Difference between revisions of "Category:BMI560-W-08"

From Clinfowiki
Jump to: navigation, search
Line 1: Line 1:
  
 +
Quantitative technique: One-Way Analysis of Variance (ANOVA)
 +
 +
Description:
 +
The analysis of variance is a partitioning of the total variance in a set of data into a number of component parts, so that the relative contributions of identifiable sources of variation to the total variation in measured responses can be determined. From this partition, suitable F-tests can be derived that allow differences between sets of means to be assessed.1
 +
 +
Thus ANOVA is a biostatistical method for determining whether a difference exists between the means of three or more independent populations. Expressed mathematically, it tests the null hypothesis- H0: 41 = 42 = 43  The one-way ANOVA parametric test will result in either accepting or rejecting this null hypothesis. If we reject the null hypothesis, then we can conclude that the population means are not equal. We do not know however whether all the means are different from one another or only some of them are different. This additional specificity is determined by conducting multiple comparison procedures, i.e. additional statistical tests.2
 +
 +
History:
 +
The phrase “analysis of variance” was coined by Sir Ronald Aylmer Fisher, a statistician of the twentieth century, who defined it as “the separation of variance ascribable to one group of causes from the variance ascribable to the other groups.”1
 +
 +
 +
[[Category:BMI560-W-08]]

Revision as of 05:50, 2 March 2008

Quantitative technique: One-Way Analysis of Variance (ANOVA)

Description: The analysis of variance is a partitioning of the total variance in a set of data into a number of component parts, so that the relative contributions of identifiable sources of variation to the total variation in measured responses can be determined. From this partition, suitable F-tests can be derived that allow differences between sets of means to be assessed.1

Thus ANOVA is a biostatistical method for determining whether a difference exists between the means of three or more independent populations. Expressed mathematically, it tests the null hypothesis- H0: 41 = 42 = 43 The one-way ANOVA parametric test will result in either accepting or rejecting this null hypothesis. If we reject the null hypothesis, then we can conclude that the population means are not equal. We do not know however whether all the means are different from one another or only some of them are different. This additional specificity is determined by conducting multiple comparison procedures, i.e. additional statistical tests.2

History: The phrase “analysis of variance” was coined by Sir Ronald Aylmer Fisher, a statistician of the twentieth century, who defined it as “the separation of variance ascribable to one group of causes from the variance ascribable to the other groups.”1