Probability and Sigifigance

Question 1

What is Probability?

Answer 1

Likelihood that something will happen.
Probability = Number of particular outcomes ÷ Total number of outcomes

Example:
Forecast correct 4/10 days → Probability = 0.4

Question 2

Probability in Psychology

Answer 2

Probability that results occurred by chance.
We want P to be as low as possible.
Common threshold: p < 0.05
→ Only a 5% chance the results are due to chance.

Question 3

When Are Results Significant?

Answer 3

Probaibility < 0.05 → Results significant. Reject null hypothesis, Accept experimental hypothesis.

If p > 0.05 → Results not significant
→ Accept null, Reject experiment

Question 4

Why Use p < 0.05?

Answer 4

It’s a balance between being too lenient or too strict.

Helps reduce Type I and Type II errors.

Question 5

Type I Error

Answer 5

False positive.

Rejecting the null when it was actually true.

Saying there is an effect when there isn’t.

Caused by being too lenient (e.g., p = 0.10).

Question 6

Type II Error

Answer 6

False negative.

Accepting the null when it’s actually false.

Saying there’s no effect when there actually is.

Caused by being too strict (e.g., p = 0.01).

Question 7

Calculated vs Critical Values

Answer 7

After a statistical test → get a calculated value

Compare with critical value from a table.

If calculated ≥ critical → results are significant

Question 8

Using Critical Value Tables

Answer 8

Type of test: one-tailed or two-tailed

Number of participants (or degrees of freedom)

Chosen significance level (usually p < 0.05)