A directional hypothesis is a precise, educated guess at the direction of an outcome, such as a declared difference in variable sets or an increase or decline.
Directional Hypothesis
In statistical testing, a directional hypothesis is a kind of hypothesis that predicts the expected relationship between two variables in a specific direction.
For example, a directional hypothesis may propose that, in a study examining how sleep deprivation affects cognitive performance, cognitive performance (the dependent variable) decreases as sleep deprivation (the independent variable) increases. Such a hypothesis shows a directional relationship that is clear and indicates a specific increase or decrease.
Another noteworthy example of a directional hypothesis is global warming. One possible hypothesis put out by a researcher is that rising carbon dioxide levels correspond with rising global temperatures. In this case, the hypothesis expresses an upward trend for both variables quite clearly.
In any given situation, a directional hypothesis must be supported by substantial evidence. For example, there is strong scientific evidence supporting the relationship between CO2 and global temperature, not just speculation or a random guess.
An assumption regarding a population parameter is known as a statistical hypothesis. For instance, we can estimate that a man’s average height in the United States is 75 inches.
The population parameter is the actual mean height of males in the United States, while the statistical hypothesis is the height assumption.
We take a random sample from the population and run a hypothesis test on the sample data to see if a statistical hypothesis about a population parameter is correct.
Null and Alternative Hypothesis
A null and alternative hypothesis are always reported when conducting a hypothesis test:
Null hypothesis (H0): It states that the sample data is entirely due to chance.
Alternative Hypothesis (HA): There is a non-random cause influencing the sample data.
Directional Hypothesis and a Non-directional Hypothesis
A hypothesis test can include either a directional hypothesis or a non-directional hypothesis.
Directional hypothesis: The less than(“<“) or greater than(“>”) sign is present in the alternative hypothesis. This means that we are investigating if there is a positive or negative effect.
Non-directional hypothesis: The not equal (“≠”) sign appears in the alternative hypothesis. This suggests that we are testing the presence of an effect without specifying its direction.
It should be noted that tests with directional hypothesis are also known as “one-tailed” tests, while non-directional hypothesis tests are known as “two-tailed” tests.
11 Examples of Directional Hypothesis
1. Sugar Intake and Oral Health
In the field of dental health, a common assertion could be that an increase in sugar consumption (independent variable) is associated with a decrease in dental health (dependent variable).
This is grounded in the understanding that sugar plays a significant role in tooth decay, and higher consumption of sugary foods or beverages contributes to a deterioration in dental health, primarily due to the increased likelihood of cavities.
2. Heart Health and Exercise
Based on research findings, it is suggested that an increase in regular physical exercise (independent variable) is associated with a decrease in the risk of heart disease (dependent variable). The directional hypothesis proposes that individuals who engage in routine workouts are expected to have lower odds of developing heart-related disorders.
3. Eye Strain and Screen Time
A widely held hypothesis suggests that an increase in screen time (independent variable) is associated with a higher likelihood of experiencing eye strain (dependent variable). This hypothesis is rooted in the notion that extended use of digital screens, such as computers, tablets, or mobile phones, can lead to eye discomfort or fatigue, contributing to symptoms of eye strain.
4. Screen Time and the Quality of Sleep
Another example of a directional hypothesis is evident in the relationship between the independent variable, screen time (particularly before bedtime), and the dependent variable, sleep quality. This hypothesis suggests that with an increase in screen time before bed, there is an expected decrease in sleep quality.
5. Sleep Quality and Traffic Noise
In the field of urban planning research, a common assumption is that an increase in traffic noise (independent variable) is linked to a decrease in sleep quality (dependent variable). Elevated noise levels, especially during the night, are believed to cause disturbances in sleep, resulting in a decline in sleep quality.
6. Employee Turnover And Job Satisfaction:
In organizational behavior research, it is commonly proposed that as job satisfaction (independent variable) increases, the rate of employee turnover (dependent variable) decreases. This directional hypothesis underscores the idea that higher job satisfaction is linked to a lower rate of employees leaving the company.
7. Water Intake And Kidney Health
In the context of health, a hypothesis suggests that an increase in water consumption (independent variable) is associated with a decreased risk of kidney stones (dependent variable). The hypothesis implies that increase in water intake may lower the risk of kidney stones by diluting substances that contribute to stone formation.
