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Data analysis: hypothesis testing
Data analysis: hypothesis testing

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3.2 Directional hypotheses

Directional hypotheses, also known as one-tailed hypotheses, predict the direction of a relationship or difference between variables. These hypotheses use signs like less than or equal to (≤) and greater than (>) in their statements.

For example, a directional hypothesis might propose: “A marketing campaign will increase product sales”. This hypothesis specifies the expected outcome (an increase in sales) before data collection begins.

Directional hypotheses offer several advantages in research:

  1. They provide more precise and focused predictions than non-directional hypotheses.
  2. They are often preferred in scientific research due to their specificity.
  3. In business management, they can help design studies to examine the effectiveness of strategies, such as marketing campaigns.

To test a directional hypothesis, decision-makers use a one-tailed test. This statistical test aims to determine if the data supports the anticipated direction of the relationship or difference.

Let us reconsider the study time example:

  • H0: µ ≤ 15 hours of studies
  • H1: µ > 15 hours of studies

Here, the null hypothesis (H0) states that the population mean (µ) is less than or equal to 15 hours of studies. The alternative hypothesis (H1) predicts that the population mean is greater than 15 hours of studies.