An analysis of variance (ANOVA) statistical technique is conducted to examine differences between two or more groups.

An analysis of variance (ANOVA) statistical technique is conducted to examine differences between two or more
groups.

ANALYSIS OF VARIANCE. PLEASE ANSWER QUESTIONS TO BE GRADED..

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EXERCISE 36 ANALYSIS OF VARIANCE (ANOVA) I

STATISTICAL TECHNIQUE IN REVIEW

An analysis of variance (ANOVA)
statistical technique is conducted to examine differences between two or more
groups. There are different types of ANOVA, with the most basic being the one-way
ANOVA, which is used to analyze data in studies with one independent and
one dependent variable. More details on the types of ANOVA can be found in your
research textbook and statistical texts (Burns & Grove, 2005; Munro, 2001).
The outcome of ANOVA is a numerical value for the F statistic. The
calculated F-ratio from ANOVA indicates the extent to which group means
differ, taking into account the variability within the groups. Assuming the
null hypothesis of no difference among groups is true; the probability of
obtaining an F-ratio as large or larger than that obtained in the given
sample is indicated by the calculated p value. For example, if p
= 0.0002, this indicates that the probability of obtaining a result like this
in future studies is rare, and one may conclude that group differences exist
and the null hypothesis is rejected. However, there is always a possibility
that this decision is in error, and the probability of committing this Type I
error is determined by the alpha (a) set for the study, which is usually 0.05
that is smaller in health care studies and occasionally 0.01.

ANOVA is similar to the t-test
since the null hypothesis (no differences between groups) is rejected when the
analysis yields a smaller p value, such as p = 0.05, than the
alpha set for the study. Assumptions for the ANOVA statistical technique
include:

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