HYPOTHESIS
FORMULATION

Dr. Ajay Kumar Koli, PhD | SARA Institute of Data Science, India

Variable


A variable is a characteristic or attribute that can take on different values.

Independent Variables

The variable that is manipulated or controlled by the researcher to observe its effect on another variable.

  • IV is also called as predictor variable.

Dependent Variables

The variable that is measured or observed to assess the impact of the independent variable.

  • DV is also called as Effect or output or outcome variable.

Example

Example 1: Education Study

  • Independent Variable: Teaching method (traditional vs. interactive).
  • Dependent Variable: Student performance on a test.

Example

Example 2: Health Study

  • Independent Variable: Amount of daily exercise (30 mins, 60 mins, 90 mins).
  • Dependent Variable: Weight loss (in kilograms).

Example

Example 3: Marketing Study

  • Independent Variable: Type of advertisement (video, banner, text).
  • Dependent Variable: Number of clicks or purchases.

Practice

We’ll use data to demonstrate the relationship between independent and dependent variables. Examples are:

  1. Direct Relationship

  2. Inverse Relationship

  3. No-Relation Example

Hypothesis

A hypothesis is a testable statement or prediction about the relationship between two or more variables.

Types of Hypotheses

  • Null Hypothesis (\(H_0\)): The null hypothesis states that there is no effect, no difference, or no relationship between the variables being studied. It assumes that any observed differences are due to chance.

  • Alternative Hypothesis (\(H_a\) or \(H_1\)): The alternative hypothesis suggests that there is an effect or relationship between the variables. It is the hypothesis that is supported if the null hypothesis is rejected.

Formulate Hypotheses

📚 Education Scenario: Investigating whether a new teaching method improves student test scores compared to the traditional method.

  • Null Hypothesis (\(H_0\)):: The new teaching method has no effect on student test scores.

  • Alternative Hypothesis (\(H_a\) or \(H_1\)): The new teaching method affects student test scores.

  • Null Hypothesis (\(H_0\)):: The new teaching method does not improve student test scores.

  • Alternative Hypothesis (\(H_a\) or \(H_1\)): The new teaching method improves student test scores.

Key Points

  • Non-Directional Hypotheses are used when you are testing for any effect, regardless of the direction (e.g., an increase or decrease).

  • Directional Hypotheses are used when you have a specific prediction about the direction of the effect (e.g., an improvement or reduction).

Formulate Hypotheses

💉 Medicine Scenario: Evaluating whether Drug A lowers blood pressure more effectively than a placebo.

  • Null Hypothesis (\(H_0\)): Drug A has no effect on blood pressure compared to the placebo.

  • Alternative Hypothesis (\(H_a\) or \(H_1\)): Drug A affects blood pressure compared to the placebo.

  • Null Hypothesis (\(H_0\)): Drug A does not lower blood pressure more effectively than the placebo.

  • Alternative Hypothesis (\(H_a\) or \(H_1\)): Drug A lowers blood pressure more effectively than the placebo.

Formulate Hypotheses

🌱 Environment Scenario: Determining whether an area’s air quality index (AQI) changes after implementing stricter pollution regulations.

  • Null Hypothesis (\(H_0\)): Stricter pollution regulations have no effect on the AQI.

  • Alternative Hypothesis (\(H_a\) or \(H_1\)): Stricter pollution regulations affect the AQI.

  • Null Hypothesis (\(H_0\)): Stricter pollution regulations do not improve the AQI.

  • Alternative Hypothesis (\(H_a\) or \(H_1\)): Stricter pollution regulations improve the AQI.

Formulate Hypotheses

💭 Psychology Scenario: Testing whether mindfulness training reduces stress levels among participants.

  • Null Hypothesis (\(H_0\)): Mindfulness training has no effect on stress levels.

  • Alternative Hypothesis (\(H_a\) or \(H_1\)): Mindfulness training affects stress levels.

  • Null Hypothesis (\(H_0\)): Mindfulness training does not reduce stress levels.

  • Alternative Hypothesis (\(H_a\) or \(H_1\)): Mindfulness training reduces stress levels.

Formulate Hypotheses

🧬 Biology Scenario: Investigating whether a specific fertilizer increases plant growth compared to no fertilizer.

  • Null Hypothesis (\(H_0\)): The fertilizer has no effect on plant growth.

  • Alternative Hypothesis (\(H_a\) or \(H_1\)): The fertilizer affects plant growth.

  • Null Hypothesis (\(H_0\)): The fertilizer does not increase plant growth.

  • Alternative Hypothesis (\(H_a\) or \(H_1\)): The fertilizer increases plant growth.

Formulate Hypotheses

🚀 Technology Scenario: Examining whether a new smartphone app decreases the average time users spend on their phones daily.

  • Null Hypothesis (\(H_0\)): The app has no effect on the average time users spend on their phones.

  • Alternative Hypothesis (\(H_a\) or \(H_1\)): The app affects the average time users spend on their phones.

  • Null Hypothesis (\(H_0\)): The app does not decrease the average time users spend on their phones.

  • Alternative Hypothesis (\(H_a\) or \(H_1\)): The app decreases the average time users spend on their phones.

Formulate Hypotheses

💰 Economics Scenario: Testing whether increasing the minimum wage influences unemployment rates.

  • Null Hypothesis (\(H_0\)): Increasing the minimum wage has no effect on unemployment rates.

  • Alternative Hypothesis (\(H_a\) or \(H_1\)): Increasing the minimum wage affects unemployment rates.

  • Null Hypothesis (\(H_0\)): Increasing the minimum wage does not increase unemployment rates.

  • Alternative Hypothesis (\(H_a\) or \(H_1\)): Increasing the minimum wage increases unemployment rates.

Key Differences


Aspect Directional Hypothesis Non-Directional Hypothesis
Prediction Specifies the direction of the effect (e.g., increase, decrease). Predicts an effect but no specific direction.
Test Type One-tailed test Two-tailed test
Use Case When prior research or theory suggests a specific outcome. When unsure of the outcome’s direction.
Hypothesis Example \(H_a\): Group A scores are higher than Group B scores. \(H_a\): Group A scores are different from Group B scores.
Null Hypothesis (\(H_0\)) No effect in the predicted direction. No effect or difference.