The precision of the findings.This is the range within which the predicted means of population may lie.
A confidence interval is the range of values within which the "actual" gods-own-truth result is found. Essentially, a CI of 95% means that if a trial was repeated an infinite number of times, 95% of the results would fall within this range of values.
- 95% of sample means should lie between 1.96 standard error of the mean above & below their sample mean.
- if the sample should represent the 95% CI for the population mean if:
- the sample was large enough
- the sample is evenly distributed
- the sample was selected randomly
- The CI gives an indication of the precision of the sample mean as an estimate of the "true" population mean
- A wide CI can be caused by small samples or by a large variance within a sample.
The probability of the observed result arising by chance
The p-value is the chance of getting the reported study result (or one even more extreme) when the null hypothesis is actually true.
For example, if your findings are that 1g of oral cyanide kills 95% of swallowers, a p-value of 0.05 would suggest that if cyanide was completely harmless and you repeated your experiment an infinite number of times, your results would be reproduced in 5% of those experiments.
Thus, a very small p-value - say, 0.0001- gives rise to the impression that the results are valid, because it suggests that if the investigator's hypothesis was in fact completely wrong, the chances of arriving accidentally at their "mistaken" results would be 0.1%.