Here are the essential concepts you must grasp in order to answer the question correctly.
Hypothesis Testing
Hypothesis testing is a statistical method used to make decisions about a population based on sample data. It involves formulating a null hypothesis (H0) and an alternative hypothesis (H1), then using sample data to determine whether to reject H0. The outcome helps in assessing whether there is enough evidence to support a specific claim about a population parameter.
Recommended video:
One-Tailed vs. Two-Tailed Tests
In hypothesis testing, a one-tailed test evaluates the direction of an effect, either testing if a parameter is greater than or less than a certain value. A two-tailed test, on the other hand, assesses whether a parameter is significantly different from a specified value in either direction. The choice between these tests depends on the research question and the nature of the hypothesis.
Recommended video:
Difference in Proportions: Hypothesis Tests
Standard Deviation and Population Parameters
Standard deviation is a measure of the amount of variation or dispersion in a set of values. In the context of hypothesis testing, it is often used to describe the variability of a population parameter. When a claim is made about the standard deviation, such as it being 'no more than' a certain value, it sets the stage for testing whether the actual standard deviation exceeds this threshold, influencing the type of test used.
Recommended video:
Calculating Standard Deviation