Hypothesis — Previous Year Questions
📊 Topic Overview
| Metric | Value |
|---|---|
| Papers Appeared | 8 of 28 (28.6%) |
| Priority | 🟡 MEDIUM |
| Section Distribution | Sec A: 3 | Sec B: 4 | Sec C: 1 |
| Most Repeated | Types of hypothesis / difficulties in formulation (4 times) |
| Probability | Medium |
🎯 Must-Know Concepts
- Definition and significance of hypothesis
- Characteristics of a good hypothesis
- Types of hypothesis (research, null, alternative, directional, non-directional)
- Difficulties in formulating hypothesis
- Errors in hypothesis testing (Type I and Type II)
🔥 Key Question: Types of Hypothesis and Difficulties in Formulation (Section B)
Answer (~250 words):
Definition: A hypothesis is a tentative, testable proposition about the expected relationship between two or more variables. It translates the research question into a specific, predictive statement that can be empirically evaluated.
Types of Hypothesis:
| Type | Description | Example |
|---|---|---|
| Research (H₁) | Directional or non-directional prediction | "Cognitive therapy reduces anxiety more than medication" |
| Null (H₀) | States no relationship or no difference | "There is no difference in anxiety reduction between therapy types" |
| Directional | Predicts specific direction of effect | "Group A will score higher than Group B" |
| Non-directional | Predicts difference without specifying direction | "There will be a difference between Group A and Group B" |
| Alternative | Any hypothesis other than the null | Equivalent to research hypothesis in most contexts |
Characteristics of a Good Hypothesis:
- Testable — capable of empirical verification.
- Falsifiable — can be proven wrong by evidence.
- Precise — clearly identifies variables and expected relationship.
- Parsimonious — simple; avoids unnecessary complexity.
- Consistent with theory — grounded in existing knowledge.
- Limited scope — focused enough to be testable.
Difficulties in Formulating Hypothesis:
- Insufficient knowledge of existing literature — without adequate review, hypotheses may be redundant or theoretically unsound.
- Lack of conceptual clarity — vague constructs cannot yield precise predictions.
- Ethical constraints — some relationships cannot be studied directly (e.g., effects of abuse).
- Complexity of psychological phenomena — multiple interacting variables make single-variable predictions difficult.
- Absence of good measurement tools — if a construct cannot be reliably measured, hypotheses about it cannot be tested.
Errors in Hypothesis Testing:
| Error Type | Definition | Consequence |
|---|---|---|
| Type I (α) | Reject null when it is true (false positive) | Accepting an ineffective treatment |
| Type II (β) | Fail to reject null when it is false (false negative) | Missing a real effect |
Controlling Type I error is set by α level (usually .05); reducing Type II error requires adequate sample size (statistical power).
🧠 Memory Aids
Types of Hypothesis: R-N-D-ND-A (Research, Null, Directional, Non-directional, Alternative)
Type I vs II: "Type I: You Cry Wolf (false alarm). Type II: Miss the Wolf (miss real effect)."
📚 Related Content
✅ Self-Assessment
- What is the difference between a directional and non-directional hypothesis? Give an example of each.
- Why must a hypothesis be falsifiable?
- What is a Type I error and how is it controlled?
- List three difficulties researchers face in formulating hypotheses.
- When would a researcher use a null hypothesis vs a research hypothesis?
💡 Exam Tips
- Section B format: definition → types (table works well) → characteristics → difficulties → errors.
- Type I and Type II errors are often tested as a short note — memorise both definitions clearly.
- Always link the concept of hypothesis to the broader research process.