Hypotheses are statements made about a population parameter that can be tested using sample data. They consist of a null hypothesis and an alternative hypothesis, which are mutually exclusive.
congrats on reading the definition of hypotheses. now let's actually learn it.
Hypotheses are always formulated before any data is collected or analyzed.
The null hypothesis (H0) typically represents no effect or no difference, and it is the statement being tested.
The alternative hypothesis (H1 or Ha) represents what you aim to support and indicates the presence of an effect or difference.
Hypothesis testing involves determining whether there is enough evidence in the sample to reject the null hypothesis in favor of the alternative hypothesis.
P-values and significance levels (alpha) are used to decide whether to reject the null hypothesis; if p-value ≤ alpha, reject H0.
Review Questions
What is the primary purpose of formulating a null hypothesis?
How do you decide when to reject the null hypothesis?
What does it mean if your p-value is greater than your significance level?
Related terms
Null Hypothesis: A statement asserting that there is no effect, difference, or relationship in the population; denoted as H0.
The statement that contradicts the null hypothesis by suggesting that there is an effect, difference, or relationship; denoted as H1 or Ha.
P-value: The probability of obtaining test results at least as extreme as the results actually observed, under the assumption that the null hypothesis is true.