Sources Of Variation

Question 0

Explain confidence intervals

Answer 0

To allow for variations to occur, error factors are produced and from that confidence intervals
Confidence intervals - we can say with confidence that the true value lies within the range in 95% of cases

Question 1

Discuss how ‘observed’ epidemiological quantities depart from their ‘true’ values because of random variation

Answer 1

Variation - there is a difference between the observed and the actual value

Question 2

Explain how to calculate confidence intervals using the error factor

Answer 2

Lower 95% confidence limit: x/error factor
Upper 95% confidence limit: x x error factor
(where x = IR, IRR or SMR)
Error factors - d = number of cases

Question 3

Explain the null hypothesis

Answer 3

Default - “there is no relationship between the exposure and outcome”
Null hypothesis value = 1.0

Question 4

Explain the p value

Answer 4

The probability that the data observed is simply due to chance
If p>0.05 - we cannot reject the null hypothesis
If p<0.05 - we can reject the null hypothesis (data is statistically significant)

Question 5

Interpret a 95% confidence interval

Answer 5

If null hypothesis value lies within CI:
P>0.05
The results are not statistically significant and could be due to chance
Therefore we cannot reject the null hypothesis
If null hypothesis value lies outside CI:
P<0.05
The results are significantly different and unlikely to be due to chance
Therefore we can reject the null hypothesis