Explaining the effect of sample size
Explaining the effect of sample size.
- Probability = favourable outcomes ÷ all outcomes when individual outcomes are equally likely.
- A probability lies between 0 and 1; complementary probabilities sum to 1.
- Experimental relative frequency estimates probability and can vary between samples.
Example 1
Two pupils estimate the chance of heads with the same coin. One uses 20 tosses and the other 1000. Which estimate is generally more reliable?
A larger unbiased sample usually has less relative random variation. It does not guarantee an exact probability or remove bias from a flawed experiment.
Example 2
Two pupils estimate the chance of heads with the same coin. One uses 21 tosses and the other 1020. Which estimate is generally more reliable?
A larger unbiased sample usually has less relative random variation. It does not guarantee an exact probability or remove bias from a flawed experiment.
Your turn
Two pupils estimate the chance of heads with the same coin. One uses 22 tosses and the other 1040. Which estimate is generally more reliable?
Check answer
A larger unbiased sample usually has less relative random variation. It does not guarantee an exact probability or remove bias from a flawed experiment.
Two pupils estimate the chance of heads with the same coin. One uses 23 tosses and the other 1060. Which estimate is generally more reliable?
Check answer
A larger unbiased sample usually has less relative random variation. It does not guarantee an exact probability or remove bias from a flawed experiment.
Two pupils estimate the chance of heads with the same coin. One uses 24 tosses and the other 1080. Which estimate is generally more reliable?
Check answer
A larger unbiased sample usually has less relative random variation. It does not guarantee an exact probability or remove bias from a flawed experiment.
Two pupils estimate the chance of heads with the same coin. One uses 25 tosses and the other 1100. Which estimate is generally more reliable?
Check answer
A larger unbiased sample usually has less relative random variation. It does not guarantee an exact probability or remove bias from a flawed experiment.
Two pupils estimate the chance of heads with the same coin. One uses 26 tosses and the other 1120. Which estimate is generally more reliable?
Check answer
A larger unbiased sample usually has less relative random variation. It does not guarantee an exact probability or remove bias from a flawed experiment.
Two pupils estimate the chance of heads with the same coin. One uses 22 tosses and the other 1040. Which estimate is generally more reliable?
AnswerA larger unbiased sample usually has less relative random variation. It does not guarantee an exact probability or remove bias from a flawed experiment.
Two pupils estimate the chance of heads with the same coin. One uses 23 tosses and the other 1060. Which estimate is generally more reliable?
AnswerA larger unbiased sample usually has less relative random variation. It does not guarantee an exact probability or remove bias from a flawed experiment.
Two pupils estimate the chance of heads with the same coin. One uses 24 tosses and the other 1080. Which estimate is generally more reliable?
AnswerA larger unbiased sample usually has less relative random variation. It does not guarantee an exact probability or remove bias from a flawed experiment.
Two pupils estimate the chance of heads with the same coin. One uses 25 tosses and the other 1100. Which estimate is generally more reliable?
AnswerA larger unbiased sample usually has less relative random variation. It does not guarantee an exact probability or remove bias from a flawed experiment.
Two pupils estimate the chance of heads with the same coin. One uses 26 tosses and the other 1120. Which estimate is generally more reliable?
AnswerA larger unbiased sample usually has less relative random variation. It does not guarantee an exact probability or remove bias from a flawed experiment.