Six differences between the null hypothesis and the research hypothesis

Sample Solution

     

Null Hypothesis vs. Research Hypothesis: Key Differences

Here's a breakdown of the six key differences between the null hypothesis (H0) and the research hypothesis (H1):

1. Directionality:

   • Null Hypothesis (H0): States no difference or relationship between variables. It's the default assumption that the research aims to disprove. (e.g., There is no difference in student performance between online and in-person learning)
   • Research Hypothesis (H1): Proposes a specific direction for a difference or relationship between variables. (e.g., Students will perform better in online learning environments compared to in-person classes)

Full Answer Section

   

1. Burden of Proof:
   • Null Hypothesis (H0): Assumed to be true unless evidence proves otherwise. (Easier to disprove than prove)
   • Research Hypothesis (H1): Needs to be supported by the research data. (The researcher actively tries to prove it)
2. Complexity:
   • Null Hypothesis (H0): Generally simpler and more concise.
   • Research Hypothesis (H1): Can be more complex and specific, depending on the research question.
3. Example Focus:
   • Null Hypothesis (H0): Focuses on "no change" or "no difference."
   • Research Hypothesis (H1): Focuses on the predicted change or relationship.
4. Decision Making:
   • Null Hypothesis (H0): If we fail to reject H0, it suggests there isn't enough evidence for a relationship between variables, but it doesn't necessarily mean there isn't one.
   • Research Hypothesis (H1): If we reject H0 and support H1, it suggests evidence for a relationship, but it doesn't guarantee a causal link.
5. Wording:
   • Null Hypothesis (H0): Often uses phrases like "no difference," "no effect," or "no association."
   • Research Hypothesis (H1): Often uses phrases like "is greater than," "is less than," or "is correlated with."

Research Hypothesis in Google News Articles While searching Google News for specific uses of research hypotheses can be unreliable due to the ever-changing nature of news articles, here's a general example of how they might be used: Headline: "Study suggests link between social media use and increased anxiety in teenagers" Here, the implicit research hypothesis would be: Social media use is positively correlated with anxiety in teenagers (i.e., as social media use increases, so does anxiety). The study would then aim to collect data and test this hypothesis to see if there's a statistically significant relationship between the two variables.