Hypothesis Testing Flashcards
(16 cards)
What is reliability
Reliability is how consistent a process is — you get the same results if repeated under the same conditions.
What is validity?
Validity is how accurate a process is — it correctly measures what it claims to measure.
Ways to improve reliability
• Increase sample size
• Repeat tests (test-retest or parallel forms)
• Use representative samples
Ways to improve validity
• Use random sampling to avoid bias
• Ensure no external factors affect what’s being measured
What is content-related validity?
Content-related validity checks how well a process measures all aspects of a variable.
• It requires expert knowledge of the variable.
• Valid example: A calculus test covering differentiation, integration, and applications.
• Not valid example: Asking people to report their own happiness levels (too subjective).
What is criterion-related validity?
Criterion-related validity checks how well one variable predicts the outcome of another variable (the criterion).
• Valid example: Mock exam results used to predict real exam results.
• Not valid example: Using meerkat heights to predict squirrel heights.
What are two ways to test for validity?
- Content-related validity (covers all aspects of a variable)
- Criterion-related validity (uses one variable to predict another)
What is test-retest reliability?
Test-retest reliability repeats the same process with the same sample at a later time.
• If results are positively correlated, the process is reliable.
• Differences may occur due to time gaps or learning effects.
What is parallel forms reliability?
Parallel forms reliability gives the same sample a second set of similar questions or tasks.
• If results are positively correlated, the process is reliable.
• It may be difficult to create two equally similar tests.
What are two ways to test for reliability?
- Test-retest (repeat same process with same sample later)
- Parallel forms (use a second, similar set of tasks/questions)
What is a type I error?
Probability of rejecting H0 when H0 is true (incorrectly rejecting H0)
What is a type II error?
Probability of accepting H0 when H0 is true, (incorrectly accepting H0)
Ways of reducing chance of Type I and Type II errors:
Type 1: decrease sig. level
Type 2: Increase sample size / increase significance level
Determine when we reject or accept H0 regarding:
1) p-value & sig levels
2) values inside or outside critical region
3) number being larger or smaller than critical value
1) p-val > sig level , don’t reject H0 / p-val < sig-level = reject H0
2) when value OUTSIDE of critical region DON’T REJECT H0 / when INSIDE c.r. = REJECT H0
3) if number LARGER than a critical value = REJECT H0, if number SMALLER than critical value = ACCEPT H0
Benefits for spearman’s rank coefficient rather than persons product moment
- less sensitive to outliers
- coefficient of determination unlikely to be linear (for some data)
What is the sum of square residual