8. Healthy Eating and Weight
It is believed that healthy eating, as the independent variable, positively impacts body weight, the dependent variable. For instance, the hypothesis could posit that an increase in the consumption of healthy foods leads to a decrease in an individual’s body weight.
9. Skin Health And Sun Exposure:
The relationship between sun exposure (independent variable) and skin health (dependent variable) supports a clear hypothesis stating that an increase in sun exposure is associated with an increased risk of skin damage or skin cancer.
10. Academic Performance and Study Hours
An often-assessed relationship in academic research proposes that an increase in study hours (independent variable) correlates with improved academic performance (dependent variable). The hypothesis suggests a positive relationship, indicating that dedicating more time to studying is likely to result in better academic achievements.
11. Exercise and Stress Levels
In the field of mental health, a common proposal suggests that an increase in physical activity (independent variable) is linked to a decrease in stress levels (dependent variable). Regular exercise is recognized for triggering the release of endorphins, the body’s natural mood enhancers, contributing to stress relief.
Other articles
Please read through some of our other articles with examples and explanations if you’d like to learn more about research methodology.
Citation Styles
- APA Reference Page
- MLA Citations
- Chicago Style Format
- “et al.” in APA, MLA, and Chicago Style
- Do All References in a Reference List Need to Be Cited in Text?
Comparision
- Basic and Applied Research
- Cross-Sectional vs Longitudinal Studies
- Survey vs Questionnaire
- Open Ended vs Closed Ended Questions
- Experimental and Non-Experimental Research
- Inductive vs Deductive Approach
- Null and Alternative Hypothesis
- Reliability vs Validity
- Population vs Sample
- Conceptual Framework and Theoretical Framework
- Bibliography and Reference
- Stratified vs Cluster Sampling
- Sampling Error vs Sampling Bias
- Internal Validity vs External Validity
- Full-Scale, Laboratory-Scale and Pilot-Scale Studies
- Plagiarism and Paraphrasing
- Research Methodology Vs. Research Method
- Mediator and Moderator
- Type I vs Type II error
- Descriptive and Inferential Statistics
- Microsoft Excel and SPSS
- Parametric and Non-Parametric Test
Comparision
- Independent vs. Dependent Variable – MIM Learnovate
- Research Article and Research Paper
- Proposition and Hypothesis
- Principal Component Analysis and Partial Least Squares
- Academic Research vs Industry Research
- Clinical Research vs Lab Research
- Research Lab and Hospital Lab
- Thesis Statement and Research Question
- Quantitative Researchers vs. Quantitative Traders
- Premise, Hypothesis and Supposition
- Survey Vs Experiment
- Hypothesis and Theory
- Independent vs. Dependent Variable
- APA vs. MLA
- Ghost Authorship vs. Gift Authorship
Research
- Research Methods
- Quantitative Research
- Qualitative Research
- Case Study Research
- Survey Research
- Conclusive Research
- Descriptive Research
- Cross-Sectional Research
- Theoretical Framework
- Conceptual Framework
- Triangulation
- Grounded Theory
- Quasi-Experimental Design
- Mixed Method
- Correlational Research
- Randomized Controlled Trial
- Stratified Sampling
- Ethnography
- Ghost Authorship
- Secondary Data Collection
- Primary Data Collection
- Ex-Post-Facto
Research
- Table of Contents
- Dissertation Topic
- Synopsis
- Thesis Statement
- Research Proposal
- Research Questions
- Research Problem
- Research Gap
- Types of Research Gaps
- Variables
- Operationalization of Variables
- Literature Review
- Research Hypothesis
- Questionnaire
- Abstract
- Validity
- Reliability
- Measurement of Scale
- Sampling Techniques
- Acknowledgements
Statistics
- PLS-SEM model
- Principal Components Analysis
- Multivariate Analysis
- Friedman Test
- Chi-Square Test (Χ²)
- T-test
- SPSS
- Effect Size
- Critical Values in Statistics
- Statistical Analysis
- Calculate the Sample Size for Randomized Controlled Trials
- Covariate in Statistics
- Avoid Common Mistakes in Statistics
- Standard Deviation
- Derivatives & Formulas
- Build a PLS-SEM model using AMOS
- Principal Components Analysis using SPSS
- Statistical Tools
- Type I vs Type II error
- Descriptive and Inferential Statistics
- Microsoft Excel and SPSS
- One-tailed and Two-tailed Test
- Parametric and Non-Parametric Test