8.1 practice: Ho/H1 practice

The null hypothesis (H0) is a statement that there is no effect or no difference, and it serves as a starting point for statistical testing.

The alternative hypothesis (H1) is a statement that indicates the presence of an effect or a difference, opposing the null hypothesis.

This means that the average weight of the group is hypothesized to be 89 lbs (H0), while the alternative suggests it could be different from 89 lbs (H1).

No, the null and alternative hypotheses cannot be the same; they must represent opposing statements.

The level of significance (often denoted as alpha, α) is the threshold for determining whether to reject the null hypothesis, commonly set at 0.05 or 0.01.

A one-tailed test is a hypothesis test that evaluates the direction of the effect, either greater than or less than a certain value.

A two-tailed test is a hypothesis test that evaluates whether a parameter is significantly different from a specified value in either direction.

This represents the null hypothesis stating that the proportion of a certain characteristic in the population is 50%.

The purpose of hypothesis testing is to make inferences about population parameters based on sample data.

Rejecting the null hypothesis suggests that there is sufficient evidence to support the alternative hypothesis.