Lecture 3- Sampling

Question 1

Define sampling error

Answer 1

A sample that doesnt represent the population

Question 2

What does the p value represent

Answer 2

The probability that the null hypothesis is true.

The probability that an effect would be seen in a population where the null hypothesis is true.

Question 3

What is a type 1 and type 2 error

Answer 3

A type 1 error is when we think there is an effect but there actually isnt
A type 2 error is when we think that there isnt an effect but there actually is.

Question 4

What happens when you reject the null hypothesis

Answer 4

This means that the probability that there is no effect in the population is less than .05.

Question 5

What happens when you accept the null hypothesis

Answer 5

This means that the probability that there is no effect in the population is greater than .05.

Question 6

How does the p value relate to standard error

Answer 6

IF the standard error is small, we dont have a lot of deviation between our sample and the population.
Therefore its unlikely we have made a sampling error.
Therefore, chances we have an effect in our sample but not in the population (type 1) is low.

Question 7

Limitations of the p value

Answer 7

0.05 is an arbitrary number, encourages over reliance on finding results that are under the cut off.

Question 8

How much % does a significant outcome have of making error

Answer 8

5%