a statistical technique used to determine if there is enough evidence in a sample of data to infer a certain conclusion about a population parameter. It is used to test a hypothesis about a population parameter, such as the mean or proportion, by using sample data. The steps of a hypothesis test include stating the null and alternative hypotheses, determining the level of significance, calculating the test statistic, and comparing the test statistic to the critical value to make a decision.