S3 Intro to Key Stastical Concepts

Question 1

What is the difference between truth and observed results? Give an example in terms of flipping a coin

Answer 1

The true probability is what you expect to see based of stats but the observed probability may be different due to random variation

The true probability of getting a tail on a fair coin is a half, but what we observe may depart from this by random variation

Question 2

What is a hypothesis?

Answer 2

A statement that an underlying truth of scientific interest takes a particular quantitative value

Question 3

What is hypothesis testing?

Answer 3

Calculate the probability of getting an observation as extreme as, or more extreme than, the one observed assuming the hypothesis is true

Question 4

What is the calculated probability called (in terms of hypothesis)?

Answer 4

P-value

In most cases this is 0.05

Question 5

What are the limitations of hypothesis testing?

Answer 5

• rejecting the hypothesis isn’t always useful - depends on the same size, the p value is arbitrary (very little difference between 0.049 and 0.051 and if it is statistically significant, it doesn’t mean it’s clinically important

Question 6

What is the 95% confidence interval?

Answer 6

The range within which we can be 95% certain that the true value of the underlying truth really lies.

It is centres on the observed value because it’ss our best guess of the true underlying value

Question 7

What is the p-value if the null hypothesis lies inside the 95% confidence interval and outside this interval?

Answer 7

Inside - p is more than or equal to 0.05

Outside - p is less then 0.05