Null Hypothesis and Alternative Hypothesis Examples
Let’s envision a scenario where a researcher aims to examine the impact of a new medication on reducing blood pressure among patients. In this context:
Null Hypothesis (H0): “The new medication does not produce a significant effect in reducing blood pressure levels among patients.”
Alternative Hypothesis (H1 or Ha): “The new medication yields a significant effect in reducing blood pressure levels among patients.”
The null hypothesis implies that any observed alterations in blood pressure subsequent to the medication’s administration are a result of random fluctuations rather than a consequence of the medication itself. Conversely, the alternative hypothesis contends that the medication does indeed generate a meaningful alteration in blood pressure levels, distinct from what might naturally occur or by random chance.
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Null Hypothesis
Null Hypothesis, often denoted as H0, is a foundational concept in statistical hypothesis testing. It represents an assumption that no significant difference, effect, or relationship exists between variables within a population. It serves as a baseline assumption, positing no observed change or effect occurring. The null is the truth or falsity of an idea in analysis.
In this article, we will discuss the null hypothesis in detail, along with some solved examples and questions on the null hypothesis.
Table of Content
- What is Null Hypothesis?
- Null Hypothesis Symbol
- Formula of Null Hypothesis
- Types of Null Hypothesis
- Null Hypothesis Examples
- Principle of Null Hypothesis
- How do you Find Null Hypothesis?
- Null Hypothesis in Statistics
- Null Hypothesis and Alternative Hypothesis
- Null Hypothesis and Alternative Hypothesis Examples
- Null Hypothesis – Practice Problems
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