Results 201 to 210 of about 754,985 (219)
Some of the next articles are maybe not open access.
Chemometrics and Intelligent Laboratory Systems, 1989
Abstract Univariate ANOVA is reviewed from a user point-of-view with emphasis on understanding the model building and the assumptions underlying the method. Illustrative examples are taken from organic chemistry and analytical chemistry. The use of graphical techniques to visualize the ANOVA model as well as to analyse residuals is recommended.
Lars St»hle, Svante Wold
openaire +1 more source
Abstract Univariate ANOVA is reviewed from a user point-of-view with emphasis on understanding the model building and the assumptions underlying the method. Illustrative examples are taken from organic chemistry and analytical chemistry. The use of graphical techniques to visualize the ANOVA model as well as to analyse residuals is recommended.
Lars St»hle, Svante Wold
openaire +1 more source
2002
ANalysis Of VAriance (ANOVA), or F-test, is an extension of the independent groups t-test. Analysis of variance is a more general statistical procedure than the groups t-test. You will remember that the t-test was used when we had two levels of the independent variable (males and females) and we wanted to see how the groups differed on a interval/ratio
Robert L. Miller +4 more
+4 more sources
ANalysis Of VAriance (ANOVA), or F-test, is an extension of the independent groups t-test. Analysis of variance is a more general statistical procedure than the groups t-test. You will remember that the t-test was used when we had two levels of the independent variable (males and females) and we wanted to see how the groups differed on a interval/ratio
Robert L. Miller +4 more
+4 more sources
2014
In the last chapter, we were able to compare two population means using either the large sample Z test or the two-sample t test. Analysis of variance (that is, analysis based on the variation in the data) often written as “ANOVA” concerns how to test the means of more than two populations.
openaire +2 more sources
In the last chapter, we were able to compare two population means using either the large sample Z test or the two-sample t test. Analysis of variance (that is, analysis based on the variation in the data) often written as “ANOVA” concerns how to test the means of more than two populations.
openaire +2 more sources
1986
In the last chapter we explained how it was possible to test whether two sample means were sufficiently different to allow us to conclude that the samples were probably drawn from populations with different population means. When more than two different groups or experimental conditions are involved we have to be careful how we test whether there might
openaire +1 more source
In the last chapter we explained how it was possible to test whether two sample means were sufficiently different to allow us to conclude that the samples were probably drawn from populations with different population means. When more than two different groups or experimental conditions are involved we have to be careful how we test whether there might
openaire +1 more source