Difference between revisions of "Inferential statistics"
| Line 1: | Line 1: | ||
| − | In many epidemiological studies, it is not possible to include every individual in a population. Rather, a [[Sampling strategies|sample]] of individuals is collected. This may be take the form of a [[Study design#Surveys|survey]], a [[Study design#Cross sectional studies|cross-sectional study]], a [[Study design#Experimental studies|randomised controlled trial]], and so on. The important issue is that '''not every individual in the [[Sampling strategies#Source population|source population]] is included, which means that [[Random error| random, or sampling, error]] and [[Bias|biases]] may be introduced. | + | In many epidemiological studies, it is not possible to include every individual in a population. Rather, a [[Sampling strategies|sample]] of individuals is collected. This may be take the form of a [[Study design#Surveys|survey]], a [[Study design#Cross sectional studies|cross-sectional study]], a [[Study design#Experimental studies|randomised controlled trial]], and so on. The important issue is that '''not every individual in the [[Sampling strategies#Source population|source population]] is included''', which means that [[Random error| random, or sampling, error]] and [[Bias#Selection bias|biases]] may be introduced. These affect our ability to extrapolate our results (whether [[Study design#Descriptive studies|descriptive]] or [[Study design#Analytic studies|analytic]] in nature) to the source population. However, the aim of most studies is to draw some conclusion about the source population, using the results obtained from the sample. This is known as '''inferential statistics''', and is a very important concept.<br> |
| + | '''Selection biases''' introduced during sample collection cannot be accounted for in the analysis, and so should either be avoided from the start, or discussed in the analysis report. Statistical methodology employed during analysis of sample data is aimed at accounting for '''random error''' in the sample. | ||
[[Category:Veterinary Epidemiology - Statistical Methods|D]] | [[Category:Veterinary Epidemiology - Statistical Methods|D]] | ||
Revision as of 13:52, 9 May 2011
In many epidemiological studies, it is not possible to include every individual in a population. Rather, a sample of individuals is collected. This may be take the form of a survey, a cross-sectional study, a randomised controlled trial, and so on. The important issue is that not every individual in the source population is included, which means that random, or sampling, error and biases may be introduced. These affect our ability to extrapolate our results (whether descriptive or analytic in nature) to the source population. However, the aim of most studies is to draw some conclusion about the source population, using the results obtained from the sample. This is known as inferential statistics, and is a very important concept.
Selection biases introduced during sample collection cannot be accounted for in the analysis, and so should either be avoided from the start, or discussed in the analysis report. Statistical methodology employed during analysis of sample data is aimed at accounting for random error in the sample.