Probability

The video tutorial covers the concept of probability and its central role in inferential statistics. It explains how statistical significance is determined and the importance of the null hypothesis. The tutorial also discusses the probability of events, using examples like coin tosses, and explains the common significance level used in psychology. Additionally, it covers type I and type II errors, illustrating them with real-world analogies to clarify the concepts of false positives and false negatives.

What is the primary goal of inferential statistics?

• To collect data

• To describe data

• To visualize data

• To determine statistical significance

In psychology, what is the most common level of significance used?

• 10% or 1 in 10

• 1% or 1 in 100

• 20% or 1 in 5

• 5% or 1 in 20

What does the 'p' in p-value stand for?

• Percentage

• Probability

• Proportion

• Prediction

What is a type I error also known as?

• False negative

• True negative

• True positive

• False positive

Which error occurs when the null hypothesis is accepted despite significant results?

• Type III error

• Type II error

• Type I error

• Type IV error